Difference between revisions of "CHIRPS Reality Checks"
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'''CHIRPS v2.0 monthly Reality Checks''' | '''CHIRPS v2.0 monthly Reality Checks''' | ||
− | == | + | CHIRPS Reality Checks (rchecks) occur across the many steps to create CHIRPS and on the final product itself. |
+ | |||
+ | [[File:realitychecks.source.legend.3.png|right|Legend for Reality Check station icons]] | ||
+ | |||
+ | == Background == | ||
A team of data analysts routinely quality check each month’s CHIRPS data before its release. | A team of data analysts routinely quality check each month’s CHIRPS data before its release. | ||
− | This page documents major points of these Reality Checks. | + | This page documents major points of these Reality Checks. The [http://wiki.chg.ucsb.edu/wiki/CHIRPS_Reality_Checks#Rchecks_Highlights Rchecks Highlights] section contains information that CHIRPS users may find helpful, for example, notes about major rainfall events shown by the data and validation for some. |
− | major rainfall | + | |
Rcheck is a hands-on approach that helps enable a quality product for hazards monitoring and other scientific activities. In Reality Checks we examine the data visually via the Early Warning Explorer and separately using calculated statistics. Ancillary information, such as FEWS NET datasets, news reports, and government meteorological reports, are frequently used in the process. Rchecks has been successful in: 1) Validating anomalous wet and dry events around that world as shown by CHIRPS, 2) catching inaccurate station reports that would have otherwise negatively influenced the dataset, such as creating false droughts, 3) checking that the semi-automated flow CHIRPS data creation is working correctly, 4) identifying weaknesses and strengths of the algorithm and data inputs, which helps in planning improvements in future versions. | Rcheck is a hands-on approach that helps enable a quality product for hazards monitoring and other scientific activities. In Reality Checks we examine the data visually via the Early Warning Explorer and separately using calculated statistics. Ancillary information, such as FEWS NET datasets, news reports, and government meteorological reports, are frequently used in the process. Rchecks has been successful in: 1) Validating anomalous wet and dry events around that world as shown by CHIRPS, 2) catching inaccurate station reports that would have otherwise negatively influenced the dataset, such as creating false droughts, 3) checking that the semi-automated flow CHIRPS data creation is working correctly, 4) identifying weaknesses and strengths of the algorithm and data inputs, which helps in planning improvements in future versions. | ||
− | == '''Helpful Links''' == | + | === Historic vs Operational rchecks === |
− | + | ||
+ | There are two basic types of rchecks: historic and operational. | ||
+ | *'''Historical''': Historic looks across the whole timeseries of CHIRPS (1981-present) | ||
+ | |||
+ | *'''Operational''': Operational is designed to spot check our products are they are produced. | ||
+ | **Does this station value fall within expected range? | ||
+ | **Do the anomaly fields have a reasonable distribution? (not all negative) | ||
+ | |||
+ | === View individual stations time series === | ||
+ | |||
+ | * The center pixel of the station's 11x11 pixel representation is assigned the anchor station's sequence number in the CSCD1 database. Clicking on this pixel in the EWX will list the seqnum in the lower left corner of the map pane. Note that this may not be the station that was actually used if there was missing data and a nearby station filled in the value. The source seqnum of the station can be obtained with the follow SQL command: | ||
+ | **select * from station where seqnum=xxx | ||
+ | **then the source seqnum can be used to get the name of the source like this: | ||
+ | **select * from source where seqnum=xxx | ||
+ | **then precipitation table can be selected from the following list of precip tables: | ||
+ | **daily_precip_conagua | ||
+ | **daily_precip_fgsod | ||
+ | **daily_precip_fits | ||
+ | **daily_precip_ghcn | ||
+ | **daily_precip_ideam | ||
+ | **daily_precip_sasscal | ||
+ | **then the following command will return the station time series: | ||
+ | **select * from daily_precip_sasscal where station_seqnum=xxx order by date desc | ||
+ | **Note that the filled value is the precipitation value that is used in CHIRPS. This is the sum of the daily "value" column with any missing data filled in with the mean of the values that do exist in the table. | ||
+ | |||
+ | == Helpful Links == | ||
+ | |||
+ | [[File:realitychecks.source.legend.3.png|thumb|150px|right|Legend for Reality Check station icons]] | ||
+ | |||
+ | The following are resources that are helpful for conducting monthly CHIRPS Reality Checks. These include links to CHC resources (e.g. data viewers & details from Rchecks) and other products that are used for comparisons. | ||
+ | |||
+ | '''CHC resources''' | ||
+ | *[https://docs.google.com/spreadsheets/d/1GK86wSQdJwMp6Sa-ySvOM7fP_StVG0xmVg9Iv_b_gxk/edit?ts=5716aea2#gid=0 '''*** R Checks STATION WATCHLIST ***'''] | ||
+ | *[ftp://ftp.chg.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/chirps-n-stations_byCountry/ '''CHIRPS station locations by country'''] | ||
+ | * [https://ewx3.chc.ucsb.edu/ewx/ '''EWX viewer'''] | ||
+ | |||
+ | '''Global products''' | ||
+ | *[http://chrsdata.eng.uci.edu/ ''Global'' '''PERSIANN data viewer'''] Suggestion: Compare CHIRPS to Monthly PERSIANN, PERSIANN-CCS, and PERSIANN-CDR totals | ||
+ | |||
+ | *[https://www.accuweather.com/ ''Global'' '''Accuweather rainfall stations'''] Suggestion: Search for a nearby city and the click the month button, then select the month and then the settings button (last on right) to see daily precip totals | ||
+ | |||
+ | *[http://www.cpc.ncep.noaa.gov/products/international/index.shtml <!-- PAGE HAS MOVED http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/--> ''Global'' '''NOAA Climate Products''']: Choose zone of the world for special products (Central Asia, South Asia, Africa, Central America & Caribbean) | ||
+ | *[http://earlywarning.usgs.gov/fews ''Global'' '''FEWS Data Portal'''] | ||
+ | *[https://public.wmo.int/en ''WMO'' '''Links to other National Met Services''']: | ||
+ | *[https://en.climate-data.org ''Climate-Data.org'' '''Website with climatology info.'''] Googling a city name + climatology might be helpful also | ||
+ | |||
+ | '''Africa products''' | ||
+ | *[ftp://ftp.cpc.ncep.noaa.gov/fews/threats/ ''Africa'' '''FEWS Archived Hazards/Threats'''] | ||
+ | * [http://www.icpac.net/index.php ''East Africa'' '''IGAD website'''] | ||
+ | * [http://www.meteo.go.ke/index.php?q=crop ''Kenya'' '''Kenya Met Department''']. Here is a link to [https://meteo.go.ke/forecast/agrometeorological-bulletins dekadal monitoring reports] https://meteo.go.ke/forecast/agrometeorological-bulletins. | ||
+ | *[http://www.ethiometmaprooms.gov.et:8082/maproom/Climatology/#tabs-1 ''Ethiopia'' '''NMA Maproom'''] | ||
+ | *[http://www.anacim.sn/ ''Senegal'' '''ANACIM''']: [http://www.anacim.sn/wp-content/uploads/2017/01/cumul_pluviometrie Seasonal rainfall accumulation] [http://www.anacim.sn/wp-content/uploads/2017/01/comparaison_normale Seasonal rainfall anomaly] | ||
+ | |||
+ | '''Central and South America products''' | ||
+ | *[http://www.cpc.ncep.noaa.gov/products/international/camerica/camerica.shtml ''Central America and Caribbean'' '''CMORPH precipitation and more'''] | ||
+ | *[http://www.cpc.ncep.noaa.gov/products/international/samerica/samerica.shtml ''South America'' '''CMORPH precipitation and more'''] | ||
+ | *[ftp://ftp.cpc.ncep.noaa.gov/fews/cent_amer_threats/ ''Central America'' '''FEWS Archived Hazards/Threats'''] | ||
+ | *[http://www.inmet.gov.br/portal/index.php?r=home2/index ''Brazil'' '''INMET''']: Click the Mapas de Precipitacao tab and then the Plus button at the bottom of the map and an end date and time period can be selected (30 dias). | ||
+ | *[http://www.smn.gov.ar/serviciosclimaticos/?mod=hidro&id=1 ''Argentine'' '''Servicio Meteorologico Nacional''']: Click on Precipitacion Observada or Precipitación Estimada links. | ||
+ | |||
+ | '''Asia products''' | ||
+ | *[http://www.cpc.ncep.noaa.gov/products/international/sasia/sasia.shtml ''South Asia'' '''RFE2.0 precipitation and more'''] | ||
+ | *[http://www.ndmc.pmd.gov.pk/index.htm ''Pakistan'' '''National Drought Monitoring Centre''']: Maps of monthly rainfall, anomalies, and SPI to compare to. | ||
+ | *[http://hydro.imd.gov.in/hydrometweb/(S(2bcd2t55pggpi4ecfde2zf55))/landing.aspx ''India'' '''CRIS from India Met Dept''']: Variety of products. Rainfall graphs helpful b/c many maps show cumulative rains over month+ periods. | ||
+ | |||
+ | ==Rchecks Highlights== | ||
+ | |||
+ | === September 2024 === | ||
+ | |||
+ | '''Central Europe''' In mid-September, Storm Boris swept through central Europe and dumped well over a month’s worth of rain within several days. Authorities reported that they recorded the heaviest rainfall in 100 years on September 15th. At least 17 people were killed during the floods in Austria, Poland, the Czech Republic and Hungary. More information about Storm Boris is available [https://www.cnn.com/2024/09/16/weather/storm-boris-floods-europe-intl/index.html here]. | ||
+ | |||
+ | '''Hungary''' Despite reports of record-high rainfall throughout the region, monthly rainfall totals at Hungary stations were slightly below-average throughout the entire country. These are all GTS stations. The resulting map of precipitation anomalies shows Hungary as a pocket of below-normal rainfall surrounded by highly above-average rains. With station values overlaid, one can clearly see a difference between stations within Hungary's border and stations outside the border. We elected to exclude Hungary rainfall stations from CHIRPS final for this month. | ||
+ | |||
+ | '''Morocco, Algeria, Tunisia, and Libya''' CHIRPS shows above-average rainfall in these areas due to satellite and station inputs. A [https://earthobservatory.nasa.gov/images/153320/a-deluge-for-the-sahara NASA article] names the cause as an extratropical cyclone that brought substantial rain during Sep 7th and 8th. Satellite imagery shows that the rain filled up desert lakes in the northwestern Sahara that are usually dry. | ||
+ | |||
+ | '''Rchecks plots''' Stats fall with normal ranges with the exception of the Great Lakes region. There are a large number of stations reporting high negative z-scores throughout this area. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' [https://data.chc.ucsb.edu/people/will/Requests/R_Checks/CHIRPS_minus_Prelim/archive/Difference_global_202409.png This map] shows the difference between Prelim data and Final data, for September 2024. | ||
+ | |||
+ | === August 2024 === | ||
+ | |||
+ | '''Mali, Niger, Chad''' Stations captured extreme August rainfall in Mali, Niger, Chad, and elsewhere in the Sahel. High above-normal seasonal rainfall has flooded rivers and communities, leading to many fatalities and severe damages to infrastructure. OCHA describes the August 2024 flooding in West and Central Africa as follows: "In the last two weeks of August alone, 1,590,000 people were affected in the region. The heavy rains recorded in this two-week period affected 12 countries, 7 in terms of displacement of population and 11 for houses destroyed or damaged. From 15 to 30 August, 465 people were reportedly killed and 1,747 others injured. Between 15 and 30 August, an additional 354,000 hectares of agricultural land were affected, making a total area of 380,000 hectares unsuitable for agricultural and livestock production" [https://reliefweb.int/report/chad/west-and-central-africa-flooding-situation-overview-6-september-2024 -September 6th situation overview]. According to various sources, over 50 people have been killed and close to a million people affected in Mali. In [https://floodlist.com/africa/niger-floods-september-2022 Niger], at least 94 people have been killed, and more than 137,000 have been displaced due to flooding. The flooding damaged homes and classrooms and resulted in the death of more than 15,000 livestock. In Chad, where impacts have been most severe, at least 341 people have died and 1.5 million have been affected. | ||
+ | |||
+ | '''Somalia''' FAO SWALIM station reports are a very important source of accurate CHIRPS rainfall estimation in Somalia. This source has provided reports into CHIRPS for the past 8 years. SWALIM was not able to provide reports for August 2024 CHIRPS data. | ||
+ | |||
+ | '''Cuba''' High rainfall amounts are estimated by CHIRPS due mainly to the blending of stations. A station in western Cuba (580 mm) had particularly large influence, and while CHIRP (satellite estimates) were above average, estimated amounts were lower (~250-300mm). The high August 2024 rainfall is consistent with impacts from Tropical Depression 4, which crossed over the area on August 3rd. | ||
+ | |||
+ | ''' Brazil''' A recurring problem with station reports, identified by Rchecker Seth, is in need of attention. There are numerous stations being identified manually in Rchecks that appear to be too low. Based on evaluation of nearby stations that align with satellite estimates. The issue has been addressed in the past by flagging and permanent omission of certain stations from CHIRPS blending process. At minimum, this will need to happen again. However, introducing an automated filter- crafted especially for this source- is a potential solution that will be discussed. This would be a valuable addition for final CHIRPS v3 historical and ongoing data production. | ||
+ | |||
+ | '''Rchecks plots''' All stats are within a normal range. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' [https://data.chc.ucsb.edu/people/will/Requests/R_Checks/CHIRPS_minus_Prelim/archive/Difference_global_202408.png This map] shows the difference between Prelim data and Final data, for August 2024. | ||
+ | |||
+ | === July 2024 === | ||
+ | |||
+ | '''South Africa''' Southwestern Africa (near Cape Town) had very heavy storms, damage, flooding during July 2024. More on the impacts, which displaced 4,500 people, can be read [https://www.usnews.com/news/world/articles/2024-07-11/south-africas-cape-town-is-hit-by-more-storms-with-4-500-people-displaced-by-floods-and-damage here]. CHIRPS is showing this anomalous high rainfall, due to the blending of 20+ stations in this area. The station reports greatly increased CHIRPS compared to CHIRP (satellite-only estimates). | ||
+ | |||
+ | '''Panama''' Only 2 stations reported, which is far less than [https://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/stations-perMonth-byCountry/pngs/Panama.129.station.count.CHIRPS-v2.0.png high station count] that we've had during 2023 to 2024. | ||
+ | |||
+ | '''Brazil''' Rchecker Seth continues to find numerous stations in Brazil are reporting too-low rainfall. For July 2024, he identified 35 stations. These were omitted from CHIRPS Final. | ||
+ | |||
+ | '''Rchecks plots''' There is a new hit CHIRPS maximum, standard deviation and anomaly max in Southern Africa. However, these were verified by news reports from Cape Town. There is also a new high for global CHIRPS - CHIRP but by a very small margin. All else looks bueno. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' [https://data.chc.ucsb.edu/people/will/Requests/R_Checks/CHIRPS_minus_Prelim/archive/Difference_global_202407.png This map] shows the difference between Prelim data and Final data, for July 2024. | ||
+ | |||
+ | === June 2024 === | ||
+ | |||
+ | '''Saudi Arabia''' Two stations reported moderate rainfall in the desert. These were retained in CHIRPS due to [https://english.alarabiya.net/News/saudi-arabia/2024/06/17/muslim-pilgrims-mark-final-days-of-hajj-amid-extreme-heat news reports] of rainfall in Mina in June 2024. | ||
+ | |||
+ | '''Panama''' Numerous stations report over 600 mm of rain and some are 1000+ mm. These are included and substantially increase CHIRPS values, compared to CHIRP. No news reports of flooding were discovered. | ||
+ | |||
+ | '''Brazil''' Rchecker Seth continues to find numerous stations in Brazil are reporting too-low rainfall. For June 2024, he identified ~60 stations. These were omitted from CHIRPS Final. | ||
+ | |||
+ | '''Rchecks plots''' The South American region contained a new CHIRPS maximum high value of over 2000mm. Previous highs are all under 1500mm. A new anomaly high was also calculated there. Otherwise, all stats fall withing previous boundaries. | ||
+ | |||
+ | === May 2024 === | ||
+ | |||
+ | '''Switzerland and Italy''' Automated checks removed a series of large station values from southern Switzerland and northern Italy. However, during reality checks these stations were added back in to CHIRPS, as they correctly identified [https://www.bbc.com/news/articles/c9xz8w2p8l8o reported heavy rainfall events] that led to flooding throughout the area. | ||
+ | |||
+ | '''Brazil and Uruguay''' In southern Brazil and Uruguay, the stations included in CHIRPS captured heavy rains that led to severe flooding. According to [[https://www.msf.org/unprecedented-flooding-brazil-leaves-millions-affected-and-hundreds-thousands-displaced a report from MSF news], "The extreme rainfall and flooding that hit the southern Brazilian state of Rio Grande do Sul isolated and forced the evacuation of whole cities. Roads have been destroyed, bridges knocked out and the main airport, in the capital city of Porto Alegre, is indefinitely closed. More than 460 state municipalities, out of a total of 497, have been hit." CHIRP estimates, in the 200 mm range for the month, were much lower than the values reported at stations, which reached as high as 800 mm. This highlights the importance of in situ observations for accurate depictions of extreme rainfall in gridded satellite rainfall data products. | ||
+ | |||
+ | '''India and Bangladesh''' In late May Cyclone Remel hit the coasts of India and Bangladesh and dumped approximately 89 mm of rain, according to [https://www.cnn.com/2024/05/26/india/cyclone-remal-india-bangladesh-landfall-intl-hnk/index.html news reports]. CHIRP and CHIRPS both estimated above average rainfall for May 2024. The stations included in CHIRPS widened the area of estimated anomalous rainfall. | ||
+ | |||
+ | '''Rchecks plots''' All statistics ranged within normal bounds except the Latin American region, Z-score mean, which is a recorded a low of -0.9. This is corroborated in a report by the [https://reliefweb.int/report/el-salvador/el-salvador-honduras-and-nicaragua-key-message-update-delayed-rainfall-onset-will-extend-annual-lean-season-may-2024 Relief Web International] about delayed onset of seasonal rains. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202405/CHIRPS_diff_GLB_PR_202405.png] shows the difference between Prelim data and Final data, for May 2024. | ||
+ | |||
+ | === April 2024 === | ||
+ | |||
+ | '''Afghanistan and Pakistan''' Stations blended into CHIRPS captured extreme rainfall values in mid-May that led to [severe flooding, destruction, and loss of life https://floodlist.com/asia/afghanistan-floods-may-2024] in Afghanistan and Pakistan. Of the satellite-only products, IMERG late v6 outperformed CHIRP in capturing the extreme rainfall. | ||
+ | |||
+ | '''United States''' CHIRP underestimated rainfall in the Midwest, from Missouri to Pennsylvania. Station values blended into CHIRPS brought up the values 2 to 3 times higher. IMERG late v6 captured the amounts relatively better than CHIRP. | ||
+ | |||
+ | '''Rchecks plots''' All stats look good. High CHIRPS values and anomalies meet previous highs but still within reasonable ranges | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202404/CHIRPS_diff_GLB_PR_202404.png] shows the difference between Prelim data and Final data, for April 2024. | ||
+ | |||
+ | === March 2024 === | ||
+ | |||
+ | '''Swaziland''' Multiple stations in southern Mozambique reported very high rainfall values, associated with impacts from Tropical Storm Filipo. According to OCHA, "...heavy rains in Maputo city and province affected 93,240 people. A few days earlier, Tropical Storm Filipo had already impacted 57,178 people in Sofala, Inhambane, Gaza and Maputo provinces." ([https://www.unocha.org/publications/report/mozambique/mozambique-maputo-heavy-rains-and-tropical-storm-filipo-flash-update-no-3-28-march-2024 March 28, 2024 OCHA]). CHIRP estimates were much lower; the blended stations markedly increased CHIRPS final values. Several of these stations had a large effect on CHIRPS v2 in the region, particularly Swaziland, because they are included in the 2nd step of a two-step blending procedure. That effect is reduced in v3.2 beta version, which uses an improved single blending procedure. | ||
+ | |||
+ | '''Australia''' CHIRPS shows the impacts of Tropical Cyclone Megan that hammered the northern territories in mid-March. CHIRP predicted ~400mm, CHIRPS ~700mm. | ||
+ | |||
+ | '''Rchecks plots''' All statistics look within normal ranges with the exception of South America where CHIRPS max reached an unusual new high but not out of a reasonable range. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202403/CHIRPS_diff_GLB_PR_202403.png (soon will be here)] shows the difference between Prelim data and Final data, for March 2024. | ||
+ | |||
+ | === February 2024 === | ||
+ | |||
+ | '''Southern Africa drought''' CHIRPS Final shows extremely dry conditions in a large area spanning major maize production areas in southern Zambia and Zimbabwe, and in southeastern Angola, southern Malawi, and eastern Botswana. A severe dry spell occurred during late January and February, and the minimal to no rains and above-average hot temperatures led to widespread crop failures. [https://www.aljazeera.com/news/2024/2/29/zambia-declares-national-disaster-after-drought-devastates-agriculture Zambia declared a national disaster] due to the loss of approximately 1 million hectares of maize crops- about half of their planted areas. The timing of the dry spell coincided with yield-sensitive development stages. In some areas, below-average rainfall in November to early December, 2023, had also forced some farmers in the region to plant a month later than usual. The CHIRPS preliminary data for February 2024 provided early indication that rainfall during this period was extremely low. Very poor rains were confirmed by station reports and FEWS NET/USDA FAS interviews and field visits. In Zimbabwe, ~30 stations reported very low rainfall, many of which ranged from near zero to less than 40 mm for the month. This is just a fraction of typical rainfall in February (~ 150 mm at many of these). Upon the inclusion of these (plus stations from SASSCAL and other sources) into CHIRPS Final, [https://data.chc.ucsb.edu/products/CHIRPS-2.0/moving_06pentad/pngs/africa_southern/archive/Rank_06PentAccum_2024_p12.png worst on record] and close-to worst rankings are indicated for many locations across central Southern Africa. CHIRPS Final shows [https://data.chc.ucsb.edu/products/CHIRPS-2.0/moving_06pentad/pngs/africa_southern/archive/PON_06PentAccum_2024_p12.png less than 30% of average] February rainfall in southern Zambia, Zimbabwe, Namibia's Caprivi Strip, Botswana, western Mozambique, and southeastern Angola. | ||
+ | |||
+ | '''Italy''' Heavy, above average rainfall was recorded throughout northern Italy. A strong storm brought heavy rainfall and flooding to the cities of Milan, Veneto, Emilia-Romagna, and Vicenza. Some areas recorded 188mm in 24 hours. According to reports, the storm was reminiscent of Storm Vaia in 2018 and the 'Great Flood of 2010.' See [https://www.ansa.it/english/news/general_news/2024/02/28/extreme-weather-batters-italy-red-alert-in-veneto_b81d8afb-8a38-475c-8ad2-011ae9677b55.html this link] for more about this event. | ||
+ | |||
+ | '''South Africa''' After incorporating station data in the area, the CHIRPS Final product shows that February 2024 rainfall was below average across most of South Africa, Lesotho, and eSwatini. Satellite-based estimates (CHIRP and IMERG-Late) overestimated rains in eSwatini and northeastern South Africa (Mpumalanga, northern Free State, Gauteng, Limpopo, North West). Based on reports from South Africa (from stations, interviews, and field visits from FEWS NET/ USDA FAS), the dry conditions in February 2024 negatively impacted rainfed maize. Moisture and heat stress had disrupted cob formation and grain filling in some areas, introducing concerns about impacts on seasonal yields and maize quality in affected areas. | ||
+ | |||
+ | '''Brazil''' Rchecks/Seth omitted a large number of stations that made it into the pre-release CHIRPS Final but had rainfall values that appeared to be unrealistic. Of these, 62 stations had values that were identified as being too low and 5 were too high, based on the timing, location, and disagreement from neighboring station reports. | ||
+ | |||
+ | '''Rchecks plots''' All statistics look within normal ranges. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202402/CHIRPS_diff_GLB_PR_202402.png here] shows the difference between Prelim data and Final data, for February 2024. | ||
+ | |||
+ | === January 2024 === | ||
+ | |||
+ | '''Zimbabwe''' Impressive station coverage in Zimbabwe for January 2024. You can see maps of monthly CHIRPS with station locations overlaid here: [https://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/chirps-n-stations_byCountry/Zimbabwe/Zimbabwe.2024.01.png Jan 2024], [https://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/chirps-n-stations_byCountry/Zimbabwe/Zimbabwe.2023.12.png Dec 2023], and for [https://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/chirps-n-stations_byCountry/Zimbabwe/Zimbabwe.2023.01.png Jan 2023]. Beginning in December 2023, the Meteorological Services Department of Zimbabwe began providing 35+ station reports to CHIRPS, and in Jan 2024 there was also a notable increase in the number of GTS stations passing quality control and being blended into CHIRPS (10). In past years, oftentimes these GTS stations have not reported enough days in the month to pass. The recent increase in number of stations in Zimbabwe is exciting for CHIRPS producers and users. The v2 processing involves a two-step blending process, with newer sources being blended in the 2nd step. This means that some of these stations (co-located met agency & GTS) are included in both steps in Jan 2024 CHIRPS v2. The duplicate station and 2nd blending processes will not used in CHIRPS v3. | ||
+ | |||
+ | '''Argentina''' A couple of stations reported very high rainfall totals, likely associated with the [https://crisis24.garda.com/alerts/2024/01/argentina-disruptions-due-to-flooding-ongoing-in-parts-of-cordoba-province-jan-7 flooding in Cordoba province]. These stations had only a minor effect on CHIRPS Final v2. | ||
+ | |||
+ | '''Sri Lanka''' Stations data blended into CHIRPS Final v2 captured the heavy rain that led to [https://reliefweb.int/report/sri-lanka/sri-lanka-heavy-rain-and-floods-update-dg-echo-dmc-meteo-sri-lanka-media-echo-daily-flash-12-january-2024 flooding]. These reports substantially increased CHIRPS rainfall estimates, compared to the satellite-based CHIRP. | ||
+ | |||
+ | '''Australia''' Stations data blended into CHIRPS Final v2 captured the heavy rain that led to [https://www.abc.net.au/news/2024-01-22/nt-flooding-freight-disruptions-supermarket-food-supplies/103374468 flooding near Darwin]. These reports substantially increased CHIRPS rainfall estimates, compared to the satellite-based CHIRP. | ||
+ | |||
+ | '''Rchecks plots''' All stats look good with the exception of the Sahel. Based on the pre-Final CHIRPS, the CHIRPS - CHIRP is much higher than any month previously. The values are very near zero, however, so it isn't of any consequence. Also, this was likely associated with a report at a station that ended up being omitted in CHIRPS Final due to an unreasonably high value for this dry time of year (and no satellite products indicated such an abnormal event). | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202401/CHIRPS_diff_GLB_PR_202401.png here] shows the difference between Prelim data and Final data, for January 2024 (this map will be available ~ Feb 18th). | ||
+ | |||
+ | === December 2023 === | ||
+ | |||
+ | '''Zimbabwe''' 37 new stations have been included in CHIRPS in Zimbabwe, in December 2023 CHIRPS Final data. This is exciting. CHIRPS has needed improved station coverage in Zimbabwe for years. These stations should help better capture observed rainfall and topographic patterns, and will be especially important for monitoring impacts of extreme storm events like tropical cyclones. CHIRP tends to underestimate values in such cases, and in recent years there were few stations located in Zimbabwe being blended into CHIRPS. Several years ago CHIRPS began blending in valuable station databases with coverage in Mozambique and other areas of Southern Africa, and this Zimbabwe data contribution is another progressive move in support of high quality, publicly available gridded data that can support agroclimatic monitoring and many other applications. | ||
+ | |||
+ | The following describes some of the Rchecks on these data for December 2023 CHIRPS Final. These new 37 stations reported high rain amounts > 250 for some locations. These were higher than CHIRP amounts. Satellite datasets generally diverged with respect to anomalies, with RFE2 and CHIRP showing generally below average rain for Dec 2023. TAMSAT shows a similar pattern to what these (and other stations) in CHIRPS Final indicated: A wetter-than-average swath stretching across northeastern South Africa, part of Mozambique, and across Zimbabwe from southeast to northwest. Another check on the high values focused on 'are these rain amounts within range of past reports, and in similar geographic pattern?' An adhoc comparison using Zimbabwe station reports in CHIRPS from December in the 1980s, which had with similar good spatial coverage (as shown by the EWX Rchecks layer), determined that yes, such amounts were reasonable. Similarly, this was indicated by standardized anomalies at the stations, which were high but not outside the bounds of what we see in this type of comparison; i.e. compared to CHIRPS history, the wettest of the stations in this set had z scores ~ 2.5. Confirmation that these station reports seemed reasonable also came from examination of the "Anchors" Rchecks layer. This shows what CHIRPS would look like if only the Anchor stations were blended (i.e. not including this set of stations or the set from MZ and some of SASSCAL). The answer was that, even without blending these Zimbabwe station reports, a similar wet spatial pattern is present. In other words, these stations are giving reports that are congruent with other station-blended data. Finally, active rainfall has been expected and reported in the area during December-early January. [https://www.zimbabwesituation.com/news/zim-braces-for-another-cyclone/ This news article] notes this for northern Zimbabwe. | ||
+ | |||
+ | '''Tanzania''' Stations capture extreme rainfall amounts in western and northern Tanzania from a severe storm in early December. Heavy rain in the area triggered flooding and landslides to gush down steep slopes of Mount Hanang, and into areas around the towns of Katesh and Gendabi. See Floodlist for [https://floodlist.com/africa/tanzania-floods-landslides-hanang-district-december-2023 more information]. | ||
+ | |||
+ | '''Australia''' In northern Queensland, there are prominent rainfall amounts in CHIRP, but the blended stations in CHIRPS Final notably increased estimates. In mid December, Tropical Cyclone Jasper brought heavy rainfall and flooding. [https://www.bbc.com/news/world-australia-67740978 According to the BBC], the "extreme weather driven by [the cyclone] dumped a year's worth of rain on some areas." | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202312/CHIRPS_diff_GLB_PR_202312.png here] shows the difference between Prelim data and Final data, for December 2023. | ||
+ | |||
+ | '''CHIRPS v3''' In Honduras, Dec 2023 data, there is an unnatural linear boundary in rainfall in v2. In contrast, it looks great in v3 here, presumably due to a difference in the newer chpclim. | ||
+ | |||
+ | '''Rchecks plots''': All stats look within normal ranges. | ||
+ | |||
+ | === November 2023 === | ||
+ | |||
+ | '''Somalia''' Extreme rainfall in Somalia in November 2023 led to catastrophic flooding. See [https://youtube.com/watch?v=zs5KpLF6mCk this AP video] for a glimpse of the results: 1.7 million people impacted, standing water in streets, and difficult access to clean water. CHIRPS shows extremely high, record-breaking amounts for November 2023, due to the blending of FAO SWALIM stations that reported extreme high values. Several reported 400+ mm for November 2023. One in Gedo reported 775mm. Strong positive Indian Ocean Dipole and El Nino conditions were responsible for producing extreme wet conditions. When comparing the 2023 rainfall to other historic rain seasons, it is important to keep in mind is that there is a high level of uncertainty around extreme rains in the past. This is due to the absence of reporting stations in the same locations and across Somalia. The historic 1997 extreme season, which is the most comparable to 2023, is an example. According to CHIRP v2 and v3 estimates in Nov 1997 vs. 2023, satellite estimates suggests that southern Gedo and an area to the south of there received higher amounts in Nov 1997 than in Nov 2023. Based on what CHIRPS Rchecks for v2/v3 show, there were no reporting stations in Somalia CHIRPS data in 1997. Without in situ reports to blend with the satellite estimates, the 1997 values could be underestimates of actual amounts. The Nov 2023 data will be ranked as wettest in CHIRPS v2 Nov. history, but beneath that is an unfortunate discrepancy in when there were stations reporting (2023) versus when there weren't (1997). This is an example of the great challenges in tracking extreme rainfall, especially in data sparse areas. | ||
+ | |||
+ | '''Ethiopia''' The second-blending processing step in v2 has produced vastly different (much much higher!) rainfall estimates in Nov 2023 in southeastern Ethiopia, compared to what would be expected based on Ethiopia reports and satellite estimates. This can be seen from comparing the anchor station and 2nd blend rchecks layers. The anchor stations layer shows what it looks like before second-blending. This case is extreme in that it produces higher values in v2 than in v3, wherein v2 is estimating very high values (400-600 mm) and much higher rain (2x higher) than v3 here. The artifact is not surprising-- the FAO SWALIM reports in Somalia are blended in a second step, after the Ethiopia NMA stations have already been blended. The SWALIM stations are reporting extreme high rainfall values, and their influence in propagated into "nearby" areas in rainfall estimation. In the past, some artifact situations have been avoided in v2 final data by omitting one or several of the extreme stations, while making sure that the impact in local (at-station) area is minimized. | ||
+ | |||
+ | '''Brazil''' High rainfall in southern Brazil that [https://earthobservatory.nasa.gov/images/152153/flooding-in-southern-brazil caused flooding] was not captured in CHIRP v2 but was somewhat captured in CHIRP v3 beta. Definitely captured by stations and CHIRPS v2/v3. CHIRPS v2 has a "crop circle" of higher rain due to duplicate stations; CHIRPS v3 beta is more natural looking. | ||
+ | |||
+ | '''CHIRPS v3''' V3 beta overestimates out-of-season rain over northern Africa. A known feature. Some positive feature in v3 is that a second-blending step, and multiple use of same station, are not used in processing. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202311/CHIRPS_diff_GLB_PR_202311.png here] shows the difference between Prelim data and Final data, for November 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats look within normal ranges. | ||
+ | |||
+ | === October 2023 === | ||
+ | |||
+ | '''Somalia, Ethiopia, Kenya''' Stations in CHIRPS Final markedly increased rainfall in October in southern Somalia, northeastern Kenya, and southeastern Ethiopia, compared to Preliminary data. These helped CHIRPS data better reflect the extreme wet conditions brought about by positive Indian Ocean Dipole and El Nino conditions. Preliminary data, which is mainly based on CHIRP here, underestimated the rainfall amounts compared to other near real time monitoring products and observations. The most extreme station report for October was in Bay (Baidoa), Somalia, provided by FAO SWALIM. This station reported 601 mm for the month, and that the rains were extreme through the month. In Oct 1-10, 11-20, and 21-31, it rained 197.0 mm, 135.5mm, and 268.5 mm, respectively. Heavy rains continued into November, and have led to highly destructive flooding in northern Kenya and along the Juba River in Somalia. From [https://floodlist.com/africa/east-africa-floods-november-2023-somalia-ethiopia-kenya-burundi-malawi Floodlist]: The United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA) reports that since October, floods have affected more than 706,100 people in Somalia, mostly in South West, Hirshabelle, Jubaland and Galmudug states. At least 14 people have lost their lives. | ||
+ | |||
+ | '''Brazil''' High precipitation that lead to [https://floodlist.com/america/brazil-floods-santa-catarina-october-2023 severe flooding in Santa Catarina] was much better estimated after stations were blended into CHIRPS Final, compared to CHIRP, Final is still underestimating the values reported at some very wet stations. | ||
+ | |||
+ | '''Dominica and Guadeloupe''' CHIRP and CHIRPS captured the high rainfall from Tropical Storm Phillipe that led to [https://www.local10.com/weather/hurricane/2023/10/03/major-flooding-ongoing-across-dominica-and-guadeloupe-from-philippe/ major flooding across these islands]. This is in contrast to Mexico, where storm activity was not well captured by CHIRP (but was by the blending of stations into CHIRPS Final). | ||
+ | |||
+ | '''CHIRPS processing notes''' During this Rchecks, a beta version of CHIRPS v3 (v3.2) was also examined, for purposes of checking station quality and getting more eyes on what that data looks like. For October 2023, and many other months/year, the v3.2 data shows an erroneous precipitation feature in the Sahel/Sahara/North Africa region that is also in some other satellite products (in this month IMERG-Late, Persiann-CCS, ARC2, and RFE2), but not the CHIRPS operational v2. In this month the estimated precipitation pattern spans from east Niger to south Libya, associated with the beta CHIRP estimates, which are not as directly tied to climatology as they were in CHIRPS v2 (thereby limiting estimated rain in dry areas and seasons. Other things noted by Rcheckers include: The much higher estimated rainfall amounts in the beta CHPclim in central Guatemala, compared to the CHPclim used in CHIRPS v2. Different stations were excluded from the automated "too big too small" screening step- associated with different CHIRP values used in that step as well as different "anchor locations" (more in v3 beta) used in station blending. An undercatch "correction", which is planned to be implemented in v3 and is used in the beta, resulted in the extreme Somalia report being modified for v3 to be 643 mm (25.3") instead of the observed 601 mm (23.7"). In southern Brazil, where v2 data occasionally has circular features, v3 beta had a win over v2 by not showing that feature in this month. In Scotland, rainfall gradient in the beta CHPclim was examined, and in the process a source was discovered that could possibly be useful in the future for incorporating more stations into CHIRPS data. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202310/CHIRPS_diff_GLB_PR_202310.png here] shows the difference between Prelim data and Final data, for October 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats look within normal ranges. | ||
+ | |||
+ | === September 2023 === | ||
+ | |||
+ | '''Brazil''' Flooding and fatalities were [https://www.euronews.com/green/2023/09/07/hundreds-were-saved-heavy-rains-cause-record-death-toll-in-southern-brazil widely reported in southern Brazil]. Station reports blended into CHIRPS Final had important influence in increasing estimated rainfall values in Rio Grande do Sul state for September 2023. The satellite-based estimate, CHIRP, shows slightly enhanced rain here, and then the stations bump rainfall values up around 600 mm. | ||
+ | |||
+ | '''Spain''' Stations improved CHIRP in helping to identify widespread heavy rainfall and flooding in early September. In a 24-hour period to 03 September, the storm, referred to as “Depresión Aislada en Niveles Altos,” or DANA, by Spanish authorities, dumped 217.7 mm of rain in Alcanar and 243.4 mm of rain in Mas de Barberans, both located in Catalonia. The total seen in Mas de Barberans is the highest in 23 years. Other areas of the country also saw significant rainfall totals during the same period, according to figures provided by the State Meteorological Agency AEMET and [https://floodlist.com/europe/spain-floods-september-2023 reported by Floodlist]. | ||
+ | |||
+ | '''Greece, Turkey, and Bulgaria''' Neither CHIRP nor stations appear to have captured the record breaking rainfall events reported in early September in Greece, Turkey, and Bulgaria. Reports state between 650 and 750 mm of rain fell over Greece in one day, [https://floodlist.com/europe/greece-turkey-bulgaria-floods-september-2023 according to Floodlist]. | ||
+ | |||
+ | '''Cameroon''' Two GTS stations in Cameroon were excluded from blending due to their past inconsistency. During recent months and years, these stations have not reported for enough days of the month to make it past CHIRPS Final quality-control screening and into the blending step of CHIRPS Final. They did report enough this month, and would have had large influence on lowering CHIRPS estimates values due to having quite low reports. Due to their inconsistency, and absence from CHIRPS in the past, September 2023 rainfall patterns from multiple datasets were compared. In northeastern Cameroon, the station in question was not in line with the above-average rainfall indicated by several products (e.g. TAMSAT and IMERG-Late). | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202309/CHIRPS_diff_GLB_PR_202309.png here] shows the difference between Prelim data and Final data, for September 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats look within normal ranges. | ||
+ | |||
+ | === August 2023 === | ||
+ | |||
+ | '''Mali''' CHC received reports from field scientists in Mali that CHIRPS Prelim was under-reporting rainfall in the southwest. The season is reported to have been average, to above average. CHIRP signals agree with these reports, however CHIRPS stations show negative anomalies. These stations were removed to ensure CHIRPS anomaly fields match field reports. | ||
+ | |||
+ | '''Kenya''' Four 3D-PAWS Stations have been included into CHIRPS this month. The rainfall totals, anomalies, and z-scores, agree with CHIRP and other source stations pretty well. | ||
+ | |||
+ | '''Belize''' A new source for Belize has been added to CHIRPS this month, and has added 17 stations. These stations seem to agree with CHIRP and nearby stations pretty well. | ||
+ | |||
+ | '''South Korea''' A new source for South Korea was tested for inclusion in CHIRPS final this month, but CHC decided to hold off and not include those station reports. These were making South Korea much drier than CHIRP and IMERG were indicating. Like other new sources, the reports are blended as part of a 2nd blending step. This results in those stations having substantial influence in CHIRPS estimates. In this case, the drier values were also affecting North Korea and China. Due to this is effect the source was turned off for CHIRPS v2, and will instead be considered for inclusion in CHIRPS version 3. There will not be a 2-step blending in version 3. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202308/CHIRPS_diff_GLB_PR_202308.png here] shows the difference between Prelim data and Final data, for August 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats look within normal ranges. | ||
+ | |||
+ | === July 2023 === | ||
+ | |||
+ | '''Panama''' The number of stations in Panama that have station reports blended into monthly CHIRPS has noticeably increased over the past year, bravo! It even largely smooths out the visible abrupt differences that have occurred in the CHIRPS rainfall data between Central America model and South America. | ||
+ | |||
+ | '''Turkey''' Stations improve the CHIRPS product by capturing heavy rainfall values for the month of July 2023 in the Black Sea region of northwestern Turkey. In early July, The Disaster and Emergency Management Authority (AFAD) reported damages in the provinces of Bartın, Zonguldak, Düzce, Kastamonu, Samsun, Giresun, Bolu and Karabük. AFAD said more than 250 mm of rain fell in 24 hours to 09 July in Yığılca in Düzce. Station values in CHIRPS show slightly smaller values, but are much improved relative to initial CHIRP estimates. See [https://floodlist.com/asia/turkey-black-sea-floods-july-2023 floodlist] for more. | ||
+ | |||
+ | '''CHIRPS processing''' In CHIRPS production there are automated quality control steps that screen out station reports that are likely to be errors, associated with too big or too small values. The goal is to reduce the impact of errors on the product. With the development of CHIRPSv3, CHC is investigating ways to improve the screening methods, including through statistical modeling using multiple data sources and through better visualization of the screening process. In July 2023 data, a handful of stations in Turkey and Russia that had been auto-screened out were re-included into CHIRPS, based reports of [https://floodlist.com/europe/russia-floods-sochi-late-july-2022 storms] and [https://crisis24.garda.com/alerts/2023/07/turkiye-disruptions-due-to-flooding-and-landslides-ongoing-across-northern-regions-as-of-july-10 flooding] at those locations. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202307/CHIRPS_diff_GLB_PR_202307.png here] shows the difference between Prelim data and Final data, for July 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats look fine. | ||
+ | |||
+ | === June 2023 === | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202306/CHIRPS_diff_GLB_PR_202306.png here] shows the difference between Prelim data and Final data, for June 2023. | ||
+ | |||
+ | '''Rchecks plots''': Southern Africa doubled it's previous CHIRPS maximum but we are removing a couple of these outliers. Otherwise, all looks normal. | ||
+ | |||
+ | === May 2023 === | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202305/CHIRPS_diff_GLB_PR_202305.png here] shows the difference between Prelim data and Final data, for May 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats look fine. | ||
+ | |||
+ | === April 2023 === | ||
+ | |||
+ | '''Mexico''' No Conagua station reports were blended into CHIRPS for April 2023. This created a major reduction in in situ reports that are typically included in Mexico, at more than 300 locations from Conagua, to less than 50 locations from global networks. Conagua, Mexico's National Water Commission, usually also provides station reports that are used to improve the CHIRPS preliminary pentad product, but these were missing during April 2023 as well. | ||
+ | |||
+ | '''Brazil''' Heavy rains produced flooding in Bahia state, [https://floodlist.com/america/brazil-floods-bahia-april-2023 according to Floodlist]. CHIRPS estimates in this area were improved from blending of station reports that showed wetter conditions than CHIRP. | ||
+ | |||
+ | '''Columbia''' CHIRP estimates were moderately high, but numerous station reports were wetter. This resulted in a substantial portion of mountainous areas having CHIRPS estimates that range from 600 mm to higher than 1000 mm for the month. Flooding impacted multiple areas in early and late April, with landslides and fatalities reported in [https://floodlist.com/america/colombia-floods-cundinamarca-april-2022 Cudinamarca] and [https://floodlist.com/america/colombia-landslide-floods-antioquia-april-2022 Antioquia]. | ||
+ | |||
+ | '''Peru''' Severe flooding also occurred during April 2023 in Piura, Peru. A GTS station that doesn't regularly show up in CHIRPS reported a very high amount for Piura: 361 mm. According to news reports, affected areas received [https://www.lemonde.fr/en/international/article/2023/04/20/peru-pummeled-by-heavy-rains-and-destructive-floods_6023654_4.html 5 times more rain] in a few days than would typically occur in the whole month, and that the flooding greatly [https://reliefweb.int/report/peru/peru-flooding-situation-report-no-04-24-april-2023 impacted basic services] and increased risks of vector-borne and contamination-related diseases in the northern coastal areas of the country. The wet conditions came after [https://en.wikipedia.org/wiki/Cyclone_Yaku Cyclone Yaku] brought heavy rain and flooding to northern Peru in March. | ||
+ | |||
+ | '''Australia''' Station data prominently increased the CHIRPS rainfall estimates, compared to CHIRP, for the peninsula area in east Arnhem and Nhulunbuy. A [https://www.abc.net.au/news/2023-04-18/nhulunbuy-wettest-location-in-the-world-303mm-rain-12-hours/102235326 tropical storm] grazed northern Australia. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202304/CHIRPS_diff_GLB_PR_202304.png here] shows the difference between Prelim data and Final data, for April 2023. | ||
+ | |||
+ | '''Rchecks plots''': There were new CHIRPS maximums in South America, 2300mm as opposed to the previous high of around 1300mm. Stations in Columbia and Peru confirm there were very wet conditions in April 2023, so the statistics seem reasonable. | ||
+ | |||
+ | === March 2023 === | ||
+ | |||
+ | '''California''' Blended stations majorly increased CHIRPS values in northern coast and Sierra Nevada mountain regions of California. CHIRPS, and even just the CHIRP, did a better job delineating these as areas of high rainfall than IMERG-Late, probably due to the orographic influence built into the climatology (in CHIRP and CHIRPS), plus the stations (in CHIRPS). In contrast, IMERG-Late shows rainfall that lacks an elevation pattern as is pretty even and around 60-70 mm across much of the state. With some wetter areas along the coast and drier areas in the west. | ||
+ | |||
+ | '''Mozambique''' Three station reports along the central coast were inspected, due to their close proximity to Cyclone Freddy's landfall and the low and below-average amounts reported at two of these. A similar situation with one of these stations occurred last year (Feb/March 2022 data/Cyclone Gombe). In that case we omitted the station's report, out of consideration that it could be an inaccurate report for a monthly total. The same decision was made for these two in the March 2023 Final blending; the third station's report, which was more realistic, was retained. An article on Freddy and its heavy rain and major flooding impacts in Quelimane, the nearby main city, can be found [https://www.bbc.com/news/world-africa-64928093 here]. | ||
+ | |||
+ | '''Kenya''' A GSOD station report in northeast Kenya was inspected, due to a report of 12.5 mm being markedly lower than what is indicated by satellite rainfall estimates. Higher and above-average March amounts are indicated in this area, associated with storms in mid-late March, by CHIRP, TAMSAT, IMERG satellite products. There was also substantial surface green up indicated in eVIIRS NDVI maps near this location during this month. A pre-March and post-March NDVI comparison is shown [https://drive.google.com/file/d/15g5wvt_LX6RsCgL3RmSLdYPudNP8kQiV/view?usp=share_link here]. Due to the multi-source agreement, the 12.5 mm report was omitted from the Final blending procedure, out of precaution that it could be an accurate report for a monthly rainfall total. | ||
+ | |||
+ | '''CHIRPS improvement''' Quality control and procedural station blending steps are points of planned near term focus in CHIRPS v3 development. An automated station screening step in the CHIRPS processing was marked as a quality control step that will be revisited. It checks for stations that are "too big or too small", compared to expectations based on CHIRP and climatology, and is resulting in some geographic clustering of auto-omitted stations. A step of processing that blends some newer stations as part of a second blending step, was again discussed as being problematic. This 2nd step can markedly increase the influence of extreme station reports in CHIRPS rainfall estimates, and is planned to not be used in CHIRPS v3. Some inconsistencies were recently noted for some SASSCAL stations, such as a reduction in reporting frequency in recent years and possibility of sub-monthly daily totals in lieu of full-month daily totals. The latter potential issue may be improved with new screening steps, which will be investigated. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202303/CHIRPS_diff_GLB_PR_202303.png here] shows the difference between Prelim data and Final data, for March 2023. | ||
+ | |||
+ | '''Rchecks plots''': A new high for Costa Rica of 1900 mm, other than that, all stats fall within normal ranges | ||
+ | |||
+ | === February 2023 === | ||
+ | |||
+ | '''Mozambique''' [https://en.wikipedia.org/wiki/Cyclone_Freddy Cyclone Freddy] was a major driver on high rainfall amounts reported by stations in southeastern and central-eastern Mozambique. The wettest report was near the town of Vilankulos (eastern Inhambane province) at 835 mm for the month. This is ~650 mm higher than average, based on historical CHIRPS data at that location. The blending of station reports greatly increased CHIRPS compared to CHIRP in southern Mozambique. In contrast, several stations in Manica province, in central-western Mozambique, reported much less rain than satellite data indicated. In Chimoio a station reported 182.3 mm while CHIRP estimated 278 mm. These stations have been reliable in the past, and their reports were maintained in CHIRPS Final. These stations influenced a drier CHIRPS in portions of central-western Mozambique compared to what CHIRP had indicated. | ||
+ | |||
+ | '''Philippines''' There were reports of monsoon flooding in some admin level 2 areas that CHIRPS identifies as having receiving high rainfall amounts. CHIRP estimates were decently high, but CHIRPS are higher due to the blending of stations. More information about the flooding can be read in in [https://floodlist.com/asia/philippines-floods-february-2023 this Floodlist article]. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202302/CHIRPS_diff_GLB_PR_202302.png here] shows the difference between Prelim data and Final data, for February 2023. | ||
+ | |||
+ | '''Rchecks plots''': All stats fall within normal ranges | ||
+ | |||
+ | === January 2023 === | ||
+ | |||
+ | '''Algeria''' In coastal areas, January CHIRPS shows welcome improvement in rainfall, compared to the very dry conditions in December. Several stations blended into CHIRPS reported above average January rainfall, in Jijel, Alger, and into Medea. While CHIRP also picked up on this; having these station reports improved (increased) CHIRPS Final estimates. | ||
+ | |||
+ | '''Philippines''' Extreme rainfall was picked up by CHIRP and CHIRPS; see [https://floodlist.com/asia/philippines-floods-january-2023 Floodlist] for more information. | ||
+ | |||
+ | '''Australia''' High rainfall amounts that led to [https://floodlist.com/australia/floods-kimberley-western-australia-january-2023 flooding in northern Australia] were captured by CHIRP and CHIRPS, with the blended stations in CHIRPS resulting in higher and more accurate estimates. | ||
+ | |||
+ | '''Afghanistan''' CHIRPS Final is somewhat wetter than Prelim for January 2023 data, in southwestern and southeastern Afghanistan. This is seemingly due to several stations in Pakistan that reported above-average precipitation near the border. There are no stations located in Afghanistan that have reports blended into Final, since September 2021, so the estimates are influenced by a combination of satellite-based (CHIRP) estimates and reports in surrounding countries. The increases in Jan 2023 seem believable, due to higher precipitation being indicated by CPC Unified. IMERG-Late daily data also estimates high rainfall amounts in the southwest during early January, with much higher amounts than indicated by CHIRPS. | ||
+ | |||
+ | '''Brazil''' There are roughly 20 stations reporting near the town of Bela Horizonte. The sources are fGTS and local. This is an extreme case of high density stations being blended into CHIRPS. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202301/CHIRPS_diff_GLB_PR_202301.png here] shows the difference between Prelim data and Final data, for January 2023. | ||
+ | |||
+ | Rchecks plots: A high value of 2400 mm was plotted in the global CHIRPS maximum pane, which stood out because it was several hundred mm higher than previous value. Marty identified that this pixel is located in the Pacific Islands region at 145.65 E, 18.85 N. There were also 2 other pixels greater than 2000 mm along the same chain of the Mariana Islands. Other than that, all other statistics fall within normal bounds | ||
+ | |||
+ | === December 2022 === | ||
+ | |||
+ | '''Brazil''' In central coastal Brazil, in Espirito Santo state, the blending of stations into CHIRPS produced much higher rain estimates compared to CHIRP. These high rainfall amounts were associated with flooding reported in this area, which resulted from heavy rain in both November and December. Read [https://floodlist.com/america/brazil-floods-espiritosanto-santacatarinaparana-riodejaneiro-bahia-december-2022 here] for more. | ||
+ | |||
+ | '''Congo and DRC''' In Kinshasa, capital of the Democratic Republic of the Congo, torrential rainfall in December reportedly brought "months of rain." Floods and landslides killed at least 169 people and caused major damage to infrastructure. ReliefWeb offers [https://reliefweb.int/report/democratic-republic-congo/democratic-republic-congo-flash-update-3-floods-caused-heavy-rains-kinshasa-31-december-2022 more information about this event]. What is surprising is that CHIRPS has a station reporting not very far from Kinshasa, just north of the Congo border, and the amount reported there seems very low considering this high impact event. This station from GHCN-v2 monthly reported 214 mm: An amount that is considered slightly below average compared to CHIRPS average for that month. Two satellite products, TAMSAT 3.1 and CHIRP show above-average rain in the area. Given the Kinshasa flood news reports and the general agreement from the satellite products, this station's report and was recommended for omission from CHIRPS Final this month. | ||
+ | |||
+ | '''Armenia and Azerbaijan''' Rchecks during this month and previous months identified 8 stations that repeatedly reported standout high values, ranging from 200 to 600 mm, that are interspersed with a dozen stations that report less than 20 mm. The source of inconsistency is not known, though maybe it has to do with data errors e.g. missing decimals. Since these stations have been flagged multiple times already, the set was recommended for permanent removal. | ||
+ | |||
+ | '''Spain''' Severe weather and flooding was [https://floodlist.com/europe/spain-floods-extremadura-castilla-la-mancha-madrid-december-2022 reported in Spain], in several provinces in mid December. CHIRPS Final for December is benefitting from the blending of high, above-average rainfall reports across many locations. CHIRP did a decent job resolving above-average rainfall in northern Spain, but the stations across a larger region (including Portugal and France) really bumped up the CHIRPS values. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202212/CHIRPS_diff_GLB_PR_202212.png here] shows the difference between Prelim data and Final data, for December 2022 (a link will be active soon). | ||
+ | |||
+ | Rchecks plots: Slightly new highs for number of pixels with rain and CHIRPS - CHIRP mean for the Sahel but by very small amounts. Otherwise, statistics are within normal ranges. | ||
+ | |||
+ | === November 2022 === | ||
+ | |||
+ | '''Spain''' Stations blended into CHIRPS final data captures an intense rainfall event on the eastern coast of Spain. The weather station at Valencia airport recorded 66.1 liters of rain per square meter in just one hour -- the most intense rainfall on record for November, according to Spanish meteorological agency AEMET. More on this story is [https://www.euronews.com/2022/11/12/hundreds-stranded-at-valencia-airport-after-storm-floods-the-runway here]. | ||
+ | |||
+ | '''Kenya''' In western Kenya there are typically around 5 GTS and GSOD station reports blended into CHIRPS final data, but for Nov 2022 the Rchecks shows this area has no station reports going into CHIRPS final. The above-average Nov 2022 CHIRPS estimates in western Kenya are coming from CHIRP and likely also are influenced by above-average rainfall reported at two stations in central Kenya. Other satellite products (e.g. RFE2, IMERG-Late) also indicate above-average rainfall near the CHIRPS above-average rainfall areas in western Kenya. | ||
+ | |||
+ | '''Panama''' There is a particularly obvious visual seam between November CHPclim tiles, which is producing an odd-looking artifact in the Panama Canal region in November 2022 data. | ||
+ | |||
+ | '''Honduras''' Multiple stations reported below-average rainfall along the Caribbean coast, which lowered CHIRPS values compared to the CHIRP and CHIRPS-Prelim estimates quite a bit in northern and eastern Honduras | ||
+ | |||
+ | '''Indonesia'' A linear artifact was spotted in November CHPclim data in Indonesia+Papua Barat (near 134E, 4S) | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202211/CHIRPS_diff_GLB_PR_202211.png here] shows the difference between Prelim data and Final data, for November 2022. | ||
+ | |||
+ | Rchecks plots: All statistics are within normal ranges. | ||
+ | |||
+ | ===October 2022 === | ||
+ | |||
+ | '''East Africa''' October 2022 CHIRPS Final shows drier-than-average conditions across many equatorial and southern locations, including areas of concern in Kenya, southern Somalia, and parts of southeastern Ethiopia. Available station reports confirmed the regional dry signal, and the wetter-than-average conditions in western Ethiopia. Those conditions were previously indicated by CHIRP and CHIRPS Preliminary estimates, and other satellite-based estimates. The station reports that were blended into CHIRPS Final also identified some additional areas with higher rainfall (e.g. see entry on Somalia). Forecasted below-average rainfall during September to November/December 2022 in this region has been a concern, due to drought conditions during several consecutive key rainfall seasons and extreme impacts to agricultural and pastoral livelihoods, water resources, and food security. See the [https://reliefweb.int/report/somalia/multi-agency-drought-alert-immediate-global-action-required-prevent-famine-horn-africa-november-2022 Multi-Agency Drought Alert] for more information. | ||
+ | |||
+ | '''Somalia''' FAO SWALIM stations that are blended into CHIRPS Final reported that many locations recieved only low to moderate amounts during October 2022, and a few recieved localized heavy rain. Ample, localized rainfall of 140 mm to 250 mm+ for the month was reported in Sool and Togdheer near the Ethiopia Somali region border. Some satellite rainfall estimates, e.g. IMERG-Late, indicate above-average rains nearby, though not > 200mm. In this area and in eastern Somali, NDVI imagery and time series (eVIIRS) indicate vegetation greenup during late October to early November, and cooler than average land surface temperatures, both of which are consistent with higher rainfall in these areas during October. Several stations in southern Somalia (two in Bay and one in Bakool) reported moderately above-average October rainfall. However, reports from most other stations in southern Somalia indicated below-average October rainfall, confirming the CHIRP, RFE2, IMERG-Late estimates that also showed drier-than-average conditions. NDVI imagery also confirms the widespread vegetation stress across these areas into early November. | ||
+ | |||
+ | '''Vietnam''' CHIRPS data shows the heavy rainfall received in Vietnam. The country was recently hit by 5-6 tropical storms, which resulted in [https://floodlist.com/asia/vietnam-floods-storm-sonca-october-2022 widespread flooding.] | ||
+ | |||
+ | '''Brazil and Paraguay''' Blended station reports led to large differences in CHIRPS versus CHIRP rainfall estimates in eastern Paraguay and southern Brazil. Three station reports in Brazil were omitted; two were possible falso zeros and one had a seemingly inaccurate high rainfall amount. Those station reports were markedly different from neighboring stations and also indications from multiple satellite-based rainfall estimates (CHIRP, PERSIANN, and IMERG-Late). | ||
+ | |||
+ | '''Columbia''' The very dense station network significantly raised CHIRPS values compared to CHIRP. Many stations reported much higher than average rainfall values. The wet signal was also seen in IMERG-Late and PERSIANN-CCS data. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202210/CHIRPS_diff_GLB_PR_202210.png here] shows the difference between Prelim data and Final data, for October 2022. | ||
− | '' | + | '''Rchecks plots''' All statistics are within normal ranges. |
− | + | ===September 2022 === | |
− | '' | + | '''United States''' In late September, Hurricane Ian made landfall in southwestern Florida and brought heavy rain and severe flooding. It was [https://www.accuweather.com/en/hurricane/southwest-florida-in-tatters-after-hurricane-ians-rampage/1256208 one of the strongest storms to ever hit the United States.] Station reports blended into CHIRPS ranged from 15 to ~28 inches for the month, in affected areas. CHIRP v2 seems to have underestimated the precipitation, compared to IMERG and Persiann. By comparison, the beta version of CHIRP v3 was better able to pick up the increased precipitation-- a good sign for higher accuracy of extreme rainfall events in the next version of CHIRPS. |
− | '' | + | '''Thailand''' Thailand was hit by [https://floodlist.com/asia/vietnam-thailand-typhoon-noru-september-2022 Tropical Cyclone Noru] at the end of September. CHIRP captures the higher-than-average rainfall pattern but CHIRPS shows higher rainfall amounts, with differences in some of the wettest areas that are ~ 150mm higher in CHIRPS. There aren't any stations reporting to CHIRPS in Cambodia, and it was stations in Thailand that led to the increase in Cambodia. |
− | '' | + | '''South Korea''' South Korea was hit with Typhoon Hinnamnor in early September, causing flooding and evacuations. It was the second major rain event in a few weeks time. More information is available [here https://www.cbsnews.com/news/typhoon-hinnamnor-south-korea-deaths-missing-flooding-in-south-and-north-korea/]. CHIRPS data shows above-average rainfall across the Korean Peninsula and in southeastern China and Russia during the first dekad of September. |
+ | '''Europe''' [https://www.theguardian.com/environment/2022/sep/19/weather-tracker-deadly-floods-italy-adriatic-coast-typhoon-nanmadol- Deadly floods battered] countries along the Adriatic Sea in mid and late September, including Italy, Slovenia, [https://floodlist.com/europe/croatia-floods-rijeka-september-2022 Croatia], Montenegro and Bosnia-Herzegovina. Stations blended into CHIRPS data reported very high monthly totals in western Slovenia, with several around 500 mm (20 inches). | ||
+ | '''Puerto Rico''' Hurricane Fiona led to very high rainfall. CHIRP didn't capture the high values well, with isolated pixels near 500 mm. In contrasts, CHIRPS shows a widespread area with over 600 mm for the month, and one pixel of 936 mm! | ||
− | + | '''Western Sahara''' A station reported a value here ~30 mm. Despite being a relatively low value, this amount of rain is not typical here. This seems to be an accurate station report, as multiple satellite products show higher than average rain. A station in coastal Mauritania also reported above average rainfall. The area was affected by [https://en.wikipedia.org/wiki/Tropical_Storm_Hermine_(2022) Tropical Storm Hermine], an unusual storm that formed northeast of Cabo Verde in late September 2022. | |
− | + | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202209/CHIRPS_diff_GLB_PR_202209.png here] shows the difference between Prelim data and Final data, for September 2022. | |
− | ''' | + | '''Rchecks plots''' Statistics fall within previous ranges except for in West Africa. The CHIRPS maximum value is much higher than any previous value for September. This was traced to several pixels along and just off the coast of Mauritania that were very high. This appears to be related to very high CHPclim (climatology) values at those locations, which appear in both September and August monthly CHPclim. The extreme values in CHIRPS final September 2022 were created by a combination of the high climatology pixels and exaggeration of those when a wetter-than-average station report was in their vicinity was blended into the data. Rcheckers also examined the next (beta) version of CHPclim, and found that the same issue was occuring in the same locations, but value were even higher than in the current CHPclim. This issue was communicated to Pete Peterson, data curator. |
− | |||
− | == | + | ===August 2022 === |
− | ====Rchecks | + | '''Uganda''' August 2023 had a higher than usual number of stations reporting in Uganda. All 8 of these are GTS stations. Several reported much higher than average rainfall, with the highest amount in the Eastern Region (~300 mm), where [https://floodlist.com/africa/uganda-floods-mbale-kapchorwa-july-2022 destructive, heavy rain] also occurred in late July. Data indicate that this highly above-average monthly total was mainly reflecting rainfall during the last dekad in August. In Uganda, June and July rainfall was substantially below average, and wetter and more mixed conditions occurred since then. CHIRP data tends to underestimate heavy, localized rain events, which was the case here- the wet station report increased CHIRPS-estimated amounts by more than 50% in some locations. |
+ | |||
+ | '''Yemen''' The magnitude of very high rainfall values in Yemen in August 2022 are regarded with only moderate confidence. This is because there are no Yemen station observations being blended in. Rather, the high values are a result of a combination of several wetter-than-average stations in southern Saudi Arabia and possibly Ethiopia, and above-average CHIRP values. This type of wet exaggeration has been apparent in CHIRPS through this summer in Yemen, and is associated with persistent wet conditions that have occurred. A wet tendency is strongly inferred by agreement between multiple satellite-based rainfall products (e.g. IMERG-Late, RFE2, CHIRP) and the stations in the general area. When it comes to differences between CHIRP (or CHIRPS Prelim) and CHIRPS Final, we occasionally see the much lower variance of CHIRP underestimating extreme rainfall, and that stations blended into Final can really make a wet difference. This seems to be one of those cases, though unfortunately we don't have local stations to provide indication of actual rainfall amounts. This case was an extreme one, as evidenced by CHIRPS having several pixels off-shore that were higher than any other August pixel from 1981-2021 in the East Africa region monitored by the Rchecks Plots. | ||
+ | |||
+ | '''Mali''' In August 2022 there was a major underreporting of GHCN-v2, globally dropping from ~1700 to ~1250 stations. Mali is one country where this had a major impact on typical station composition- while most months this year had GHCN-v2 and GSOD in Mali, this month the stations are all GTS. The values reported at these stood out as being suspiciously low, compared to what CHIRP and IMERG-Late indicate, especially in southern Mali. The impact would be to dramatically lower CHIRPS values across southern Mali. We also checked GTS amounts against a secondary station dataset, the MCDW, and found GTS to be around 100 mm lower than those in some areas in question. Given that the CHIRP seemed to have a reasonable-looking anomaly pattern (mixed, with some ongoing dryness but not more intense compared to previous months), and that GTS is the lowest-ranked station source in terms of quality, we opted to omit almost all the GTS reports in Mali this month. CHIRPS relies mainly on the CHIRP estimates there. We kept one GTS, in the northwestern zone of southern Mali, to "counteract" influence of an anomalously wet station in western Senegal. | ||
+ | |||
+ | '''Pakistan''' [https://www.theguardian.com/environment/2022/sep/15/pakistan-floods-made-up-to-50-worse-by-global-heating Exceptional and highly destructive flooding ] has occurred in Pakistan this summer. The 2 southern states of Sindh, Balochistan were most affected, according to August news reports. August CHIRP data and z-scores don't pick up on the severity of this. Stations help CHIRPS quite a bit, and resulted in CHIRPS z-scores in the +2-3 range. Some estimates may be underestimated, based on a station reporting 500 mm and CHIRPS FINAL ultimately estimating 200-300 mm near there. | ||
+ | |||
+ | '''Somalia''' Several stations in southern Somalia reported moderate and above-average rainfall during August, mainly ranging from 30 to 50 mm in total, and these are reflected in the August CHIRPS estimates. The location of this localized rain, in Bay, Shabelle-Hoose, and Shabelle-Drexe, matches well with the pattern indicated in RFE2's August rainfall anomaly estimates. Good to see that level of agreement between these data products. | ||
+ | |||
+ | '''Panama''' There is a particularly obvious visual seam between August CHPclim tiles, which is producing an odd-looking artifact in the Panama Canal region in August 2022 data. | ||
+ | |||
+ | '''Brazil''' Four stations in southeastern Brazil along the southern boundary of Sao Paulo state and the northern boundary of Parana state were omitted and suspected of having false zeros. Their station values of zero contrasted the surrounding CHIRPS' pixel values that ranged between ~30 to 90 mm. Other stations within 5-10 km reported around 60 mm. IMERG-Late and PERSIANN data also indicated ample precipitation, around 30 to 100mm in this region. | ||
+ | |||
+ | '''Iran''' CHIRP is reporting near zero rainfall across southwestern Iran. However, some GSOD and GTS gauge stations are reporting rainfall between 32 and 74.5 mm. Other data, e.g. IMERG-Late and PERSIANN-CCS, confirm there was precipitation in this area, with values ranging from 50 mm to localized amounts higher than 150 mm. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202208/CHIRPS_diff_GLB_PR_202208.png here] shows the difference between Prelim data and Final data, for August 2022. | ||
+ | |||
+ | '''Rchecks plots''' All statistics fall within previous ranges except the "Long Horn of Africa", CHIRPS maximum value. CHIRPS Final data for August 2022 contains several pixels that are much higher than any in previous August data. These are located just off the coast of western Yemen. The high value pixels are ~ 1050 mm and are seemingly created from a combination of abnormally wet CHIRP values and abnormally wet station reports in southern Saudi Arabia. | ||
+ | |||
+ | ===July 2022=== | ||
+ | |||
+ | '''Yemen''' CHIRPS shows much higher July rainfall totals than CHIRP in western Yemen. The accuracy of July 2022 CHIRPS high rainfall amounts in the area near Marib and Sana'a is in question, as these are not verified by stations in that area. There are no stations in Yemen that are blended into CHIRPS. The high values in this area appear to be from a combination of two things: Above-average rainfall in CHIRP and reports from stations in nearby countries. | ||
+ | |||
+ | '''Afghanistan''' It has been almost one year since any stations have reported in Afghanistan to be included in CHIRPS. The last report was a GSOD station on August 2021. | ||
+ | |||
+ | '''Australia''' In New South Wales, the dense station network shows high rainfall amounts for July, which increased CHIRPS compared to CHIRP. Some locations could potentially have received higher amounts than shown by CHIRPS. Australia has been hammered by rain lately, producing [https://www.aljazeera.com/news/2022/7/4/devastating-thousands-more-told-to-evacuate-from-sydney-floods repeative and damaging floods]. | ||
+ | |||
+ | '''New Zealand''' CHIRP performed decently well in estimating high rainfall amounts along the west coast of the South Island, but anomalous station reports all around the area further increased CHIRPS values. Much of the area that was most affected by heavy rains is uninhabited, but there was plenty of flooding in surrounding areas. More on the South Island floods is [https://www.rnz.co.nz/news/national/471258/south-island-floods-clean-up-ahead-for-parts-of-otago-canterbury here]. | ||
+ | |||
+ | '''United Arab Emirates''' Extreme high rainfall occurred during July 27th-29th, and had major impacts in the city of Kalba. A station blended into CHIRPS reported 220mm for the month of July at this location as well as several others with lower amounts; an article about the event noted that rains were the [https://en.wikipedia.org/wiki/2022_United_Arab_Emirates_floods heaviest in 27 years] during the event. While CHIRPS contained these reports, the data values do not reflect such high amounts. This is due to the estimation algorithm being tied to climatological averages, which are low in this location. That suppression of localized wet extremes in dry locations/seasons is a downside of that methodology. | ||
+ | |||
+ | '''China''' On Hainan island, blending of one station's report for July rainfall boosted CHIRPS values, compared to CHIRP. A typhoon brought heavy rain to this area; some locations could potentially have received higher amounts than shown by CHIRPS. More on the typhoon is [https://www.reuters.com/world/china/china-lashed-by-years-first-typhoon-record-rains-forecast-2022-07-02/ here]. | ||
+ | |||
+ | '''Colombia''' CHIRP seems to have problems estimating high orographic rainfall in the mountains of Colombia (particularly coastal); stations help CHIRPS a lot. Probably not a lot of agricultural areas there, but it's an interesting feature. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202207/CHIRPS_diff_GLB_PR_202207.png here] shows the difference between Prelim data and Final data, for July 2022. | ||
+ | |||
+ | '''Rchecks plots''' All statistics fall within previous ranges except the "Long Horn of Africa", CHIRPS - CHIRP mean. It is about 2 mm higher than any previous July and looks to be due to the Ethiopian highlands increases. | ||
+ | |||
+ | ===June 2022=== | ||
+ | |||
+ | '''Côte d'Ivoire''' Heavy, abnormally high rainfall in June 2022 was reported by a station in Abidjan. This is in part due to an extreme rain event that reportedly brought 160 mm of rain in 12 hours, [https://floodlist.com/africa/ivory-coast-floods-bingerville-june-2022 according to Floodlist]. Flooding from this event, and another one during the previous week, led to at least 6 fatalities. The GTS station blended into CHIRPS reported 728 mm for June. The station resulted in higher CHIRPS estimates compared to CHIRP in this area, though CHIRP did a decent job resolving a high amount at the same location (~600mm and ~ 150mm higher than average for the month). | ||
+ | |||
+ | '''USA''' Heavy rainfall combined with the melting of late season snow pack to produce [https://floodlist.com/america/usa/floods-montana-yellowstone-park-june-2022 record-high river levels that flooded portions of southern Montana], including in Yellowstone National Park. The flooding washed out roads and bridges, and occurred in some river and creek areas that seldom or [https://www.weather.gov/byz/June-2022-Unprecedented-Flooding reportedly never have experienced flooding]. Stations blended into CHIRPS in this area and in northwestern Wyoming have above-average monthly totals, and satellite-based estimates from CHIRP and IMERG-Late show this being primarily to above-average rain in mid-June. The blending of these stations' reports into CHIRPS final resulted in wetter monthly totals over a larger area, compared to CHIRP estimates. | ||
+ | |||
+ | '''Guatemala''' Numerous stations in Guatemala report heavy rainfall, which led to [https://www.infobae.com/america/america-latina/2022/06/20/guatemala-supero-el-millon-de-afectados-por-las-lluvias-y-las-muertes-subieron-a-22/ fatalities, flooding, landslides, and damaged infrastructure]. The high density of INSIVUMEH stations that are blended into CHIRPS final data increased CHIRPS estimates compared to CHIRP, across western, southern, and southeastern areas. | ||
+ | |||
+ | '''Costa Rica''' Station data increased CHIRPS estimates compared to CHIRP. News reports note tropical waves have led to high rainfall/flooding in the north part of the country. More information is [https://ticotimes.net/2022/06/29/costa-ricas-northern-zone-is-affected-by-rain-floods-and-landslides available here]. | ||
+ | |||
+ | '''Nicaragua''' Station data has been missing here for the last few months. | ||
+ | |||
+ | '''Persian Gulf''' To the northwest of Dubai in the Persian Gulf, on the small island of Siri, GTS and GSOD reported station values of 65 mm and 64 mm, respectively. CHIRP, IMERG, and PERSIANN show the same area and its surroundings to have zero precipitation. The closest measurable precipitation, on the southern shore of Iran, is about 0.6 to 2.5 mm. These stations were omitted from blending in CHIRPS final due to lack of support of rain from satellite products; Rcheckers also did not find any online reports to support highly localized rain. | ||
+ | |||
+ | '''North Korea''' North Korea is showing up as much wetter in CHIRPS than the CHIRP for June 2022 due to the influence of blended station data. Rain gauge data from a station in Pyongyang, for example, recorded 591 mm. CHIRP estimates partially resolve this event, with above-average rainfall in the same area; however, CHIRP totals range from 150 mm to 195 mm. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202206/CHIRPS_diff_GLB_PR_202206.png here] shows the difference between Prelim data and Final data, for June 2022. | ||
+ | |||
+ | '''Rchecks plots''' All stats fall within normal ranges, except for the Southern Africa region, where new a CHIRPS mean and maximum and CHIRPS-CHIRP all had new highs for June totals. Looking back at previous years' CHIRPS final data for June, the current highs correspond to unusally widespread rain in June 2022. | ||
+ | |||
+ | ===May 2022=== | ||
+ | |||
+ | '''Southern Africa''' CHIRP and stations fail to capture severe rainfall and flooding in late May in Kwazulu-Natal. Some areas reportedly received [https://floodlist.com/africa/south-africa-floodi-kwazulu-natal-may-2022 over 200mm in 24 hours on May 22]. Stations blended into May 2022 CHIRPS in KwaZulu-Natal that are visible in the Rchecks interface all had less than 100 mm for the month. | ||
+ | |||
+ | '''Puerto Rico''' Stations reported lower rainfall totals than were estimated by CHIRP. There is a relatively dense station network here, to this lowered CHIRPS values. In general, stations appear to be having a bigger role than normal this month in CHIRPS in Southern and Central America. | ||
+ | |||
+ | '''Columbia''' Reports from the dense station network, including some stations in the Amazon region, had the effect of increasing CHIRPS rainfall values above the already high CHIRP estimates. | ||
+ | |||
+ | '''Brazil''' In southern Brazil, many stations report a band of higher rainfall amounts than are estimated by CHIRP, and resulted in higher CHIRPS values. | ||
+ | |||
+ | '''United States''' Stations increased CHIRPS estimates, compared to CHIRP, across most areas. Especially in the central US and upper midwest. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202205/CHIRPS_diff_GLB_PR_202205.png here] shows the difference between Prelim data and Final data, for May 2022. | ||
+ | |||
+ | '''Rchecks plots''' All statistics are within previous ranges with the exception of Southern Africa, where the regional mean difference in CHIRPS and CHIRP was higher than any previous values for May. This is due to the effect of many stations in South Africa and Mozambique increasing CHIRPS estimates along the coast. The May 2022 mean CHIRPS - mean CHIRP value is about 1mm higher than the previous high value. | ||
+ | |||
+ | ===April 2022=== | ||
+ | |||
+ | '''Madagascar''' In southeast Madagascar, a station that is included in CHIRPS reported a very high 429 mm rainfall for April. High values are not shown in CHIRP, TAMSAT, ro RFES2 estimates, but they are in IMERG-Late. The reported wet conditions are likely related to a tropical storm that made landfall in the region in late April. More on Tropical Storm Jasmine is [https://watchers.news/2022/04/26/tropical-storm-jasmine-to-make-landfall-over-madagascar/ here]. | ||
+ | |||
+ | '''Australia''' CHIRP estimates were decent in northern Queensland, but station data boosted CHIRPS Final values quite a bit. Heavy rains lead to [https://www.abc.net.au/news/2021-04-21/bruce-highway-cut-as-flooding-rain-continues/100083226 extensive flooding in this area] in late April. | ||
+ | |||
+ | '''Columbia''' After a hiatus, Columbia stations are back in CHIRPS Final. Rchecker Seth noted: "Good to see the stations back. CHIRP doesn't seem to perform optimally with orographic rainfall, and the stations always make a difference (increasing estimates)" | ||
+ | |||
+ | '''Northern US and southern Canada''' CHIRPS data shows the highly above-average precipitation in April 2022 in western Washington and Oregon, USA, western British Columbia, Canada, and the region from North Dakota, USA to southern Ontario, Canada. In many locations in these areas, April 2022 precipitation amounts were close-to or above previous record highs, according to [https://www.foxweather.com/extreme-weather/april-2022-records-temperatures-precipitation this article] about April 2022 precipitation and temperature extremes. | ||
+ | |||
+ | '''Western US''' The hydrologic drought in most of California and across the southwest was worsened by below-average April precipitation. In northern California, Washington, and Oregon, precipitation conditions were mixed and many areas had above-average amounts. Most western US areas are now in extreme or severe stages of drought, as of May 10th. See US Drought Monitor map [https://droughtmonitor.unl.edu/CurrentMap/StateDroughtMonitor.aspx?West here] for more information. | ||
+ | |||
+ | '''Panama and Costa Rica''' The stations included in CHIRPS resulted in large changes along the Atlantic side of Panama and Costa Rica. | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202204/CHIRPS_diff_GLB_PR_202204.png here] shows the difference between Prelim data and Final data, for April 2022. Overall, CHIRPS Final had higher rainfall amounts than Prelim, in most of the regions where data were different. | ||
+ | |||
+ | '''Rchecks plots''' There is a new high for CHIRPS-CHIRP in Latin America. This seems to be the result of a large number of very high measurements along the Colombian coast as well as Panama. Since they are in good agreement, this looks legitimate. | ||
+ | |||
+ | ===March 2022=== | ||
+ | |||
+ | '''Mozambique''' On March 11th, Cyclone Gombe made landfall in coastal Nampula Province as a Category 3 Tropical Cyclone. March CHIRPS Final data shows above-average rainfall in this region, in a large part due to this storm and above-average rain that occurred during the following week. Local sourced station and GTS reported 536.1 mm and 535.4 mm for the month, respectively. The cyclone brought large amounts of rain and flooding to central-northern Mozambique. In the city of Beira, to the south, the city's [https://abcnews.go.com/International/wireStory/beira-mozambique-hit-flooding-cyclone-gombe-83526697 mayor reported] that they had received more than 400 mm of rain in two days, associated with Cyclone Gombe. More about the destructive Cyclone Gombe can be read [https://reliefweb.int/report/mozambique/mozambique-tropical-cyclone-gombe-flash-update-no2-14-march-2022 here]. | ||
+ | |||
+ | '''Western U.S.''' The hydrologic drought worsened during March 2022. CHIRPS data shows monthly precipitation deficits over most areas of California, Oregon, and Washington (and farther east) in January, February, and March. Precipitation totals for that 3-month period, across coastal and southern Sierra Nevada mountains, are ~300 to 400+ mm (11-15+ inches) lower than typical amounts for that period. According to the U.S. Drought Monitor, "Water storage in the two largest reservoirs in the west – Lake Powell along the central Arizona/Utah border, and Lake Mead farther downstream along the Colorado River – has dropped to unprecedented levels. In early April, the combined storage was only 44 percent of the average since 1964." More on that at the [https://droughtmonitor.unl.edu/ US Drought Monitor]. | ||
+ | |||
+ | '''Southern California''' As predicted by the weather models, Southern California received a late season rain storm that soaked the Southland. It did not have much of an impact on the drought but delayed the start of fire season. The March CHIRPS reflects this rainfall event very well. More on this event is [https://www.washingtonpost.com/weather/2022/03/28/california-rain-cold-front-band/ here]. | ||
+ | |||
+ | '''Australia''' Severe flooding occurred in New South Wales and southern Queensland along Australia's East Coast, associated with record-breaking rainfall. Inclusion of more station reports led to CHIRPS showing much higher rainfall amounts there compared to CHIRP. CHIRP. More than 21 people died in the flooding; more on this extreme rainfall event can be read [https://www.theguardian.com/australia-news/ng-interactive/2022/mar/03/flood-map-nsw-qld-queensland-rain-chart-maps-brisbane-lismore-gympie-floods-weather-emergency-australia-east-coast here]. | ||
+ | |||
+ | '''Portugal and Spain''' In Portugal and northwestern Spain, CHIRP (without stations) depicted well-above average precipitation for the month of March that was significantly downgraded by local weather stations. The CHIRPS Final product is still above average, but the signal is considerably weaker than was seen in CHIRP. | ||
+ | |||
+ | '''Kazakhstan''' An unusual-looking precipitation pattern is visible in the CHIRPS in the Caspian Sea. The source of this feature was traced back to the CHIRPS climatology, which has data values over the Caspian Sea that form a shape similar to the Sea extent. The next version of CHIRPS climatology will mask out data values over the Caspian Sea (see e.g.; in EWX, the CHIMPS Clim 925 data layer). | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202203/CHIRPS_diff_GLB_PR_202203.png here] shows the difference between Prelim data and Final data, for March 2022. Many more station reports are blended during the CHIRPS Final processing. Where Prelim and Final estimates were different by more than 10 mm, in March 2022 data, most of these were instances of Final being wetter as opposed to being drier. Some areas with large "wet" differences are in Mozambique, southern Tanzania, western Zambia, western Republic of the Congo Namibia, coastal China, coastal southeast Australia, and portions of South America. Some of these changes were examined during Rchecks, and were found to correspond with stations reporting high rainfall impacts that seemed possible, such as in coastal central Mozambique (high localized rain amounts from Cyclone Gombe), in Republic of the Congo (IMERG-Late data also indicated localized wet conditions), and flooding rains in coastal Australia. | ||
+ | |||
+ | '''Rchecks plots''' All statistics are within previous values except in South America where a new CHIRPS mean and CHIRPS standard deviations set new highs but by small amounts. | ||
+ | |||
+ | ===February 2022=== | ||
+ | |||
+ | '''Australia''' During late February 2022, eastern Australia (southeast Queensland and northeast New South Wales) experienced major flooding due to extremely high rainfall. During February 22nd and 28th, Brisbane had its wettest 3 days on record, and other notable areas received over 1100 mm (That is more than 43 inches!). Read more from weatherzone.com.au [https://www.weatherzone.com.au/news/677-mm-in-three-days-breaks-brisbane-rainfall-record/536318 here]. CHIRPS data included numerous gauge reports in this region, and the reports being blended into the product results in good depiction of the observed spatial pattern. The satellite-based CHIRP estimates showed above-average rainfall, but greatly underestimated monthly totals and totals for late February. Because of this, CHIRPS estimated amounts are lower than many of the gauge reports; however, the data still show the historical extremity of rainfall. CHIRPS totals for the last 8 days of February are more than 3 standard deviations from the mean in the very wet areas. | ||
+ | |||
+ | '''Columbia''' Heavy rain and flooding in the department of Nariño, Colombia led to flash floods, destruction, and at least one fatality (see [https://floodlist.com/america/colombia-floods-narino-february-2022 Floodlist report]). CHIRPS data shows rainfall amounts as being substantially above average during this time, and very high amounts for February totals. The wet signal is coming both from CHIRP and the IDEAM gauge reports; the gauges are responsible for CHIRPS having very high values here. | ||
+ | |||
+ | '''Eastern Mediterranean''' In western Turkey, southern Bulgaria, and eastern Greece, blending of multiple station reports resulted in CHIRPS correctly reflecting above-average rainfall. CHIRP estimates were drier-than-average in these areas. | ||
+ | |||
+ | '''Western United States''' February 2022 CHIRPS depicts the severe ongoing dry conditions across much of the Western US. February is typically one of California's wettest months, but most areas received either no precipitation or a fraction of typical amounts, according to CHIRPS (and supported by numerous blended gauge reports). As shown by CHIRPS, December 2021 was wet but deficits during October, January, and February have resulted in much lower than average water year precipitation totals through February. According to the U.S. Drought Monitor, snow water equivalent values are below-normal in many Western basins, and parts of California's San Joaquin and Sacramento Valleys and Central Coast have experienced record dryness since January 2022. In those areas, some reservoirs are at record low levels and stream flows and soil moisture is ranking below the 2nd percentile (March 15th, 2022 summary). | ||
+ | |||
+ | '''CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/GLOBAL/version1/CHIRPS_diff/202202/CHIRPS_diff_GLB_PR_202202.png here] shows the difference between Prelim data and Final data, for February 2022. Many more station reports are blended during the CHIRPS Final processing. Where Prelim and Final estimates were different by more than 10 mm, in February 2022 data, most of these were instances of Final being wetter as opposed to being drier. Some areas with large "wet" differences are in western Tanzania, northern Zambia, northeastern Namibia/southwestern Angola, northern Brazil, and eastern Australia. | ||
+ | |||
+ | ===January 2022=== | ||
+ | |||
+ | '''Central America''' In eastern areas of Honduras, Nicaragua, and Costa Rica, and in northern Panama, CHIRPS Final is showing an area with large negative anomalies during January. The values show drier conditions than Prelim data had indicated. The pattern appears associated with multiple stations reporting below-average rainfall in central Honduras, two co-located stations in eastern Honduras, and multiple stations to stations to the south and east. The co-located eastern Honduras stations were examined using two layers in the EWX that show the influence of stations incorporated in the first “anchor blend” and 2nd blending step. Stations used in the 2nd blending step can have more influence. A good sign for validity of data is that these two reports generally agree that rainfall was very low compared to climatology, around 53 mm for GSOD and 35 mm for the locally-sourced report. CHIRPS values near this location are similar to these reported values. Overall, multiple stations and the satellite-based CHIRP provide support for drier-than-average conditions having occurred in Caribbean coast region of Central America in eastern Honduras and to the south. It is possible that low station density could obscure localized differences from this dry pattern. | ||
+ | |||
+ | ''' CHIRPS Final versus CHIRPS Prelim''' A map [https://data.chc.ucsb.edu/products/FEWSNET_NASA/Africa/WATERSTRESS/FINAL/202201/precip_diff.png here] shows the difference between Prelim data and Final data for Africa, for January 2022. In southern Africa, stations provided by SASSCAL and by Mozambique are blended into CHIRPS Final (along with reports from global networks). These quality-controlled resources can greatly improve precipitation estimates beyond what is achievable with satellite-based estimation and the pentadal-blended GTS stations. In January data, Mozambique and SASSCAL reports resulted in increased CHIRPS Final rainfall estimates in some areas affected by [https://watchers.news/2022/01/24/tropical-cyclone-ana-makes-landfall-over-mozambique/ Tropical Cyclone Ana]. Difference map provided by the FEWS NET NASA team. | ||
+ | |||
+ | '''Western USA''' January CHIRPS Final shows severe dry conditions in California's Sierra Nevada Mountain range, across central and northern California, and in western Oregon and Washington. CHIRPS data indicate that January precipitation totals are 4 to 5 inches (~100-150 mm) lower than average in many areas, while some localized deficits are around 8 inches for just the month of January. The data also show expansive drier-than-average conditions across the Western US for January, corresponding to the ongoing moderate-to-severe drought as described by the [https://droughtmonitor.unl.edu/ US Drought Monitor assessment] for early February | ||
+ | |||
+ | '''Ongoing dry conditions in portions of Southern Africa''' As shown by CHIRPS Final for January, in southwestern Angola, northwestern Namibia, southwestern Madagascar, and southern Mozambique. | ||
+ | |||
+ | '''Montana and Colorado, USA''' Stations were helpful in correcting for satellite-based (CHIRP) overestimation of precipitation in Montana, while both data types showed agreement about above-average January precipitation in the Denver area of Colorado. According to the [https://www.weather.gov/media/bou/Jan2022Cli.pdf Weather.gov January summary] for the Denver area, upper level disturbances, Pacific moisture, and orographic lift led to several snow events in the Rocky Mountain region, and the first month of above-average precipitation and below-average temperatures since May 2021. | ||
+ | |||
+ | '''Venezuela''' Rchecker Seth noted the inclusion of several additional station reports in Venezuela and that these agree with CHIRP estimates. | ||
+ | |||
+ | '''Australia''' In January CHIRPS Final, stations led to higher rainfall estimates in north and eastern Australia compared to CHIRP. An Rchecker noted that they usually observe similar estimates from CHIRP and station reports here. | ||
+ | |||
+ | '''Rchecks plots''' CHIRPS mean is at a new high for Africa, but by a very small amount. Otherwise, all statistics are with historical ranges. | ||
+ | |||
+ | === December 2021 === | ||
+ | |||
+ | '''Kenya''' CHIRPS Final data is notably wetter than preliminary estimates from CHIRPS Prelim, for December 2021 monthly totals in southeastern Kenya, northeastern Tanzania, and far southwestern Somalia. The higher December values resulted from the blending of multiple wetter-than-average station reports (some on the periphery of this area) with weaker but still wet anomalies estimated by the satellite component, CHIRP. Reports of swollen rivers and, sadly, [https://floodlist.com/africa/kenya-floods-december-2021 numerous fatalities] in Kitui County highlight the very high amounts of rainfall received recently in some areas. CHIRPS data indicates that the wettest period was in late December. Other satellite-based products like TAMSAT, RFE2, and IMERG-Late also estimate above-average December 2021 rainfall in this region, however, at lower levels of extremity than CHIRPS Final. Given the lack of station reports where CHIRPS estimates are very high, it is difficult to ascertain the accuracy of estimated values. Differences between rainfall products and the uneven station network suggest that CHIRPS may be overestimating rain totals in some of these areas. | ||
+ | |||
+ | '''Final vs. Prelim data''' As a reminder, CHIRPS Final data incorporates station reports from more sources than Prelim, and additional quality control procedures are applied for Final. For Africa data, Prelim data is based on CHIRP and the stations from GTS only. For December 2021 Final, no GTS reports were included due to the source having missing reports for 6 days of the month. Differences in Final and Prelim occur regularly, and are usually not systematic. An image showing the difference between CHIRPS Final and CHIRPS Preliminary, for October, November, and December 2021 totals in Africa, can be viewed [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2021/Africa_Final%20and%20Prelim%20difference%20for%20Oct-Nov-Dec%202021.PNG here.] | ||
+ | |||
+ | '''Mongolia and China''' More than 10 GHCN-v2 monthly stations and several GSOD stations reported precipitation in northwestern and eastern Mongolia and in northeastern China. Reports ranged from no precipitation to over 100 mm in China. December CHIRPS precipitation estimates are generally low across this region, due to low values in CHIRPS climatology as well as the influence of the mixed station reports. | ||
+ | |||
+ | '''Columbia''' No station reports from IDEAM for Columbia data. | ||
+ | |||
+ | '''Australia''' CHIRPS estimates shows high amounts of rainfall brought by a monsoonal low [https://www.theguardian.com/australia-news/2021/dec/25/boxing-day-cyclone-alert-for-northern-territory into the coastal Northern Territory], near Darwin, in late December. CHIRPS captured this due to the blending of station reports; CHIRP did not resolve this wet event. | ||
+ | |||
+ | '''Panama''' Coastal differences between station reports and CHIRPS Final estimates in Panama appear related to irregular spatial coverage of stations and its impact on the estimation algorithm. In CHIRP, the Atlantic Coast shows high rainfall, and the few stations there also show high rain. However, the Pacific side has more stations, and they are low, which drags down CHIRPS rainfall estimates on the Atlantic side. | ||
+ | |||
+ | '''Rchecks plots''' All regional stats fall within normal ranges this month. | ||
+ | |||
+ | === November 2021 === | ||
+ | |||
+ | '''India''' Southern India received very heavy rains during November, reportedly associated with five low pressure systems that developed in the North Indian Ocean Region and a later-than-normal exit of the southwest monsoon. In some areas, it was the wettest November since 1901. See [https://indianexpress.com/article/india/how-south-india-recorded-its-wettest-november-this-year-7657146/ this Indian Express] article for more information. CHIRPS data shows November rainfall as being more than 2 standard deviations from the mean across much of southern India. The very wet conditions are reported by numerous stations as well as the satellite-based CHIRP estimates, IMERG-Late, and Persiann-CCS data. The very wet conditions are reported by numerous stations as well as the satellite-based CHIRP estimates, IMERG-Late, and Persiann-CCS data. | ||
+ | |||
+ | '''Canada''' Highly above average rainfall was received in areas of British Columbia, with some stations reporting monthly totals that were more than 2 times higher than typical amounts. According to [https://www.cbc.ca/news/canada/british-columbia/bc-rain-records-november-2021-1.6269863 Environment and Climate Change Canada (ECCC)], the very wet conditions came after an extremely hot and dry summer, and that the occurrence of such extremes was consistent with climate change projections for Canada. Flooding in British Columbia, caused by the heavy rainfall events in November led to at least $450 million in damage, making it the "most costly severe weather event in the province's history,m according to the [https://www.cbc.ca/news/canada/british-columbia/bc-flood-damage-1.6280393 Insurance Bureau of Canada]. CHIRPS data captured the high November rainfall totals in B.C., Canada as well as in western Washington, USA. | ||
+ | |||
+ | '''Spain''' While rainfall totals were marginally above average for the month, the majority of rains came in short, extreme events, which caused [https://floodlist.com/europe/spain-floods-cantabria-basque-november-2021 flooding throughout Basque country] in mid- to late-November. | ||
+ | |||
+ | '''Italy''' CHIRP and stations capture extreme rainfall in Sardinia. On November 15, heavy rain of over 100 mm in 4 hours caused flooding in the south of the island, including the capital, Cagliari, and the communes of Villa San Pietro and Sant’Anna Arresi. According to [https://floodlist.com/europe/italy-floods-sardinia-november-2021 Floodlist], heavy rain had previously affected parts of the island of Sicily around 10 November, in particular in Agrigento and Trapani Provinces. Extreme CHIRPS values (~500) on the ball of the foot of Italy (Calabria, Italy) is an artifact of the elevation DEM that goes into CHIRPS. This is expected to be remedied in CHIRPS3.0. | ||
+ | |||
+ | '''Panama''' CHPclim having noticeable impacts on data artifact in Panama. This should be remedied in CHIRPS v3. | ||
+ | |||
+ | '''Nicaragua''' Rchecks identified a non-realistic-looking anomaly pattern in Nicaragua pre-release CHIRPS. A station with a high rainfall report in southwestern Nicaragua was identified as a probable source of the pattern (high z-score, low climatology, station is blended in the 2nd blending step). Experimentation with and without this station, in a test version of CHIRPS, confirmed that this was the case. It was omitted and the non-realistic pattern does not occur in CHIRPS Final. The Final data show a more narrow and coastally-located above-average rainfall pattern. In southeastern Nicaragua, those estimates may by influenced by wet reports at stations in southern coastal Honduras and northeastern Costa Rica. Some satellite data depict above-average rainfall in that area in late-November, and uncertainty is high due to low station density in that area. | ||
+ | |||
+ | '''Rchecks plots''' In the Africa region, new lows in CHIRPS mean, CHIRPS standard deviation and z-score mean. Most CHIRPS grid cells in East, Central, and Southern Africa have estimated below-average November rainfall. Globally, there were new highs in CHIRPS standard deviation and CHIRPS-CHIRP mean but only by a small amount. Haiti stats show new lows in CHIRPS mean, maximum, standard deviation and z-score by small amounts. This follows a dry trend that has been ongoing for several months. | ||
+ | |||
+ | === October 2021 === | ||
+ | |||
+ | '''East Africa''' October CHIRPS final data includes a substantial set of station reports that are blended into the CHIRP satellite IR-based rainfall estimates in eastern areas, with approximately 50 stations in Somalia (from FAO SWALIM) and 50+ stations in Ethiopia (from Ethiopia National Meteorological Agency). During Rchecks of this data, most were retained in processing. One station in southern Somalia was recommended to be excluded due to unreliable reporting and a suspected false zero. The October final data confirms below-average rainfall conditions shown in other less-station inclusive data sets, including in CHIRPS preliminary data. A figure that can be viewed [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2021/Oct2021/east_africa_rchecks_Oct2021-vs-Oct2020.PNG here] shows the station reports overlaid on the CHIRPS final estimates, for rainfall totals (left column), anomalies (middle column), and z-scores (right column). The top row shows these for October 2021. The bottom row shows these for October 2020, which was also a dry month and part of a poor performance Short Rains/Deyr SOND rainfall season. As can be seen in the maps, both stations and CHIRPS estimate show drier conditions in October 2021 in many affected areas. A major concern for this 2021 season, is that drier-than-average conditions have persisted throughout the season thus far, and that forecasts indicate are likely to continue through November. | ||
+ | |||
+ | '''Sicily, Italy''' CHIRP/IR data and stations captured [https://floodlist.com/africa/algeria-tunisia-italy-medicane-floods-october-2021 heavy rainfall that led to flooding] throughout Sicily in late October. Sicily Regions meteorological agency Servizio Informativo Agrometeorologico Siciliano reported 312.2 mm of rain fell in 24 hours to 25 October at a weather station at Linguaglossa. | ||
+ | |||
+ | '''Liguria province, Italy''' CHIRP/IR data failed to capture [https://floodlist.com/europe/italy-liguria-floods-october-2021 extreme flooding in northern Italy] in early October. Reports indicate 181mm of rainfall fell in 1 hour and >900 mm in 12 hours on October 4th/5th. During Rchecks is was identified that a station that normally reports in this area was not included. It was discovered that the data screening step eliminated the station value for being outside of of the acceptable distribution (z-score too high). This was corrected, and the station was included in CHIRPS final, and improved estimates in this region. | ||
+ | |||
+ | '''Columbia''' Says Rchecker Seth: "Yay, IDEAM Colombia station data are back!" This is great news for quality CHIRPS data in Columbia. | ||
+ | |||
+ | '''Oman and Pakistan''' Oman and Pakistan contain multiple stations from three different sources that demonstrate very high rainfall amounts that the CHIRP/IR estimates did not resolve. An intense rainfall event was confirmed in this area during the first week of October 2021. Cyclone Shaheen formed in the southeastern Arabian Sea and maintained its intensity as it made landfall. The last time a cyclone made landfall in northern Oman was in 1890, according to [https://www.mei.edu/publications/cyclone-shaheen-reminder-arabian-peninsulas-vulnerability-extreme-weather-events this article.] | ||
+ | |||
+ | '''Rchecks plots''' All statistics fall within previous ranges except for South America which had a new low for CHIRPS max. But very small difference. | ||
+ | |||
+ | === September 2021 === | ||
+ | |||
+ | '''Spain''' CHIRPS, informed by both the CHIRP satellite estimates and station reports, captured record rainfall across Spain. Heavy rainfall in two separate storms, in early and late September, caused [https://floodlist.com/europe/spain-floods-catalonia-september-2021 flash floods and destruction] in central and eastern Spain/Catalonia. | ||
+ | |||
+ | '''Thailand''' CHIRPS data, informed by both the CHIRP satellite estimates and station reports, captured very high September 2021 rainfall amounts in locations that were affected by Tropical Storm Dianmu and by heavy rain earlier in the month. According to [https://floodlist.com/asia/thailand-flood-update-september-2021 Floodlist], 229,220 households were impacted by flooding across northern and central Thailand. | ||
+ | |||
+ | '''India''' CHIRPS shows September 2021 was wetter than average in many areas across central and northern India. Many of these were impacted by heavy rains from Cyclone Gulab in late September, including near where it made [https://floodlist.com/asia/india-floods-cyclone-gulab-september-2021 landfall, between the east coast states of Odisha and Andhra Pradesh], as well as in areas to the west after it transitioned to a tropical depression. Numerous stations that were blended into CHIRPS reported above-average and high amounts for the month, which helped to increase the more muted wet signal shown by CHIRP in some areas. According to CHIRPS, consistent, above-average rainfall occurred in some western and northern states (e.g. Gujarat, Punjab) through September. | ||
+ | |||
+ | '''France''' CHIRPS, informed by station data, captured an extreme rainfall event in mid-September, which led to [https://floodlist.com/europe/france-floods-gard-september-2021 widespread flooding and dozens of rescues from flooding] in the towns of Uchaud, Bernis, Calvisson and Boissieres. | ||
+ | |||
+ | '''Honduras''' The addition of local station data, which began in January 2021, really paid off this month. They made quite a difference in modifying CHIRPS from the satellite-based CHIRP estimates. Rainfall amounts in CHIRP in some areas of western Honduras were 300-400 mm, where the station data and resulting CHIRPS were in the low 200s. | ||
+ | |||
+ | '''Panama''' There were no local station reports in Panama blended into CHIRPS this month. Also, the chpclim v2 climatology is producing an artifact of high precipitation, and its influence on CHIRPS is particularly bad this month. | ||
+ | |||
+ | '''Rchecks plots''' For the Hispaniola region, new lows where calculated for the CHIRPS mean, CHIRPS max and z score mean statistics. Low station reports contributed to these new lows which are just a small amount lower that the previous low values. All other statistics fall within previous value ranges. | ||
+ | |||
+ | === August 2021 === | ||
+ | |||
+ | '''Turkey, Ukraine, Russia''' Station reports that were blended into CHIRPS captured devastating amounts of precipitation from [https://watchers.news/2021/08/13/medistorm-falchion-black-sea-august-2021/ Medistorm Falchion]. This storm formed over the Black Sea and caused [https://floodlist.com/asia/turkey-floods-black-sea-august-2021 severe floods and landslides] in several provinces of Turkey, Ukraine, and Russia in mid-August. | ||
+ | |||
+ | '''Spain''' Station reports that were blended into CHIRPS captured abnormally high rainfall in southeastern Spain that led to flash floods in several areas in late September. There were reports of 45 mm of rainfall in a one hour. | ||
+ | |||
+ | '''India''' In Rajasthan, CHIRPS show high rainfall amounts that are corroborated by [https://floodlist.com/asia/india-floods-rajasthan-august-2021 reported flooding] in the area. CHIRP showed higher-than-average rainfall in this area, but stations increased the values quite a bit in CHIRPS. | ||
+ | |||
+ | '''Jamaica''' Station reports that were blended into CHIRPS, in southeastern Jamaica, show much higher rainfall than CHIRP. The reports may be associated with the [https://www.usnews.com/news/world/articles/2021-08-17/strengthening-storm-grace-pummels-jamaica-with-heavy-rain-wind heavy rain and flooding] caused by Tropical Storm Grace | ||
+ | |||
+ | '''Costa Rica''' A station report from the Nicoya Peninsula increased the CHIRPS estimates in northwestern Costa Rica. The CHIRPS estimates seems plausible, due to [https://qcostarica.com/at-least-160-people-affected-after-floods-in-jaco/ reported flooding in western Costa Rica] and due to stations further north on the Pacific Ocean coast of Central America also reporting high rainfall. | ||
+ | |||
+ | '''Canada''' CHIRPS data, based on CHIRP and the blended stations, as well as IMERG-Late data show substantially below-average rainfall for August 2021 in southeastern Canada (southern and eastern Ontario and in much of Quebec) and into the United States' Northeast (Maine). According to a Montreal CTV report, many areas received 25 to 50 percent of typical rainfall. Late August heat waves brought record-breaking high temperatures, such as in downtown Montreal where temperatures hit 35 °C on Aug. 21 (2° C higher than the previous record set in 1916). In Montreal, [https://montreal.ctvnews.ca/august-2021-was-the-hottest-on-record-for-montreal-1.5569995 August 2021 mean temperature was the hottest on record]. | ||
+ | |||
+ | '''United States''' Across many areas in the central and western United States, CHIRPS rainfall totals for June-July-August 2021 show mild to substantial rainfall deficits. The largest areas with substantially below-average 3-month totals are in Minnesota and Kansas, and in other Midwestern states. While above-average August rains in some northern areas eased deficits, low August rainfall in eastern Colorado, Kansas, added to the ongoing deficits from June and July. In the southern and eastern United States, and in some southwestern monsoon-affected areas, CHIRPS shows average or wetter-than-average conditions. High rainfall amounts in Alabama and Mississippi are in part due to [https://www.weather.gov/mob/ida Hurricane Ida]. | ||
+ | |||
+ | '''Columbia''' Unfortunately, this is another month without station reports from IDEAM for Columbia. | ||
+ | |||
+ | '''Rchecks plots''' Other than a new high (just barely) for CHIRPS standard deviation in the Sahel, all stats look good and are within the normal ranges. | ||
+ | |||
+ | === July 2021 === | ||
+ | |||
+ | '''South Africa''' Several stations reported above-average precipitation in the western Cape region, which is likely associated with the severe weather reported in the area. See reports [https://www.news24.com/news24/SouthAfrica/News/weather-warning-flooding-snow-expected-as-western-cape-battered-by-another-cold-front-20210712 here] and [https://www.news24.com/news24/southafrica/news/cape-town-authorities-urge-caution-as-another-cold-front-hits-the-city-20210708 here]. The station reports, combined with the CHIRPS blending process, are producing overall above-average CHIRPS estimates across this region. The satellite-only CHIRP does not indicate a wetter-than-average July. Stations show a mixed precipitation pattern, and IMERG-Late shows a more localized mixed pattern, compared to the CHIRPS estimates. | ||
+ | |||
+ | '''New Zealand''' Heavy rainfall on west coast of the South Island in CHIRP is backed up by news reports, e.g. [https://www.theguardian.com/world/2021/jul/19/new-zealand-west-coast-hit-by-heavy-floods-after-month-of-rain-falls-in-one-weekend here]. CHIRPS lowers the rainfall amounts because it is averaging in stations on the other side of the island. | ||
+ | |||
+ | '''Romania''' Stations captured exceptionally high rainfall in central Romania mid-July, which led to [https://floodlist.com/europe/romania-floods-july-2021 widespread flooding] in Lerești, Argeș County and in Busteni in Prahova County. | ||
+ | |||
+ | '''Columbia''' July 2021 was another month without the good station coverage that CHIRPS had, until recently, in Columbia. This is a topographically complex country, and reports for July were limited to a low elevation valley. | ||
+ | |||
+ | '''Southwestern US''' A map series that compares CHIRPS, CHIRP, and IMERG-Late precipitation estimates, and station reports for July 2021, can be viewed [https://data.chc.ucsb.edu/people/laura/RChecks_figures/Jul2021/CHIRPS%20vs%20CHIRP%20vs%20IMERG%20vs%20stations_Jul2021.PNG here]. The lower right map shows station reports as boxes with black symbols, with the box color indicating reported value, and the underlying CHIRPS as the pixelated background. One can see the broad similarities between CHIRPS spatial patterns and station-observed amounts, which is coming from both the satellite-only component (CHIRP) and the blended stations. Compared to the stations that reported, CHIRP (upper right map) estimates underestimated station reports in many areas, as can be seen from the comparatively higher amounts in CHIRPS (post station blending) than in CHIRP. IMERG-Late (lower left map) overestimated the amount and spatial extent of high precipitation in southeastern Arizona and southwestern New Mexico and in other locations in the Four Corners region during July 2021. In the southern and eastern California desert, IMERG-Late shows extensive low rainfall amounts, in contrast to the dry conditions reported at most stations. | ||
+ | |||
+ | '''Panama''' The climatology data appears to be making a similar artifact in CHIRPS as was noted for the June 2021 data. We anticipate this will be improved in the next version of CHIRPS. | ||
+ | |||
+ | '''Rchecks plots''' All statistics fall within previous ranges, with the exception of a new CHIRPS maximum for the Global region. The turns out to be on Asuncion Island near 145E, 19N, part of the North Marianas Island chain. There was something similar last month with a value of over 2200 on an island chain off of eastern Africa. | ||
+ | |||
+ | === June 2021 === | ||
+ | |||
+ | '''Columbia''' CHIRPS typically has many stations from Columbia, but in the past several months (March to June 2021), this data source has not been reporting into CHIRPS. Instead, June 2021 CHIRPS ingested more sparse GHCN v2 stations. | ||
+ | |||
+ | '''United States''' Historic high rainfall amounts occurred in southeastern Arkansas and Mississippi in June 2021, which is shown by very high anomalies in CHIRPS. Near Dumas, Arkansas, one of the [https://www.weather.gov/lzk/jun2021.htm hardest hit areas] by a June 8 to 10 storm reported 22 inches of rain for the month. According to [https://weather.com/news/news/2021-06-10-flooding-arkansas-mississippi-dumas-desha reports], some areas received more rain in two days than is typically seen in months. Flooding and damage to homes farmland occurred throughout the region. | ||
+ | |||
+ | '''Panama''' Artifact showing high rainfall, linked to the CHPclim v2. A new version of CHPclim will be included in CHIRPS v3. | ||
+ | |||
+ | '''Southeastern Africa''' Artifacts in eastern Mozambique and eastern Madagascar due to CHPClim, which should be corrected by CHIRPS v3 | ||
+ | |||
+ | '''Tanzania-Mozambique''' CHIRPS shows above-average June rainfall in southern coastal Tanzania, northern coastal Mozambique, and the Comoros islands. This is coming from reports of higher-than-average rainfall from three stations in the area. Estimates may be amplified due to one of them being double-blended (a GSOD station in southern Tanzania reporting ~114 mm). | ||
+ | |||
+ | === May 2021 === | ||
+ | |||
+ | '''Ethiopia''' Very wet conditions from late April to early to mid May resulted in flooding damages that [http://floodlist.com/africa/ethiopia-floods-afar-snnp-somali-may-2021 displaced 70,000 people] in parts of the Afar, Somali, and SNNP regions of Ethiopia. This very wet period was preceeded by a very dry February to middle of April, and followed by dry conditions after middle May in many areas. NMA stations provided to CHIRPS report atyically high May rainfall amounts in Dire Dawa City (155 mm), a location of 9 fatalities, and for other stations in these regions and in Amhara and northern Oromia regions. CHIRPS Final May totals are informed by the ~50 NMA stations and the CHIRP satellite-bsed estimates, which show a similar spatial pattern for anomalies as the monthly station reports. There are only 2 CHIRPS-reporting stations in Afar. This low density makes it challenging to observe localized rain there. | ||
+ | |||
+ | '''Somalia''' Flash flooding near Jowhar and Mogadishu (southern-central Somalia) caused [http://floodlist.com/africa/somalia-floods-mogadishu-jowhar-may-2021 fatalities and damages to homes and crops] in early May. Two of the three nearby SWALIM stations report May rainfall totals that were above average; reported amounts were 126 mm and 182 mm. At Mogadishu, CHIRPS received two reports from two stations: one from GSOD for 42.5 mm and one from SWALIM for 0 mm. The latter was deemed a false zero and removed from Final blending. CHIRPS monthly totals will show above average rainfall for the month in the Jowhar area, however, the rainfall amounts estimated in CHIRPS will likely be lower than the wet SWALIM reports. | ||
+ | |||
+ | '''Louisiana''' May rainfall totals in southeastern Louisiana are around 2 standard deviations above average. In the Lake Charles and Baton Rouge area a May 17th rain event was [http://floodlist.com/america/usa/floods-louisiana-texas-may-2021 reported as the third wettest] in city history and hundreds of building were flooded. | ||
+ | |||
+ | '''Panama''' CHPclim has a rectangular-shaped artifact in May climatology in the center-east part of the isthmus. This makes CHIRPS values look unrealistic there. | ||
+ | |||
+ | '''Rchecks plots''' All statistics for this month's CHIRPS final data are within normal ranges. | ||
+ | |||
+ | === April 2021 === | ||
+ | |||
+ | '''Kenya''' April is a critical month for the March to May season in the eastern East Africa. In Kenya, April CHIRPS shows below average rainfall across most of the country. A few areas had above average April rainfall: In western Kenya, in localized areas of the southeast, and in the extreme northeast. | ||
+ | |||
+ | '''United States''' CHIRPS shows large negative anomalies along the western US Sierra Nevada and Cascade mountain ranges. April rainfall was below average across the Western US, in the central Midwest, and in the central-northern Eastern US. Above average rainfall is along the Gulf Coast, with historically prominent anomalies (high z-scores) in Louisiana. According to the National Weather Service, the first half of April was the second wettest on record for New Orleans (reported by Nola.com, article [https://www.nola.com/news/weather/article_601f86bc-9e34-11eb-ad27-e75430b7a2ce.html here]). The current US Drought Monitor map for the Western US ([https://droughtmonitor.unl.edu/CurrentMap/StateDroughtMonitor.aspx?West here) shows an unsettling situation for that region as it enters the annual peak fire season: Most areas are in drought, ranging from severe to exceptional levels. Let's hope someone has finally started raking the forests. | ||
+ | |||
+ | '''Columbia''' Minimal stations reporting again this month. The ones that were there agreed well with CHIRP but it is still unusual to not have 100+ stations. | ||
+ | |||
+ | '''Costa Rica and Panama''' Stations reporting to CHIRPS increase rainfall estimates on the Atlantic coast of Costa Rica and Panama. This is in agreement with CMORPH data. | ||
+ | |||
+ | '''Guatemala''' A number of stations in the mountain range near the Pacific coast have (much) higher values than CHIRP; it doesn't seem to handle orographic effects well here. | ||
+ | |||
+ | '''Papua''' There are some odd values in West Papua and Trangan. These appear related due to the current CHPclim. | ||
+ | |||
+ | '''Australia''' In northern Queensland, stations are a bit higher than CHIRP, raising rainfall from Cape York down to a little south of Cairns. | ||
+ | |||
+ | '''Taiwan''' A station on Pengjia Islet, an island to the north of Taiwan, is reporting a low value of 4.1 mm, compared to CHIRP values of between 90-145 mm in this region. Similarly, two stations in Taiwan are also reporting a value which appears to be too low relative to the CHIRP values, 9.4 mm and 20.7 mm compared to 87-150 mm respectively. While the CHIRP anomaly for north and central Taiwan is low, at between -45 and 3.5, the stations are significantly lower with anomaly readings of -128 to - 145. These three stations are having a significant effect on the CHIRPS values for the northern half of Taiwan, bringing the CHIRPS values down quite a bit. Because they differ so significantly from the CHIRP as well as the climatological average, they have been removed during the r-checks process. | ||
+ | |||
+ | '''Rchecks plots''' Two features: A new low for Southern Africa CHIRPS - CHIRP (April mean values), and the global CHIRPS z-score was very low (tying the 1987 minimum value). | ||
+ | |||
+ | === March 2021 === | ||
+ | |||
+ | '''Columbia''' IDEAM stations for Columbia were not included in March 2021 CHIRPS Final, so data quality may be low there. If IDEAM reports are received they might be included in another run of March 2021 CHIRPS Final. | ||
+ | |||
+ | '''China''' March marks the sixth continuous month of anomalous dryness in Taiwan as well as parts of southeastern China. CHIRPS is doing well at capturing both the intensity and duration of this drought. Upon looking at March’s CHIRPS R-checks, the rain gauge stations and infrared satellite products are in agreement and show another anomalously dry month. In fact, according to CNBC’s Pacific Asia News, Taiwan’s president tells residents to conserve water as the island faces the worst drought in “56 years”. A link to that information is [https://www.cnbc.com/2021/03/08/taiwan-water-shortage-president-says-to-brace-for-a-shortage.html here]. | ||
+ | |||
+ | '''Morocco''' Extreme high rainfall amounts reported for March (156 mm and 238 mm) in and near the city of Tetouan in northern Morocco appear to be corroborated by a Floodlist report: " Heavy rain caused dramatic flash flooding in the city of Tétouan in northern Morocco on 01 March 2021. Roads and infrastructure were damaged and fast flowing flood waters and debris swept through streets dragging along vehicles. Local government reported 100 mm of rain in 9 hours to the afternoon of 01 March which caused rivers and drainage channels to overflow." | ||
+ | '''Australia''' The eastern coast of Australia was in the news in March for rain/flooding. CHIRP rainfall estimates were high, but the blended stations appear to improve CHIRPS by increasing amounts. | ||
+ | |||
+ | '''USA''' Stations in the southeastern United States shifted the bulk of the precipitation north compared to CHIRP. Marty speculates that the effect may be from high clouds drifting south with the cold front(s) have already rained out, but the IR temps are still low enough to make the CHIRP processing estimate rainfall there. | ||
+ | |||
+ | '''Egypt''' There are several stations that reported very high and likely inaccurate values around 70 mm to 101 mm in northeastern Egypt. These were omitted from CHIRPS because they were extremely different from climatology (near zero) and CHIRP and other rainfall products did not indicate widespread highly anomalous rainfall. | ||
+ | |||
+ | '''Central America''' CHIRP estimates on the Atlantic side of Panama/Costa Rica quite low and the stations blended in seem to improve this. | ||
+ | |||
+ | '''Kazakhstan''' In south-central Kazakhstan, a GTS station with a monthly value of 701.8 mm was eliminated from the March CHIRPS final through the reality checks process. Compared to the anomalously high value of this station, the CHIRP pixel values for the same area range from 13-16 mm. Furthermore, this station recorded an anomaly value of approximately plus 686 mm compared to the CHIRP anomaly of between -2 and 0 mm for the exact same area. | ||
+ | |||
+ | '''Rchecks plots''' No report available | ||
+ | |||
+ | Contributors: Marty Landsfeld, Laura Harrison, Austin Sonnier, Seth Peterson, Will Turner, Pete Peterson | ||
+ | |||
+ | === February 2021 === | ||
+ | |||
+ | '''Africa''' Earlier drier than average conditions in December to January continued in February in south-central Angola, northwestern Namibia, northeastern Mozambique, east coast of Madagascar, parts of southern South Africa, and parts of central Oromia region of Ethiopia. Wetter-than-average conditions in December to January were followed by above-average February rainfall in Botswana, southern Zimbabwe, southern Mozambique, and Liberia. | ||
+ | |||
+ | '''Russia''' Record snowfall (73cm) was reported in mid-February in southern Russia, near Sochi and the Black Sea, which appears to be captured in the CHIRPS products. See [https://twitter.com/ZdenekNejedly/status/1362380939154907137 here] for more on this event. | ||
+ | |||
+ | '''Tajikistan''' A station near the cities of Chkalovsk and Khujand in northern Tajikistan was omitted from February’s CHIRPS through the R-checks process. Evidence for the station’s removal was found upon comparing the station reported value of 319.9 mm to CHIRP, the satellite-based estimate, and the CHIRPS climatology near the station. CHIRP recorded a value between 18 mm and 24 mm for the same area. Given that the station report was also far higher than climatology (~20mm), the report was deemed potentially inaccurate and omitted. | ||
+ | |||
+ | '''Pakistan''' Across northern Pakistan, multiple stations reported February precipitation totals that were lower than CHIRP estimates. For example, a station near the town of Dir in northwest Pakistan recorded a February monthly total of 47.7 mm, indicating below average conditions, while CHIRP values nearby are around 130 mm, indicating near average conditions. Given that multiple stations had this feature, all those reports were blended into CHIRPS. This CHIRP and CHIRPS Rchecks discrepancy will be noted and, if found to be recurring, will be subjected to further scrutiny. | ||
+ | |||
+ | '''Honduras''' The new stations in Honduras continue to show helpful data. Rchecks note: For some reason some switched from fGSOD in January to fGTS in February. | ||
+ | |||
+ | '''California''' Below-average precipitation in February 2021, according to CHIRPS and with support from many stations. Z-scores for February range from around -0.8 to -1.4. While parts of central California received above average January precipitation, the prevailing conditions from October to February have been drier-than-average across California. | ||
+ | |||
+ | '''Rchecks plots''' All stats for all regions fell within the previous minimum and maximums. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Laura Harrison, Austin Sonnier, Pete Peterson | ||
+ | |||
+ | === January 2021 === | ||
+ | |||
+ | '''Honduras''' There are new stations in Honduras reporting to CHIRPS, from COPECO. January 2021 CHIRPS data blended in 42 of these stations. Rchecker Seth reports that their values look good. | ||
+ | |||
+ | '''Kenya''' There is one station report included in January 2021 CHIRPS in Kenya, a GSOD in western Kenya. This is highly out of the ordinary. CHIRPS has always had at least 10 stations, GSOD and GTS sources, blended into monthly data in Kenya. According to Pete, the low count is not due to a processing issue at CHC, as all the GSOD and GTS station reports come to the CHIRPS process via a single download and these exist in many other countries for January 2021. One possibility is that more of Kenya's stations had not yet been reported to that source by the time of download. The implication of low station count is that January 2021 CHIRPS data in Kenya is mainly based on CHIRP and some influence from stations in Ethiopia, Somalia, Tanzania, and potentially Rwanda. Other nearby countries do not have station reports in CHIRPS this month. | ||
+ | |||
+ | '''Southern Africa''' Since October 2020, Southern Africa's monsoon season has exhibited lower-than-average monthly rainfall in Angola, northeastern Mozambique, and Madagascar and higher-than-average rainfall in central region areas. January 2020 CHIRPS data shows one of the more extreme months thus far into this season in this regard, with extensive above average rainfall from Namibia to central-southern Mozambique and including southern Zambia, Malawi, and central-northern South Africa. This expansive wet signal is coming from CHIRP, the satellite-only part of CHIRPS, and also from many station reports. However, across this wide region there are also station reports that show lesser amounts, and below-average or average rainfall. These seem to be swamped out by the combination of a wet CHIRP and numerous wet stations. So while there seems to be evidence for wetter-than-average conditions in January in much of continental Southern Africa, there is probably a more spatially mixed pattern than CHIRPS data indicates. | ||
+ | |||
+ | '''Burundi''' Conflicting reports from CHIRPS Prelim, CHIRPS final, and news media. According to reports, Burundi suffered from extreme rainfall in early and late January, which appears to be captured by CHIRPS Prelim. However, CHIRPS final shows below average rainfall for the month of January. It is unclear what station values led to this discrepancy between CHIRPS Prelim and Final. See [http://floodlist.com/africa/burundi-floods-bujumbura-january-2021 here] for that media report. | ||
+ | |||
+ | '''Tanzania''' CHIRPS stations capture extreme rainfall and flooding that occurred in the southeast (Mtwara) region of Tanzania in mid-January. See [http://floodlist.com/africa/tanzania-flood-mtwara-january-2021 here] for the report on the floods. | ||
+ | |||
+ | '''Central America''' Atlantic coast of Costa Rica and Panama shows quite high rain amounts in CHIRP, and the stations bring these satellite-based estimates lower. Looks like the high values in neighboring Nicaragua should come down, too, but no stations there, unfortunately. | ||
+ | |||
+ | '''South America''' The blended stations are increasing rainfall values compared to CHIRP, resulting in better agreement between CHIRPS and CMORPH estimates, in the Brazil/Paraguay area and the Amazon. | ||
+ | |||
+ | '''Rchecks plots''' A new low for CHIRPS - CHIRP Mean for Haiti. The value is only 12 mm lower then previous values though. New highs for CHIRPS mean, Z score mean and CHIRPS - CHIRP mean in southern Africa. But all are minor and it appears that stations significantly increased estimates in the region. See the '''Southern Africa''' entry above for more commentary. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Laura Harrison, Austin Sonnier, Pete Peterson | ||
+ | |||
+ | === December 2020 === | ||
+ | |||
+ | '''Mozambique and Zimbabwe''' Stations (and CHIRPS) accurately captured heavy rainfall from Tropical Storm Chalane, which made its second landfall in southern Mozambique, in Beira, after passing over northern Madagascar in late December. The storm brought high winds and ~200 mm of rainfall to south central Mozambique and Zimbabwe, resulting in some flash flooding. However, damages were reported to be minimal, relative to expectations. You can read more about Tropical Storm Chalane [https://reliefweb.int/sites/reliefweb.int/files/resources/ROSEA_20201224_TropicalStormChalane_FlashUpdate%232%20%281%29.pdf at ReliefWeb] and [https://www.reuters.com/article/us-mozambique-cyclone/tropical-storm-chalane-hits-mozambique-but-causes-little-damage-idUSKBN2940Y4 at Reuters]. | ||
+ | |||
+ | '''Mozambique and Madagascar''' Stations and satellite-based estimates (CHIRP) are in agreement regarding the December 2020 deficits in northern Mozambique and southern central Madagascar. Approximately 5 stations in each of these regions report large deficits for December. At a seasonal time scale, deficits have persisted and have accumulated to led to the October 1st 2020 to January 15th 2021 period as having the lowest rainfall total on CHIRPS record in some of these areas. The CHC Early Estimate historical rank map shows this, [https://data.chc.ucsb.edu/products/Season_Monitor/africa_southern/oct_to_apr/pngs/archive/Rank_21PentAccum_2021_p03.png here]. More CHC Early Estimates are available at the UCSB [https://chc.ucsb.edu/monitoring/ Climate Hazards Center monitoring and forecasting site]. | ||
+ | |||
+ | '''Angola''' CHIRP is showing that December 2020 was drier than average across much of western Angola, and that an area in central-western Angola had 100+ mm deficits. Several SASSCAL stations in southern Angola reported that December was drier than average. Due to very few stations in CHIRPS in Angola, much of the dry signal is coming from CHIRP. | ||
+ | |||
+ | '''Saudi Arabia''' Unique storm cell in northern Saudi Arabia. CHIRPS recorded above average December 2020 rainfall in the northeast region of Saudi Arabia. This appears to be associated with an observed extreme storm system that created one of the largest tornadoes on record for this region, along with heavy rainfall and hail. Video of the tornado is available from The Watchers news [https://watchers.news/2020/12/07/large-tornado-saudi-arabia-december-2020/ at this link]. Other local news organizations also reported on the event. Stations in the region, as well as in Kuwait and southern Iraq, reported rain gauge measurements in the 55.0-70.0 mm range to CHIRPS. These reports corroborated the rainfall event and, importantly for CHIRPS data, increased estimates in northern Saudi Arabia, raising the ~ 11 mm satellite-based CHIRP anomalies to ~ 26 mm anomalies in CHIRPS. | ||
+ | |||
+ | '''Tajikistan''' A station in southern Tajikistan, which recorded a rain gauge monthly value of 2.0 mm, was eliminated from the December’s CHIRPS through the R-checks process. Evidence for the station’s removal was found upon comparing the gauge value to both the CHIRP value and its two nearest neighbors. The CHIRP values in the area immediately surrounding the station in question, southern Tajikistan, eastern Afghanistan, and northern Pakistan, range from 30 mm to 90 mm. Furthermore, the two nearest neighbors recorded a rain gauge value of 28 mm and 53.4 mm. | ||
+ | |||
+ | '''United States''' Olympic Peninsula-- Several stations reported much higher values than CHIRP, and were responsible for raising CHIRPS estimates here by 100 mm to 200 mm compared to CHIRP. | ||
+ | |||
+ | '''Rchecks plots''' All the Rchecks plots look good. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Austin Sonnier, Will Turner, Seth Peterson, Laura Harrison, Pete Peterson | ||
+ | |||
+ | === November 2020 === | ||
+ | |||
+ | '''Somalia- Cyclone Gati''' Cyclone Gati, the [https://earthobservatory.nasa.gov/images/147576/gati-makes-historic-landfall-in-somalia strongest storm to hit Somalia in at least 50 years], brought heavy rains to Ras Hafun (the eastern point of the Horn of Africa). SWALIM stations reported 156mm, 151mm, and 71mm to normally dry areas here. CHIRPS final for November failed to reproduce these amounts in values and anomalies. Z scores, however, do show that CHIRPS amounts were historically extreme. CHIRPS users would thus want to work with percent of averages, or z scores, if they need to show the severity of the monthly rainfall in these Gati-affected areas. The CHIRPS version 2 estimates are closely tied to variations from climatology, and this is an excellent example of how that technique can go wrong. Efforts are being made in the production of a new version of CHIRPS, version 3, to limit this kind of problem. | ||
+ | |||
+ | '''Eastern Africa''' November brought below average rainfall to much of the eastern Horn of Africa, according to CHIRPS and other rainfall products. Some noteable differences between CHIRPS prelim and final are that November rainfall anomalies are more negative in CHIRPS final than in CHIRPS prelim in central-eastern Kenya, southwestern Somalia, and in some of southwestern Ethiopia. Unlike prelim, CHIRPS final shows fewer areas in southern Somalia with pockets of average to above average rainfall-- rather, below average is shown across most areas. This signal is reflecting reports from 15 stations there, of which only two show average to above average rainfall. None of these reports jump out as being bad values. There is an area where reported localized rainfall is not being represented in CHIRPS: A very wet station in dry northeastern Kenya reported 157 mm (~ 100 mm above average) but CHIRPS shows below average across this area with no clear sign of localized rainfall. By comparison, CHIRPS prelim does show more localized rainfall patterns in these areas. | ||
+ | |||
+ | '''Mozambique''' We are omitting reports of what appear to be false zeros from two stations in the Tete administration of northwest Mozambique. These two stations are located just east of the Cahora Bassa Lake. Other stations, CHIRP, and CHIRPS Prelim are demonstrating November rainfall nearby, as do other rainfall datasets. For example, the CHIRP value at these station locations is approximately 42 mm and the CHIRPS Prelim value for the location is approximately 45 mm. The reported 0 mm amounts at these stations had translated into ~ -54 mm anomalies, while CHIRPS Prelim anomalies were smaller, approximately -10 mm. | ||
+ | |||
+ | '''Europe''' November 2020 was drier than average across much of Europe, and large deficits were seen in eastern Southern Europe. Deficits in northern Italy and Mediterranean coast areas of Montenegro and Greece were some of the largest. Amounts in those areas that were 100mm to 150mm below average. The CHIRPS signal is coming from numerous stations across the region and CHIRP. | ||
+ | |||
+ | '''Cuba''' A slightly wet station (284835) on the dry side of Cuba jacks up values on the wet side to 600mm of rain, far above the values that CMORPH shows (it agrees with CHIRP). | ||
+ | |||
+ | '''Indonesia''' In Indonesia (Irian Jaya)/Papua New Guinea, there is an interesting and questionable pattern in CHIRPS. It shows much wetter than average in the south and below average in the north. The CHIRPS pattern appears related to the anomalies coming from one station in each area. However, the pattern looks questionable due to there being a spatially less distinct anomaly pattern in prelim, and the surpisingly higher than average amounts estimated in CHIRPS' very wet area compared to the southern station. | ||
+ | |||
+ | '''Rchecks plots''' | ||
+ | |||
+ | Contributors: Marty Landsfeld, Austin Sonnier, Seth Peterson, Laura Harrison, Pete Peterson | ||
+ | |||
+ | === October 2020 === | ||
+ | |||
+ | '''Southern Africa data''' Update, 11/20: CHIRPS October 2020 data has been corrected in response to this issue. It was discovered that there were two factors responsible for the problems: (a) Errors in Mozambique station reports from a preprocessing step (quick correction of the errors enabled the reports to be blended in the corrected CHIRPS Final) and (b) that the reports had been included in a 2nd blending step that overrode many reports in South Africa. The wet Mozambique reports had been thought to be possible, due to news reports of extensive flooding, but the corrected monthly totals look much more reasonable. These show October 2020 totals in Mozambique ranged from localized above average (this may still correspond to flooding reports) to minor deficits in central and other areas. In addition to corrected CHIRPS data, another positive outcome is that the Rchecks process came in handy and a new data layer showing 2nd blended stations will be tested to help diagnose similar issue in the future. Previous: CHIRPS October 2020 data is wetter than is indicated by numerous stations reports in part of eastern South Africa. Users of CHIRPS preliminary data will notice that CHIRPS final is much wetter than preliminary data. See [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2020/final%20anomaly%20vs%20rchecks%20vs%20prelim%20sa.PNG here] for a snapshot of October 2020 anomaly from these datasets: from left to right, CHIRPS preliminary, CHIRPS final with station anomalies indicated in the overlaid boxes, and CHIRPS final. The 'wetting' in CHIRPS final in Mozambique is in line with stations reports in Mozambique that were included in final data (and not in preliminary data). These stations are in line with reports of flooding in | ||
+ | [http://floodlist.com/africa/mozambique-floods-october-2020 the provinces of Niassa, Nampula, Zambézia and Manica and in Maputo city]. Wetting in eastern Zimbabwe is probably coming from the wet Mozambique observations too. Something also shown by the data comparison snapshot, is that in east central South Africa most of the stations report below average rainfall, like preliminary and other datasets, but CHIRPS final shows above average. This issue could be related to one or more things, and is currently unresolved. One factor could be that local or regional wet station(s) are having a disproportional, primary influence in the blending procedure in this area. Preliminary data from the South African Weather Service also show a much drier October than does CHIRPS final in east central South Africa, shown [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2020/za%20prelim%20oct.png here]. CHIRPS users should thus be cautious about the wet conditions shown by the CHIRPS final data in that area. | ||
+ | |||
+ | '''Ethiopia''' Southeastern Ethiopia CHIRPS data appears to underestimate rainfall for the September 1 to November 10th, 2020 period, compared to blended data that includes CHIRPS and a larger number of Ethiopia NMA station reports. Some of the data difference could be related to a station gap in the southeast in the October CHIRPS Final data. Typically there is one NMA report blended into CHIRPS Final data, in Somali's Gode zone, but this month it reported as a no data value. A different source shows 44mm reported at that location in October 11-20th, 2020. There is low station density in this part of Ethiopia in CHIRPS Final, and the low estimates were possibly influenced by stations farther away, such as below average reports in Somalia. This may help explain why CHIRPS Final is drier than CHIRPS Prelim in this region in October 2020 data. | ||
+ | |||
+ | '''Italy and eastern Europe''' Stations captured extreme rainfall values in Italy and eastern Europe at the end of October. Severe weather swept across Europe at the end of October. Strong winds, roughs seas, heavy rain, and thunderstorms caused deadly flooding, damage and power outages in Italy, Croatia, Slovenia, Bosnia, France and Switzerland. | ||
+ | |||
+ | '''Vietnam''' October was an active typhoon month for parts of southeast Asia. Typhoon Molave, also known as Typhoon Quinta in the Philippines, made landfall over the Philippines, Vietnam, Laos, Cambodia, and Thailand. A large swath of Vietnam's central coast saw flooding as October monthly totals reached well over 1,500 mm with many areas reaching over 1,800 mm. A station between the cities of Da Nang and Hoi An, for instance, recorded a value of 1863.3 mm. These totals are anomalously high for October in Vietnam. The CHIRPS anomaly for the central Vietnam coast was well over 1000 mm. See [https://www.cnn.com/2020/10/28/asia/vietnam-typhoon-molave-destruction-intl-hnk/index.html here] and [https://www.thenewhumanitarian.org/maps-and-graphics/2020/10/27/asia-vietnam-flood-october-cyclone here] for more information about the typhoons. | ||
+ | |||
+ | '''United States and Mexico''' A dry October for the western and central United States, Texas, and in northern and central Mexico. CHIRPS data shows October 2020 rainfall as being 0.5 to 1.5 standard deviations below average in many areas. | ||
+ | |||
+ | '''Mexico''' Tropical Storm Gamma brought heavy rain and damage to the Yucatan Peninsula on October 4th, 2020. CHIRPS is showing high amounts for October in coastal areas that were affected, with anomalies for the month ranging from 300 mm to 600 mm above average. More on Gamma [http://floodlist.com/america/mexico-floods-storm-gamma-october-2020 here]. | ||
+ | |||
+ | '''Panama''' There were only 3 stations reporting to CHIRPS final this month, usually there are ~14 | ||
+ | |||
+ | '''Rchecks plots''' Southern Africa posted a new high for CHIRPS - CHIRP of 13mm. The previous high was 10mm. This is related to the wetting in CHIRPS final; please see the entry 'Southern Africa data' above for more on this. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Laura Harrison, Pete Peterson | ||
+ | |||
+ | === September 2020 === | ||
+ | '''New station sources have been added to CHIRPS''' Two new sources of in situ rainfall observations were implemented in this month's CHIRPS, Brazil-Cemaden and Costa Rica-IMN. This exciting addition brings the number of sources to fifteen. In addition to global coverage from GHCN-daily, GTS, GSOD, and GHCN-v4, special contributions from national and regional sources are a big reason CHIRPS is able to provide quality rainfall estimates. Special contributions provide enhanced in situ coverage in Southern Africa, Mozambique, Somalia, Ethiopia, Brazil, Chile, Colombia, Panama, Guatemala, Costa Rica, and Mexico. There are plans to include Trans-African HydroMeteorological Observatory (TAHMO) TAMHO reports in the future to increase coverage in Africa. | ||
+ | |||
+ | '''New source Rchecks''' This included visual checks and comparisons of reported values to multiple datasets for September 2020. Brazil-Cemaden and Costa Rica-IMN reports passed these checks and were given the green light for including in CHIRPS. Rchecker Seth noted that in Costa Rica, "the 15 new stations seem to be of good data quality and lead to higher estimated rainfall amounts in CHIRPS in mountainous areas." TAMHO reports for Uganda and Kenya are also exciting, given their dense coverage, however it was determined that these receive a longer evaluation period. Specifically, there were numerous reports with very low (< 10mm) rainfall values in Uganda and western Kenya. Much higher rainfall amounts (50-200 mm) were to be expected, according to recent reports from the Kenya Met Department and [https://www.icpac.net/climate-monitoring/ IGAD ICPAC]. | ||
+ | |||
+ | '''Japan and Korean Peninsula''' CHIRPS is showing very high rainfall values in the region affected by [https://en.wikipedia.org/wiki/Typhoon_Haishen_(2020) Typhoon Haishen/Kristine], the first super typhoon of the 2020 Pacific typhoon season. It peaked as a category 4 super typhoon, then at a weaker stage made landfall in southwest Japan and the eastern Korean Peninsula. [https://english.kyodonews.net/news/2020/09/e999e67896ed-powerful-typhoon-leaves-4-missing-injures-more-than-50-in-japan.html This powerful storm left 2 dead], 4 missing, and over 100 injured in Japan. Several stations included in CHIRPS registered highly anomalous amounts for the month, including a station on Fukue Island, the southernmost of the Goto islands in Japan (+441.3 mm above average) and in the South Korea coastal city of Gangneung (+475.0 mm above average, 614 mm total). The impact in the region can be seen on CHIRPS September anomaly map [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2020/CHIRPS_092020_anomaly_typhoon.png here]. | ||
+ | |||
+ | '''Pakistan''' Although missed by CHIRP, station data provided vital information regarding above-average precipitation in September which contributed to an already [https://earthobservatory.nasa.gov/images/147330/extreme-monsoon-rains-in-pakistan heavy, deadly monsoon season] in northern and southeastern Pakistan. | ||
+ | |||
+ | '''United States''' With 10 major storms, September 2020 was the [https://en.wikipedia.org/wiki/2020_Atlantic_hurricane_season most active month on record] for the Atlantic hurricane season. One of the most damaging storms in the Gulf Coast and Mexico, Tropical Storm Beta, caused over $100 million in damage and a fatality in Texas. CHIRPS for September 2020 shows monthly totals that are far above average (greater than 2 standard deviations from average) in the Florida panhandle, southeast Alabama, southwest Georgia, and central-northeast Texas. Meanwhile, CHIRPS shows extreme low September rainfall in the upper Northeastern United States, where drought conditions are ongoing. Similarly, much of the West and Great Plains regions and central-south Canada had a much drier than average September. The West is under Extreme to Exceptional Drought conditions. The latest US Drought Monitor can be viewed [https://droughtmonitor.unl.edu/CurrentMap.aspx here]. | ||
+ | |||
+ | '''Africa dataset differences''' Rchecks observed there are very large differences between CHIRPS and NOAA ARC2, and compared these to other data. CHIRPS, TAMSAT, and PERSIANN show a band of generally above average rainfall in the Sahel region and parts of northern and western East Africa, and below average and mixed condition rainfall equatorward and for a large part of Central Africa. ARC2 is wildly different, with that data showing highly above average rainfall across nearly all of these areas. Comparison of datasets can be viewed at the following links. Map of September 2020 rainfall [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2020/CHIRPS_final_compare_data.PNG TOTAL] and [https://data.chc.ucsb.edu/people/laura/RChecks_figures/2020/CHIRPS_final_compare_anom.PNG ANOMALY]. (Top-left, CHIRPS; Top-right, ARC2; bottom-left, TAMSAT, bottom-right, PERSIANN) | ||
+ | |||
+ | '''Rchecks plots''' New highs for CHIRPS-CHIRP mean in Africa and Sahel but not extreme: eog /home/chc-data-out/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.*.stats.2020.09.png | ||
+ | |||
+ | Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Laura Harrison, Pete Peterson | ||
+ | |||
+ | === July 2020 === | ||
+ | '''Ethiopia''' Very large station values, several over or near 500mm, but they are in good agreement with PERSIANN-CCS. | ||
+ | '''Brazil''' The dry season is very dry in Northern Argentina and southern Brazil, many stations have 0 values. CHIRP was already quite low, but station data lowers values for CHIRPs. | ||
+ | '''Chili''' The CMORPH product is showing a lot of rain, ~300mm, in the Atacama desert whereas CHIRPs shows near 0 values. | ||
+ | '''Rchecks Plots''' All statistics look reasonable. There was tie for the low value for CHIRPS standard deviation in Latin America but nothing extraordinary. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Pete Peterson | ||
+ | |||
+ | === August 2020 === | ||
+ | '''China''' CHIRPS data shows impact of Typhoon Higos, which made landfall in southeast China at the coastal city of Zhuhai. More on Higos [https://abcnews.go.com/International/wireStory/typhoon-higos-hits-china-weakens-tropical-storm-72462400 here]. The signature of the typhoon on rainfall was localized, and it contrasts with the otherwise drier than average August in the greater southeast China region shown in CHIRPS. For instance, in Zhuhai, and the area closely surrounding it, a report shows 190 mm above average while just under 175 kilometers inland, reported anomalies are -51 mm to -121.9 mm. | ||
+ | |||
+ | '''North Korea and South Korea''' CHIRPS is depicting observed extreme rainfall in North Korea and South Korea. The events led to fatalities and flooding and major damage to farmland, homes, and infrastructure. More [http://floodlist.com/asia/north-korea-floods-august-2020 here]. There are ~15 stations reporting heavy, highly above average rainfall in North Korea and northern South Korea. Some of these in northern North Korea report >1000mm! Unable to check the accuracy of those, and of course they influence CHIRPS, but the CHIRPS values seem fine (albeit very large). The outcome on CHIRPS is that stations increased CHIRP anomalies to around 2x CHIRP. | ||
+ | |||
+ | '''India and Pakistan''' Pakistan and western India experienced extremely heavy rains and catastrophic flooding. More [https://www.bbc.com/news/world-asia-india-49306246 here] and [https://www.straitstimes.com/asia/south-asia/angry-residents-begin-clean-up-in-karachi-as-rains-lash-south-asia here]. CHIRPS Rchecks for August displays station anomalies as high as 703.7 mm in west India and 416 mm in southeast Pakistan. | ||
+ | |||
+ | '''United States''' Station values significantly increased CHIRPS estimates along the eastern seaboard while decreasing estimates in midwest and northwestern quarter of the country. | ||
+ | |||
+ | '''Mexico''' Quality check on what CHIRPS shows in southern Mexico (Pacific coast): Noticed that stations are quite high compared to CHIRP, which shows moderate precip. This produced comparatively much higher values in CHIRPS, which better matches CMORPH estimates. | ||
+ | |||
+ | '''South Sudan''' Interesting that ARC2 shows a strong wetter than average August while CHIRPS, CHIRP, and PERSIANN show below average rainfall in much of eastern and central South Sudan. TAMSAT shows a mixed and mainly wet signal there. More analysis could be done to gauge if CHIRPS is wrong or right, but either way there are no stations to discuss removing there. | ||
+ | |||
+ | '''Rchecks plots''' All statistics are within normal ranges. The Africa Long Horn set a new high for mean z-score but marginally at less than 0.5. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Laura Harrison, Pete Peterson | ||
+ | |||
+ | === July 2020 === | ||
+ | '''Ethiopia''' Very large station values, several over or near 500mm, but they are in good agreement with PERSIANN-CCS. | ||
+ | '''Brazil''' The dry season is very dry in Northern Argentina and southern Brazil, many stations have 0 values. CHIRP was already quite low, but station data lowers values for CHIRPs. | ||
+ | '''Chili''' The CMORPH product is showing a lot of rain, ~300mm, in the Atacama desert whereas CHIRPs shows near 0 values. | ||
+ | '''Rchecks Plots''' All statistics look reasonable. There was tie for the low value for CHIRPS standard deviation in Latin America but nothing extraordinary. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Pete Peterson | ||
+ | |||
+ | === June 2020 === | ||
+ | '''Madagascar''' Here is an identified issue with the existing climatology that CHIRP(S) is built around, known as CHPclim, which is causing artifacts in CHIRP, Prelim, and CHIRPS. The new CHPclim is approaching final stages of production, and appears to perform considerably better in this area. Correspondingly, these artifacts will likely be corrected for in CHIRPS 3.0 (release date pending). | ||
+ | |||
+ | '''Japan''' Heavy flooding in southern Japan in the news. CHIRP estimated fairly high rainfall but with the addition of stations, the CHIRPs prediction got boosted. | ||
+ | |||
+ | '''India''' Station data shows more rainfall than CHIRP. CHIRPS is more accurate but some lower elevation stations having lower rainfall are mitigating the predictions of higher rainfall at higher elevations. | ||
+ | |||
+ | '''North America''' Station values reversed a CHIRP estimated dry anomaly in the Pacific NW to become a wet anomaly from the Cascades westward. | ||
+ | |||
+ | '''Rchecks plots''' All statistics look reasonable. There was tie for the CHIRPS Max value and Anomaly Max for Southern Africa which were examined and determined to be from an artifact in CHPClim. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Pete Peterson | ||
+ | |||
+ | === May 2020 === | ||
+ | |||
+ | '''Kenya''' Stations report continued above average rainfall and flooding in the north and central regions of Kenya in early to mid-May. A total of 161,000 households (over 800,000 people) have now been affected across the country. http://floodlist.com/africa/kenya-floods-north-central-regions-may-2020 | ||
+ | |||
+ | '''Caribbean''' For some reason, in this month, the station part of the CHIRPS algorithm seems to be breaking down for islands. In Cuba, Hispaniola, Hainan Island (also inland central vietnam) there are big differences between CHIRP and rchecks due to stations that are quite a ways away from the area that changes. There are no stations where the changes occur. | ||
+ | |||
+ | '''Vietnam''' An area of moderately high precip in CHIRP (and RFE2) gets boosted to over 600-700mm, for no apparent reason. | ||
+ | |||
+ | '''China''' Moderate precip in interior of Hainan island in CHIRPS drops 100mm in rchecks because of stations in lowlands on the island. | ||
+ | |||
+ | '''Rchecks plots''' A new low CHIRPS - CHIRP for Africa but only slightly. Very low values in most variables reflects the extreme dryness in Haiti | ||
+ | |||
+ | Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson | ||
+ | |||
+ | === April 2020 === | ||
+ | |||
+ | '''South America''' In western Amazonia, confluence of Brazil, Oeru, Columbia, is a very large change in Rchecks (lower precip) over a large area that is based on stations quite a distance away, seems less ideal. In SW Amazonia the opposite happens, there is a very large increase in precipitation that is based on sparse stations. | ||
+ | |||
+ | '''Iran''' Heavy rainfall in mid-April created flash floods and swollen rivers in several Iranian provinces, including Kerman and Sistan and Balouchestan in the southern parts of the country. | ||
+ | |||
+ | |||
+ | '''Rchecks plots''' A new high for CHIRPS Max in the Long Horn of Africa. Nearly double the previous high for the region. This translated into new high CHIRPS max in Africa and globally, but not drastically. | ||
+ | |||
+ | Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson | ||
+ | |||
+ | === March 2020 === | ||
+ | |||
+ | '''Eastern Africa''' Above average rainfall and flash floods in early-to-mid-March resulted in tens of deaths and left thuousands displaced across the D.R. Congo, Rwanda, Burundi, Tanzania, and Kenya http://floodlist.com/africa/drcongo-floods-maniema-march-2020 http://floodlist.com/africa/burundi-heavy-rain-floods-march-2020 http://floodlist.com/africa/rwanda-floods-march-2020 http://floodlist.com/africa/kenya-floods-busia-siaya-march-2020 | ||
+ | |||
+ | '''Madagascar''' Despite a lack of stations, CHIRPS accurately captures significant rainfall over northeastern Madagascar, which reported flooding in mid-March from Tropical Cyclone Herold. http://floodlist.com/africa/madagascar-tropical-cyclone-herold-march-2020 | ||
+ | |||
+ | '''Rchecks plots''' New low in CHIRPS mean for Latin and Central America by a large amount, > 5 mm. Also, New low in CHIRPS Z-scrore mean for Latin and Central America by a small amount. Z-scores confirm this with much of the regioin well below normal. This extends well into South America and the southern US. Also, PERSIANN and CMORPH confirm the abnormal dryness. See: http://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.lat_amer.stats.2020.03.png | ||
+ | |||
+ | Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson | ||
+ | |||
+ | === February 2020 === | ||
+ | |||
+ | '''Ethiopia''' Ethiopia CHIRPS data has improved station density, thanks to support from the Ethiopia NMA. There were approximately 100 stations in February 2020 CHIRPS data. This is around two times more stations than in recent data. These stations corroborated and enhanced a weak dry signal also shown by CHIRP in February 2020 rainfall in central Ethiopia. | ||
+ | |||
+ | '''Australia''' CHIRPS data shows the much needed rain that eastern Australia finally got in February. The bush fires ended last month after 200+ days of burning, see article [https://www.cnn.com/2020/03/03/australia/new-south-wales-fires-extinguished-scli-intl/index.html here]. | ||
+ | |||
+ | '''Southeast Asia''' CHIRPS shows a stronger (but still low magnitude) below average signal compared to CHIRP in Thailand and Laos. This is due to reports from numerous stations in both countries | ||
+ | |||
+ | '''India''' CHIRPS shows above average rainfall in central east, whereas CHIRPS shows a much weaker signal. This is due to reports from ~6 stations in that area. | ||
+ | |||
+ | '''Ecuador''' Higher than normal station values in the rainshadow of mountain ranges caused the values at the mountain ridges to double from 300 to 600 mm. Not ideal. However in Columbia there were a couple of stations near the ridge that were in the 400-500 range so perhaps it's ok. | ||
+ | |||
+ | '''North America''' Southern CA had virtually no rain in February 2020 yet CHIRPS is showing estimates in the mountains of over an inch. Big Bear CA station [http://cetulare.ucanr.edu/About_County/Weather/?weather=station&station=199 measured zero rainfall], CHIRPS estimated 37.7mm. | ||
+ | |||
+ | '''CHIRPS processing''' In recent weeks the team investigated impacts of the two-step station blending process, which is currently a processing step designed to incorporate more recently acquired stations. This showed examples where having the 2nd step resulted in reports farther away than closer stations being blended in the second step and having a substantial influence on CHIRPS estimates. Based on the results of the investigation, Rchecks team is strongly recommending that future CHIRPS processing uses a single pass blending step. | ||
+ | |||
+ | '''CHIRPS processing''' Southern Africa CHIRPS data received additional attention in this rcheck. The final version of CHIRPS appears much improved from the first version seen during rchecks. In the first version, the data appeared excessively low in Zambia and Zimbabwe area despite some areas having actually received ample February rainfall. Three SASCAL stations with unrealistic low values were identified- these were the same problem stations identified during rchecks of other recent data. This time these stations were removed from February 2020 data and also permanently removed from future data. The second version of data (after these were removed) showed much more realistic CHIRPS estimates in that area. An odd circular excess wet feature remained, affecting Mozambique and southern Zimbabwe, and it was shown to be due to lack of local stations and influence of stations in South Africa. This was improved by omitting those stations. The result was still realistic estimates in South Africa (where there was high station density even without these) and realistic estimates in the Mozambique and southern Zimbabwe areas. Comparisons to CHIRP and ARC2 data, and previous knowledge from regional rainfall monitoring, were helpful in identifying the problems in pre-final CHIRPS and in confirming that the final, public-released February 2020 CHIRPS looks fine. | ||
+ | |||
+ | '''Rchecks plots''' All plots look good and new values fall within historical ranges. There was a new low for CHIRPS Maximum over Africa but just barely. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson | ||
+ | |||
+ | === January 2020 === | ||
+ | |||
+ | '''South America''' In general, pretty good agreement between CHIRP and CMORPH datasets. | ||
+ | |||
+ | '''Costa Rica''' Pretty sure this happened last month, too, low values on the leeward side of the country cause areas in Rchecks to have much lower values than CHIRP on the windward side (NE part of CR). | ||
+ | |||
+ | '''Nicaragua''' Odd very low rain features in rainfall SE of country near coast. Appears to be in climatology because repeats in other months. | ||
+ | |||
+ | '''North America''' Stations greatly increased the CHIRPS estimate in the Pacific NW by a factor of 8 from CHIRP. CHIRPS looks good around Santa Barbara. | ||
+ | |||
+ | '''Armenia and Azerbaijan''' We have become aware of a station reporting / CHIRPS measurement issue in Armenia and Azerbaijan. We believe that some stations are reporting solely rainfall measurements, while others are reporting snowfall. As rainfall is roughly one tenth of the snowfall amount, this leads to relatively low CHIRPS precipitation values. CHIRPS values in this area should be interpreted carefully, as the rainfall representation is likely inflated, and the snowfall representation is significantly deflated. In the attempt to make the most accurate precipitation dataset possible, this issue is on our radar and will be addressed soon. Thank you for understanding. | ||
+ | |||
+ | '''Australia and Indonesia''' Stations generally show same pattern in anomaly as CHIRPS, which is good to see for that satellite-based product. In Indonesia stations bumped up localized rainfall amounts in several areas. | ||
+ | |||
+ | '''Afghanistan, India, Pakistan''' Stations made big difference increasing CHIRP values. The wetter than average signal is coming from 20+ stations in the region, so it seems believable. | ||
+ | |||
+ | '''Thailand''' Very nice station density in this country. 25+ stations all showing mild drier than average signal. CHIRP was near average. CHIRPS seems to meet halfway, showing very mild deficits. | ||
+ | |||
+ | '''Rchecks plots''' Plot comparisons look normal. There is a new CHIRPS Max high for the Africa Long Horn but (~550mm) but just barely higher than the previous high | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Austin Sonnier, Will Turner, Sari Blakeley, Pete Peterson | ||
+ | |||
+ | === December 2019 === | ||
+ | |||
+ | '''Australia and Indonesia''' CHIRPS shows below average December rainfall in most of Australia and Indonesia. Largest deficits are in the 100-200mm range. According to Australia's Bureau of Meteorology, December 2019 had the lowest rainfall on record for the country as a whole and "rainfall was in the lowest 10% of historical observations for much of the eastern mainland and north of the Northern Territory. [http://www.bom.gov.au/climate/current/month/aus/summary.shtml (link)]" We did not examine CHIRPS historical ranks but these are areas with large anomalies and negative z-scores. A big reason for agreement with BoM would be that CHIRPS blends in hundreds of stations across the country. | ||
+ | |||
+ | '''Brunei, Malaysia (island areas), and Indonesia (near Malaysia border)''' Consistent with reports of flooding from high intensity rain during December, CHIRPS shows above average December totals (100mm-200mm anomalies). The rain event led to flooding and evacuation of several hundred people. [http://floodlist.com/asia/malaysia-sabah-floods-december-2019 (link to report)]. In this area several stations reported very high values (~600mm), which increased CHIRPS compared to CHIRP. The flood report and consistency between stations supports the wet CHIRPS signal there. | ||
+ | |||
+ | '''Zimbabwe''' Large deficits in CHIRPS across the country. In northern and western Zimbabwe, we note that the CHIRPS anomaly map indicates a larger dry signal in those areas than does CHIRP. This corresponds to CHIRPS values being lower than CHIRP values (by around 20 mm). We remind users that there are no stations in Zimbabwe being blended into CHIRPS, and as usual this results in uncertainty in the data there. Values are based on stations outside the country being blended into CHIRP. In this case for December 2019 data, Zimbabwe is surrounded by ~20 stations that show below average rainfall. These are in Namibia's Caprivi Strip, Botswana, Zambia, Mozambique, and NE South Africa. Between this and the below average CHIRP signal, the dryness in Zimbabwe indicated by CHIRPS appears reasonable. | ||
+ | |||
+ | '''Portugal, Spain, and France''' Once again (~3 months in a row), we see that CHIRP and Prelim underestimated rainfall in parts of Portugal, Spain and France (CHIRPS Final is considerably wetter than both CHIRP and Prelim). We have now seen several months of anomaly disagreement between CHIRP and Final in parts of these 3 countries. For monitoring, users should be aware of this discrepancy between CHIRP/Prelim and CHIRPS Final. | ||
+ | |||
+ | '''Costa Rica and Panama''' CHIRPS shows mixed anomalies while CHIRP shows largely above average, prompting some investigation as to the cause and which is correct. Compared both products to CMORPH. CMORPH values on land also show mixed anomalies, and while spatial patterns are not the same as CHIRPS, this aspect makes CMORPH in general was more similar to CHIRPS than CHIRP. CMORPH did show above average rainfall offshore. No problems stations in CHIRPS were identified. In terms of station agreement with CHIRPS values, there are discrepancies along the Caribbean coast. Here, some stations report higher rainfall than CHIRPS. One possibility is that the CHIRPS interpolation is being influenced by stations on the Pacific side, or at least on the other side of the mountains, that have below average rainfall. | ||
+ | |||
+ | '''Honduras and Nicaragua''' (1) In eastern Honduras and northeastern Nicaragua CHIRPS shows below average rainfall in December, ranging from deficits of 50mm to 140mm. This is in line with a dry signal also shown by CHIRP, but is more intense. Stations are also playing a role here, but these are not well distributed. One near the coast that shower a report that is much lower than CHIRP, by ~50%, and it may have a role in producing the largest difference between the products. This station reports frequently and was not deemed problematic in this check. (2) In northern Honduras, a similar comment to the one for Costa Rica and Panama. On the north coast of Honduras and the islands CHIRP shows high rain ~300mm. 2 of the stations in this area also show reasonably high rain, so this doesn't seem unreasonable. Also CMORPH shows a blob just offshore of this region. When the other more inland stations are averaged in the values on the north coast of Honduras drop down to ~200mm, probably a bit low. | ||
+ | |||
+ | ''' North America''' Station values increased the rainfall estimates in the Pacific NW reducing the dry anomalies experienced there this winter. The news also reports dryness in this region, see [https://www.capitalpress.com/state/oregon/moderate-drought-weathers-december-in-oregon-washington/article_2cf67e54-28dc-11ea-9dfd-17355d233d32.html report here.] | ||
+ | |||
+ | ''' CHIRPS processing''' (1) False zero screening was examined in east Brazil, as CHIRPS diagnostics plots show what looks like a large cluster of stations being excluded for this reason. We compared CHIRPS and this screening map to Brazil INMET's map of December 2019 rainfall. The INMET map showed rain where many of these potential false zero reports had been removed. CHIRPS estimates look similar to INMET estimates in the examined area. False zero screening therefore appeared to be working fine here. (2) Possible problem resulting from 2nd blending step. A 2nd blending is done to incorporate stations added to the database after 2015. In Rchecks it was observed that a station involved in 2nd blending was possibly having more influence on CHIRPS values than closer stations. See 'Zambia (NE) entry' on the watchlist for more information. The impacts of the 2nd blending step should be further examined. | ||
+ | |||
+ | '''Rchecks plots''' There was a new high value for CHIRPS in South America of around 1600 mm. Other than that all other stats look fine. http://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.*.stats.2019.12.png | ||
+ | |||
+ | === November 2019 === | ||
+ | |||
+ | '''East Africa''' Highly above average rainfall occurred in East Africa during November 2019, according to CHIRPS Final. Some of the more historically extreme amounts are in Kenya, southern Somalia, southern Ethiopia, Uganda, and northern and coastal Tanzania. Estimates show some areas with 100-300 mm above the long term average for November. In many of these areas CHIRPS Final estimates are higher than CHIRPS Prelim, due to blending of station reports into Final. Despite the increased wetting in Final in some areas, the regional wetter than average signal is consistent with what Prelim had indicated earlier. Extreme wet conditions during October to December 2019 are related to a strong positive Indian Ocean Dipole (IOD) mode and warm ocean temperatures. More explanation about the IOD can be be found in [https://weather.com/storms/hurricane/news/2019-12-08-tropical-cyclone-belna-madagascar-indian-ocean this article] by The Weather Channel. | ||
+ | |||
+ | '''Panama and Honduras''' Stations being blended created more realistic rainfall estimates, compared to the satellite-based CHIRPS estimates. Assessment based on comparison to CMORPH data and review of CHIRPS (too high) versus several blended station reports. | ||
+ | |||
+ | '''Portugal, Spain, and France''' Significant discrepancy observed between CHIRP and CHIRP+Stations (CHIRPS), as stations across northern Portugal and Spain and western France report heavy precipitation for the month of November. According to news reports, much of this precipitation came in the form of snow and thunderstorms. | ||
+ | |||
+ | ''' North America''' Station measurements reduced the CHIRP estimates along much of the west coast and Sierra Nevada mountains. | ||
+ | |||
+ | ''' CHIRPS processing''' The GHCN-v2 monthly product was recently replaced by a new version, v4. GHCN-v4 monthly contains thousands more station reports than v2, so it is an exciting in situ source to blend into CHIRPS. Efforts were made to do so for the November 2019 CHIRPS final data, but during Rchecks, a problem with the v4 values was identified. In some regions like East Africa GHCN-v4 monthly values were unrealistically high. The problem may have been caused by a processing error, or something else, and the decided solution was to wait on using this new source until more time could be spent quality checking the data. This new source can be included in the new version of CHIRPS due in 2020. | ||
+ | |||
+ | '''Rchecks plots''' Regional statistics did not have any outlier values. | ||
+ | |||
+ | === October 2019 === | ||
+ | |||
+ | '''East Africa''' East Africa was very wet in October 2019. According to FEWS NET, flooding has displaced more than 700,000 people in Somalia, Ethiopia, and Kenya since early October See [http://fews.net/east-africa/seasonal-monitor/november-8-2019 here] for the report. CHIRPS October data shows very high amounts in southern Ethiopia, southern Somalia (Bakool, Gedo, and and Bay regions), in Kenya (eastern, central, and western areas), Uganda, and parts of Tanzania (L. Victoria and northeast). Many of these areas show > 200 mm amounts, and localized areas show amounts > 300 mm. In and near Somalia, some of highest amounts are in upstream drainage areas of Juba and Shabelle Rivers, along which major damages related to flooding in populated and agricultural zones have been reported. In this area in particular there are ten station reports from SWALIM that are blended into CHIRPS, and comparison of these reports and CHIRPS estimates shows general agreement between the two. Most CHIRPS estimates are within ~25mm of the reported values near the same location, though CHIRPS estimates are higher than reports in northwest Bay by ~100mm. Both reports and CHIRPS show agreement as to October amounts being higher than average- 1 to 2 standard deviations above average in this part of Somalia. Across much of East Africa, October 2019 CHIRPS values are substantially wetter than average, and many of these are historically prominent at 2 to 3+ standard deviations above average. | ||
+ | |||
+ | '''Southern Africa''' CHIRPS shows a moderately drier than average October across a large area of Southern Africa, with larger, more substantial deficits in South Africa and Lesotho. October deficits are between 10 to 20 mm below average in Zimbabwe, Botswana, and parts of southern Mozambique, Zambia, and northeastern Namibia. In eastern South Africa and Lesotho October totals were ~50 mm below average. Of all the countries South Africa has highest station density (from GSOD, GTS, and GHCN monthly), and CHIRPS estimates are close to their reported values. Elsewhere, blended reports from SASSCAL and other sources also show agreement with CHIRPS estimates. It is early in Southern Africa's main period of annual rainfall (October to April) and cropping season, and the deficits outside South Africa and Lesotho were relatively small, but these were a notable departure from past Octobers, with amounts being 1 to 1.5 standard deviation below average and in parts of South Africa, up to 2.5 standard deviations below average. | ||
+ | |||
+ | '''France''' Stations blended in CHIRPS captured heavy rainfall in southern France and northern Spain. The town of Béziers, France saw 198mm (nearly 8in) of rain - or about two months' average rainfall - in just six hours on the morning of 10/23. See the BBC article [https://www.bbc.com/news/world-europe-50169525 here.] Across Spain, Germany, and Switzerland, stations reported an anomalously wet month of October, which was otherwise missed by CHIRP. | ||
+ | |||
+ | '''Japan''' CHIRPS October data shows the rainfall impacts of Typhoon Hagibis in Japan. Typhoon Hagibis which made landfall near the Izu Peninsula on October 12, 2019. Once making landfall, Hagibis moved NNE transecting the coast just east of Fukushima. It deposited a significant amount of precipitation along the eastern flank of central Honshu, the largest and most populated island in the Japanese archipelago. According to Accuweather’s documentation of precipitation in Fukushima, on October 13th alone, 19.18 in or approximately 487 mm of rain fell. During Rchecks it was observed that two stations reported markedly lower values than neighbor stations. These reports of approximately 145 mm were at the cities of Fukushima and Yamagata. Compared to their surroundings, which ranged from 295-435 mm, and the well documented torrential downpours resulting from Typhoon Hagibis, these station reports may be underestimates. Overall however, CHIRPS data registered the high amounts coming from a high density network of 60+ stations. CHIRP, the satellite-based part of CHIRPS, also showed above average rainfall but the stations substantially increased estimates and were responsible for more accurate spatial details in CHIRPS compared to CHIRP. | ||
+ | |||
+ | '''United States''' CHIRPS data shows plenty of low z-score values in the west, verifying a very dry month as noted by the [https://weatherwest.com/ California Weather Blog]. | ||
+ | |||
+ | '''Central America/Caribbean''' Cool windward/leeward rainfall effects noted in station data reports in the eastern Caribbean | ||
+ | |||
+ | '''Southeast Asia''' October amounts were below average from Myanmar to Taiwan, according to CHIRPS. This signal comes from agreement between CHIRP and stations in Thaliand, southern Vietnam, and Taiwan. Stations tended to increase the size of deficits, compared to CHIRP. Stations and CHIRP in northern Vietnam agreed as to above average amounts there. | ||
+ | |||
+ | '''India''' CHIRPS shows most of southern India as wetter than average in October, which exception of in northern Tamil Nadu and some nearby areas. The signal is coming from both CHIRP and stations, though the stations increased CHIRPS amounts compared to CHIRP in most of the wet areas. Their blending also increased estimates in southern CHIRP-deficit areas. | ||
+ | |||
+ | '''Australia''' We note a circular feature in CHIRPS in eastern Australia- this is centered on a station report that is substantially wetter than surrounding reports. CHIRP shows marginally above average amounts in area, so the station itself is possibly fine. There is no similar feature visible in the October CHPclim, so it is not coming simply from the CHIRPS climatology, but it is being produced by some aspect of the CHIRPS algorithm. This type of thing can be seen in other months of CHIRPS data in Australia. Ideally this will be corrected in next version of CHIRPS. | ||
+ | |||
+ | '''Chile/CHIRPS algorithm''' There appear to be high rainfall totals in the southern Chilean Andes, according to CHIRP, but there are no station reports are in that area. Blending of stations in the central valley, which showed low to moderate amounts, seem to have reduced the high elevation values. Seems like this could be an issue in other parts of the world, though perhaps they are better instrumented. Future formal CHIRPS assessments that may help improve blending strategies would include an examination of CHIRPS accuracy in high elevation/high topography regions. Perhaps elevation trends in the Cascades or Sierra Nevada could be useful to inform the veracity of high elevation estimates in South America. CHIRPS blends a high density station network in Guatemala and may be incorporating numerous new stations in Chile, so topography-related assessments would be useful. | ||
+ | |||
+ | '''Rchecks Plots''' New highs for region-average CHIRPS Mean and Z-score mean for the Sahel domain, and for the entire Africa domain, but these are not very far from previous highs. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Seth Peterson, Austin Sonnier, Marty Landsfeld, Pete Peterson | ||
+ | |||
+ | === September 2019 === | ||
+ | |||
+ | '''Laos''' A station in southern Laos captured the heavy rainfall from Tropical Storm Podul and Tropical Depression Kajiki, which hit one after another in the first two weeks of September 2019. More than 580,000 people were impacted and at least 28 died in the resulting floods. See the ReliefWeb article [https://reliefweb.int/report/lao-peoples-democratic-republic/situation-update-no-6-tropical-storm-podul-and-tropical here.] CHIRPS data shows high values in this region due to influence from this station and from other stations reporting high amounts located nearby in Thailand. These stations being blended in produced a substantial improvement compared to the satellite-based CHIRP, which did not estimate high amounts or above average September rainfall in the affected area. | ||
+ | |||
+ | '''India''' CHIRPS shows high rainfall amounts. These are based on the high amounts reported by stations. Heavy, extreme rainfall has led to flooding and over 100 deaths in India. The 2019 monsoon season has seen the heaviest rainfall in 25 years. See the Washington Post article [https://www.washingtonpost.com/world/2019/10/01/more-than-have-people-have-died-heavy-rains-india-heres-what-flooding-looks-like/ here.] | ||
+ | |||
+ | '''United States''' Impact of the Hurricane Imelda that struck Houston, Texas on September 17th and caused record-setting flooding is shown in CHIRPS, though we find that the satellite infrared-based estimate (CHIRP) greatly underestimated rainfall totals. Two stations around the Houston area reported around 15” and 18” rainfall and the CHIRPS blending algorithm did a fine job recreating estimates seen in an Accuweather article (link to article [https://www.accuweather.com/en/weather-news/imelda-triggers-widespread-flooding-across-southeastern-texas/535882 here]). However, high values above 10” were underestimated in CHIRPS. | ||
+ | |||
+ | '''Republic of Congo''' CHIRPS data shows below average September rainfall. This signal is attributed to several GHCN-v2 monthly stations. We examined these and found they report intermittently, which makes their reports suspect, but given they agreed in direction (below average) they were retained. | ||
+ | |||
+ | '''Rchecks Plots''' Besides a new high in Africa region anomaly (slightly higher than previous maximum), all other stats are in the normal range. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Seth Peterson, Sari Blakeley, Austin Sonnier, Marty Landsfeld, Pete Peterson | ||
+ | |||
+ | === August 2019 === | ||
+ | |||
+ | '''CHIRP vs. Prelim vs. CHIRPS Final in Africa''' Notable difference between Prelim and Final in northern Ethiopia. Final still shows below average rainfall but CHIRPS Prelim and CHIRP were substantially drier. This was indicated by the CHC Ethiopia Special Reports on dekadal rainfall (Diego Pedreros and Diriba Korecha) that do an early blending of Ethiopia NMA stations with Prelim. These can be accessed from https://chc.ucsb.edu/monitoring. Good to know that that monitoring information is reliable. It is worth noting that Final is also wetter than Prelim in southwestern Ethiopia with big influence from a couple of wet (above average) stations. Same thing in Sudan. These signals have cross-product agreement- ARC2 also shows above average rains in similar locations. Across much of the Sahel, we notice that CHIRP did not capture some of the localized heavy rains that stations in Final and Prelim show (Prelim has GTS stations). One of the areas that CHIRP did perform well is in northwestern Cote d’Ivoire. CHIRP estimates agree with stations there. | ||
+ | |||
+ | '''Niger''' CHIRPS shows higher than average August rain in eastern areas of Niger including east of Maradi and in Zinder and to just past the Chad border. Heavy August rains likely contributed to soil saturation and high river levels that, after further heavy rains in September, contributed to recent flooding events and fatalities. According to a Floodlist report from September, “Meanwhile the number of flood related fatalities in Niger has increased from the 42 reported a few days ago. In a statement of 10 September, government authorities said that that the ongoing floods have now resulted in 57 deaths and affected 132,528 people. Over 12,000 homes have been destroyed and widespread damage caused to crops and livestock. Flooding has affected some areas of Niger since June to July, but has worsened over the last week, with many of those affected in Maradi, Zinder and Agadez, as well as Dosso and the capital Niamey.” Link to article [http://floodlist.com/africa/westafrica-floods-nigeria-niger-chad-september-2019 here]. | ||
+ | |||
+ | '''Nigeria''' CHIRP captured heavy rainfall for the month of August, which was confirmed (and increased in severity) by the stations in CHIRPS. Northeast Nigeria suffered from flash floods throughout August. According to ReliefWeb, "Above-normal volumes of rain and the associated flooding are increasing vulnerabilities and risks in camps for internally displaced persons. An estimated 21,056 households have been affected by torrential rains and flash floods across Borno, Adamawa, and Yobe (BAY) states." Link to article [https://reliefweb.int/report/nigeria/nigeria-north-east-floods-situation-report-no-2-30-august-2019 here]. | ||
+ | |||
+ | '''India''' CHIRPS stations captured the extreme rainfall events that occurred in southwest India (these were not identified by CHIRP). According to AccuWeather, “Nearly 227,000 people are seeking shelter from the flooding in Karnataka, where 61 people have been killed. Chief Minister B.S. Yeddyurappa told Reuters that the flooding was the worst the state had endured in 45 years.” Link to that report [https://www.accuweather.com/en/weather-news/photos-flooding-claims-more-than-140-lives-in-western-southern-india/70009049 here]. Also in line with CHIRPS estimates of highly above average rainfall along the southwestern coast and in central-northwestern India (Madhya Pradesh and Rajasthan) is a report noting that August 2019 rainfall was especially extreme in India (see report [https://timesofindia.indiatimes.com/india/in-just-18-days-extreme-rain-this-august-at-5-year-high/articleshow/70761871.cms here]. | ||
+ | |||
+ | '''CHIRP vs. Prelim vs. Final in Central America''' Stations in Final enhanced the dry signal seen in CHIRPS in northern Guatemala and some other Central America locations. However, CHIRPS Final looks very similar to CHIRPS Prelim. This is a good thing to see, as monitoring often makes use of Prelim until Final is available (typically the 3rd week of each month). In northern Guatemala the CHIRPS Final values agree well with the numerous station reports that are blended in. Same agreement in southern Mexico. In western Guatemala, as usual there are a ton of stations, and localized variations such as above average rain reports in mountains and mixed anomalies at lower elevations, have trouble coming through. Hard to tell if there is overall under or over estimation there (by Final, compared to stations). It has been proposed to quantify this, as it could help to know if CHIRPS has any clear systematic bias in this and other high station density areas. | ||
+ | |||
+ | '''Cuba''' CHIRPS values are clearly influenced in Cuba by a single station with a high rainfall amount. An internet search did not produce explanation for the high amount, but CMORPH data is also higher in this part of Cuba so this station was deemed ok to retain in the CHIRPS data. | ||
+ | |||
+ | '''Brazil''' It was noted during Rchecks that, similar to what has previously been seen, the values on the coast south of Salvador are substantially increased from CHIRP to CHIRPS-- they go from 100-200 mm in CHIRP to 300-400 mm in Rchecks despite none of the nearby stations being particularly anomalous. | ||
+ | |||
+ | '''Rchecks Plots''' New lows for CHIRPS mean, max, standard dev and z-scores for Haiti. New high for CHIRPS max overall (“Global”) of near 2600 mm but this is not substantially different from previous maximums. A figure showing stats for August 2019 for entire near-global CHIRPS extent can been be seen [/home/ftp_out/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.global.stats.2019.08.png here]. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Seth Peterson, Sari Blakeley, Austin Sonnier, Marty Landsfeld, Pete Peterson | ||
+ | |||
+ | === July 2019 === | ||
+ | |||
+ | '''Central America''' July CHIRPS shows below average rainfall across most of Central America. Much of Guatemala, Belize, and El Salvador had deficits of 100-200 mm and totals only reaching between 50-200 mm. 100-200 mm deficits were also in Caribbean side areas of Costa Rica, Honduras and Nicaragua. These areas tend to be wetter and accordingly still received totals of 300-400 mm (and in SW Nicaragua, 450-650 mm). Large deficits were also seen in Panama, and were most pronounced (compared to climatology) in the Azuero peninsula. | ||
+ | |||
+ | '''Bangladesh''' Stations reported highly above average rainfall throughout the country. CHIRP also shows above average rainfall but the signal is more amplified in CHIRPS due to the stations. Heavy rainfall was confirmed by a news report that stated the following: "At least 60 000 homes were washed away or damaged in 13 districts across Bangladesh after a heavy monsoon rains hit Bangladesh and neighboring countries over the past week. At least 26 people have been killed and 3 million marooned. Over the past couple of days, rivers overflowed in 122 upazilas, flooding thousands of villages. According to a special flood bulletin issued by the Bangladesh Water Development Board (BWDB) on Thursday, July 18, 2019, rivers Jamuna and Teesta are at levels not seen in 40 years of water level records." -The Watchers (link to article [https://watchers.news/2019/07/18/bangladesh-flood-july-2019/ here]) | ||
+ | |||
+ | '''Southeast Asia and Thailand''' Approximately 30 stations and CHIRP show below average rainfall in Thailand. Stations amplified the CHIRP dry signal. Most of the country is showing deficits-- largest standardized anomalies are -2.5 in some western and other areas. According to a news report by Hawaii Public Radio, Thailand's government says the country is heading for its worst drought in a decade or longer and it is affecting key crop growing regions and water supplies. More on this story and drought in southeast Asia can be accessed [https://www.hawaiipublicradio.org/post/asia-minute-drought-hits-southeast-asia#stream/0 here]. | ||
+ | |||
+ | '''South Korea/Japan''' CHIRP and stations captured heavy rainfall from tropical rainstorm Danas, which drenched the Philippines, Taiwan, South Korea and Japan in mid-July, according to an Accuweather report. Report [https://www.accuweather.com/en/weather-news/tropical-storm-danas-to-unleash-heavy-rain-on-taiwan-ryukyu-islands-before-targeting-south-korea-japan/70008817 here] | ||
+ | |||
+ | '''Kenya''' A GTS station in NW Kenya was omitted from CHIRPS July 2019 Final. This station reported 95 mm which was suspicious given that this area in dry NW Kenya typically receives around 15 mm in July. The report was cross checked against maps in ICPAC dekadal reports for July 2019. These ICPAC reports blend GHA station reports with CHIRP and can be accessed [http://www.icpac.net/index.php here]. According to ICPAC maps, this area did not receive highly anomalous rainfall and the monthly total in that area were around 35mm at maximum. | ||
+ | |||
+ | '''Mexico''' Inland of Los Mochis (mainland Mexico, across from La Paz) there is a notable blob (-100 to 150mm) in the anomaly map in the mountains that seems to stem largely from lower elevation stations being below average. Higher elevation stations are only slightly below average. | ||
+ | |||
+ | '''Italy''' In Bologna, Italy a station is reading much higher than the neighboring stations and climatology (approximately 9 inches compared to 2 inches). It has a z score of approximately + 4. The station's report was cross referenced with data from Accuweather.com, which reported a monthly total of 1.88 inches with a previously forecast total of 1.5 inches. It seemed that if a highly populated area actually received such anomalous rainfall there would be a report about it, and none was found online. Thus it was recommended that this station report not be included in July CHIRPS. | ||
+ | |||
+ | '''India''' There are large differences between CHIRP and CHIRPS in northern areas of India. CHIRPS shows below average but stations show a mixed pattern, with some far northern and northeastern stations reporting highly above average rainfall. Station reports are tending to break up CHIRP negative anomaly areas so that areas with pronounced negative anomalies in CHIRPS are left in eastern India near Bay of Bengal (Orissa) and in a smaller area in northwestern India (Gujarat) | ||
+ | |||
+ | '''Sudan''' Unfortunately there were no station reports in CHIRPS data for July in Sudan. This is not atypical, but last month (in June 2019 data) there were ~14 GHCN v2 station reports included. | ||
+ | |||
+ | '''CHIRPS note 1''' In far southern Argentina along the coast, the CHIRPS climatology (CHPclim) has some artifacts that show up in CHIRPS. Here is very high precip in all months (~300-400 mm when surrounding area is ~25mm). | ||
+ | |||
+ | '''CHIRPS note 2''' In Brazil, in this month's CHIRPS, a lower than normal occurrence of duplicated stations was noticed. Also in Brazil, where July climatology is low, there were many more stations than usual (and most with near-zero values), which was interesting. At first a relationship to the false zero screening in CHIRPS processing was hypothesized. We examined Pete Peterson's maps that show false zero screening and also compared July 2019 station and CHIRPS values to the Brazil INMET July 2019 precipitation map (INMET link [http://www.inmet.gov.br/portal/index.php?r=tempo2/mapasPrecipitacao here]). It appeared that the false zero screening was working fine this month. The phenomenon of there being groups of many stations screened in some months and not others, which was clearly shown in the false zero screening maps, was not explained by this examination and would be worth looking into. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Austin Sonnier, Will Turner, Sari Blakeley, Pete Peterson | ||
+ | |||
+ | === June 2019 === | ||
+ | |||
+ | '''Global rainfall and temperature''' It is interesting to compare global June 2019 CHIRPS anomalies to the global June 2019 air temperatures from Climate Science, Awareness and Solutions' monthly Global Temperature Update. A number of global areas saw both higher than normal temperature and lower than normal rainfall in June 2019. These are southern Brazil (~ 100 mm deficits and temperatures 3+ deg Celsius higher than normal), Central America and some of Caribbean (50-150 mm deficits and temperature 1-2 deg C higher than normal), much of western Europe, West Africa, India and southeast Asia, and in western Australia and northwestern United States. The June 2019 global average was a record high, at +0.93 degC above the 1951-1980 average, and 0.1 degC above the previous record (in 2016). See the June 2019 Global Temperature [http://www.columbia.edu/~mhs119/Temperature/Emails/June2019.pdf Update] and the [http://chg-ewxtest.chg.ucsb.edu/ CHC EWX] to compare. | ||
+ | |||
+ | '''Sudan''' High amounts of rainfall and flooding in western Sudan is shown in CHIRPS and is detailed in United Nations Office for the Coordination of Humanitarian Affairs (OCHA) reports: "Flooding in North Darfur has damaged 18 homes in Kebkabiya and 550 homes were destroyed or damaged in Sarafaya village (outside El Fasher). A mission to Tawilla following reports of flooding that occurred on 4 June found 6,198 people in need of assistance. In Leiba, South Darfur, an inter-agency mission identified 325 people affected by flooding caused by torrential rains on 8 June." (Sudan Flash Flood Update No. 8, [https://reliefweb.int/sites/reliefweb.int/files/resources/190620_Sudan_Flash_Update-8.pdf 20 June 2019 ]) | ||
+ | |||
+ | '''Western Europe''' CHIRPS show below average rainfall in much of western Europe.This signal is coming coming both stations and CHIRP. In Austria the stations showed higher severity of deficits than CHIRP. | ||
+ | |||
+ | '''Panama''' All CHIRPS variations (CHIRPS, CHIRP, CHPclim show a North-South swath of high rainfall values. Does not look like a physical rainfall feature. Is also in the preliminary v2 of CHPclim. Would be good to find out what is going on there. | ||
+ | |||
+ | '''North America''' Stations often appear to increase estimates in the eastern US. Indication of potential systematic underestimation of rainfall there by CHIRP. | ||
+ | |||
+ | '''Rchecks Plots''' New lows for CHIRPS mean, max, std dev and z-scores for Latin America but nothing extreme. New highs for CHIRPS mean and std dev for Africa Long Horn but nothing extreme. New high for CHIRPS Anomaly maximum by ~50% in Sahel. Identified this as being in western Sudan, where there were reports of flooding in June. See entry above. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Pete Peterson | ||
+ | |||
+ | === May 2019 === | ||
+ | |||
+ | '''Ethiopia''' The higher than average precipitation in the southwest is mainly coming from CHIRP (satellite-based estimate) information. Based on comparison to station reports, the CHIRPS final estimates are likely too wet there. | ||
+ | |||
+ | '''Somalia''' Rchecker Marty says, "Nice to see no false zeros in the station reports here!" Marty is referring to one of the things we look for during the pre-release CHIRPS Final Reality Checks. Occasionally we notice cases when a station reports a zero value that is highly at odds with neighboring reports and CHIRP. In such cases we give the report extra scrutiny, and if deemed likely to be a "false zero," e.g. an inaccurate report, we recommend not including that report in the CHIRPS blending procedure. One of the station reports in southern Somalia was omitted for this reason last month. | ||
+ | |||
+ | '''Cote D'Ivoire''' No stations reporting for the second consecutive month | ||
+ | |||
+ | ''' Guatemala''' Great to see a very high station density (> 50 reports) in Guatemala. Reports generally agree with respect to locations of above and below average in CHIRP, with one exception: along the Pacific coast CHIRPS has an above average signal while CHIRP shows below average. Several stations point in both directions, but it appears that the wet signal there is mainly dominated by a clump of wet stations that are overriding the below average signal in other areas. | ||
+ | |||
+ | '''Haiti and the Caribbean''' Haiti now has 3 stations reporting to CHIRPS. CHIRP is very different from CHIRPS. The CHIRPS signal in Haiti (below avg in CHIRPS, mixed in CHIRP) is due to these 3 station reports (2 are below avg, 1 is above avg) but also stations in Dominican Republic (all are below average). Hard to know if CHIRP is wrong or if the difference is due to lack of stations in the discrepancy area. Jamaica and eastern Puerto Rico stations indicate below average rain, while western Puerto Rico and central-east Cuba indicate above average rain. | ||
+ | |||
+ | '''Italy/Croatia''' Station reports greatly increased CHIRPS estimates (compared to CHIRP). | ||
+ | |||
+ | '''Russia''' In southeastern Russia several stations report highly above average rainfall. CHIRP does as well but stations are more extreme. Given agreement, this feature in CHIRPS may be associated with a potentially interesting event. Did not get a chance to explore it further. If anyone reading this has information, please share it with us! | ||
+ | |||
+ | '''Myanmar''' The large magnitude of negative anomalies in CHIRPS seems due to below average reports in the neighboring country (southwestern region of China). CHIRP shows below average in this part of Myanmar but to a lesser magnitude. Overall, a below average signal in the region is supported by numerous stations and by CHIRP (across Myanmar, to north and east across southern China, and to west in Bangladesh and eastern India) | ||
+ | |||
+ | '''Philippines''' Impressive agreement between CHIRP and stations with respect to location of above and below average signal on northern islands. | ||
+ | |||
+ | '''Rchecks Plots''' New maximum value for Africa of 2504 mm and anomaly of 2000 mm in Tanzania (islands) | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Pete Peterson | ||
+ | |||
+ | === April 2019 === | ||
+ | |||
+ | '''South Africa''' CHIRPS captures the torrential rainfall that led to flooding and fatalities in Eastern Cape and KwaZulu-Natal provinces of coastal South Africa. A station in this area reported 464 mm (18 inches!) in April 2019. The flooding was documented in the April 25th FEWS NET Africa Hazards report. | ||
+ | |||
+ | '''Caribbean''' CHIRPS shows that the eastern Caribbean has been experiencing below average rainfall and that, in contrast, April was very wet in some eastern areas like the Cayman Islands. According to a Caribbean Drought and Precipitation Monitoring Network Bulletin, "CIMH said that there is concern for most of the Caribbean that the short term drought situation can impact agriculture, as well as the flow in small rivers and streams except in the vicinity of Cuba, the Bahamas, Jamaica and Cayman islands." Link to report [https://www.stlucianewsonline.com/caribbean-countries-warned-to-conserve-water-as-drought-worsens/ here]. | ||
+ | |||
+ | '''Central America''' CHIRPS has begun receiving and ingesting a large number of stations in Guatemala, which is markedly improving the estimates. See [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2019/tons%20of%20stations%20in%20guatemala_changes%20prelim%20anomaly.PNG here] for an example of how CHIRPS Prelim for April compares to the pre-release Final, with stations overlaid and the resulting product. In this figure the middle panel shows where stations are located (by pronounced boxes and symbols) and how their reports compare to historical average rainfall. Nice to see sub national variations in the result, due wholly to these stations. In combination with other station data contributions, such as in Panama (see February wiki entry) and Mexico, station density is certainly looking better in this region. | ||
+ | |||
+ | '''Europe''' CHIRP largely underestimated rainfall for the month of April. Stations contributed a great deal to capturing multiple storms across Europe and improved CHIRPS. | ||
+ | |||
+ | '''Portugal/Spain''' Stations capture widespread wet April across northwestern Portugal/Spain and southern Spain, which was missed by CHIRP. | ||
+ | |||
+ | '''Switzerland''' Stations capture extremely wet April across southern Switzerland, which was missed by CHIRP. | ||
+ | |||
+ | '''USA''' Station measurements revealed large area of negative anomalies and z-scores. This reversed the CHIRP estimates in Colorado. | ||
+ | |||
+ | '''CHIRPS issue 1''' Odd data feature identified during Rchecks that shows poor CHIRPS rainfall estimation can occur where two geostationary satellite paths meet. This is in northeastern India. In this case a station located on the eastern swath had higher than average rainfall and seems to have produced a very enhanced above average rainfall signal in data on the western swath. CHIRP was mildly above average in that area of the western swath. The problem is that CHIRPS had an unrealistic rainfall above vs below average pattern on either side of the swath line. Certainly something funny going on with the data production, and we requested that the above average station be omitted from final CHIRPS as a patch to this problem. | ||
+ | |||
+ | '''CHIRPS issue 2''' We found an interesting example of a station + algorithm issue that affects CHIRPS, CHPclim, and CHPclimv2. In this case there is a long term station that seems to have been included in CHPclim that corresponds to an unrealistic circular feature in the CHIRPS. The station is at the bottom of a valley in Himalayan mountains north of Nepal. It gets rainfall during the Indian monsoon, but is drier than surrounding area. The current CHPclim algorithm reacts to this situation by producing a dry pimple-shaped feature. This appears in CHIRPS. See the white dot in each panel of the figure [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2019/unrealistic%20feature%20from%20dry%20station%20in%20all%20CHIRPS%20products-%20Nepal_see%20April%202019%20Rchecks.PNG here]. This is a case of CHPclim struggling in extreme topography-- ideally the climatology would have more geographically realistic spatial variations (than a dot!). We will keep an eye out too see if this is a major problem in other areas. It is reminiscent of the 'circle' problems in Brazil CHIRPS data, which was noted in earlier Rchecks wiki entries. | ||
+ | |||
+ | '''Rchecks Plots''' New high z-score mean for entire global domain. Large anomaly maximum in Latin America. New low for South American minimum anomaly. Other than these, stats are in normal ranges. For those noted, no pressing need to investigate further before data release. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Marty Landsfeld, Seth Peterson, Sari Blakeley, Pete Peterson | ||
+ | |||
+ | === March 2019 === | ||
+ | |||
+ | '''Mozambique, Malawi, NE Zambia, SW Tanzania''' We normally have reports from two gauges along central Mozambique coast. Neither of these reported for March 2019. Could they have been damaged by Tropical Cyclone Idai? CHIRPS shows above average rainfall from central Mozambique to the north... into Malawi and near NE Zambia-SW Tanzania. Based on comparisons to TAMSAT, PERSIANN, and ARC2, the above average signal is mainly agreed upon by products. The most different product is ARC2, which shows above average rainfall as being less expansive and mainly in Mozambique. Two stations in NE Zambia and SW Tanzania indicate that CHIRPS estimates are too high in that area. The large extent above average signal is mainly coming from CHIRP. | ||
+ | |||
+ | '''Kenya''' We inspected two stations using dekadal reports from the Kenya Met Department website: One in Kitale (western Kenya) and one in Wajir (northeastern Kenya). Kitale report from GSOD did not match the KMD reports and was recommended for removal from CHIRPS. Wajir station from GSOD did match and was retained. The Wajir report plus influence from other stations in region prevented a moderate wet signal from appearing in CHIRPS in the NE Kenya to E Somalia area. This wet feature was coming from the CHIRP satellite information. Several other satellite products (TAMSATv3, PERSIANN, and ARC2) also showed a similar wet feature. We have more confidence in the station reports than the satellite information so it was good to see the blending process produced this correction. | ||
+ | |||
+ | '''Angola''' In central-west Angola there is a wet feature that produces an above average signal surrounded by an extensive below average signal. This is in direct opposition to nearby SASSCAL stations. CHIRP is the source of this signal. Interestingly, this feature is also seen in TAMSATv3 and PERISIANN CCS. It is much less pronounced in ARC2. Probably has something to do with common satellite information used in CHIRP, TAMSAT, and PERSIANN. Interesting that a similar thing is seen from the satellite products in NE Kenya (see "Kenya" note above). | ||
+ | |||
+ | '''South Africa''' We inspected two GTS stations in NE South Africa because they had same value (7.2mm) and low zscores. We compared these reports to reports from AccuWeather website. March Accuweather reports for Rustenburg total to 7.4 mm (<10% of average). So the 7.2mm there looks correct. Accuweather reports for Ermelo total to 17 mm) (<20% of average). Not identical value, but only off by 10mm. % of average is in agreement with the low zscore. Retained both GTS reports in CHIRPS. | ||
+ | |||
+ | '''Central America and Hispaniola''' Widespread below average March rainfall (zscores ~ -1) from Mid-Mexico down to northern Columbia. Rainfall has been below average for Central America region since last summer. Likely related to the borderline to moderate level El Nino conditions since then. | ||
+ | |||
+ | '''Problem with CHPclim in Indonesia''' CHPclim is the climatology used in CHIRPS. It has large influence on estimated rainfall values. In northern Indonesia (northern Paua Barat province) CHPclim has either near zero or patchy values for December-March. This produces poor quality CHIRPS values. March 2019 is a good example of this. A station is reporting 319 mm but CHIRPS values are around 15 mm. | ||
+ | |||
+ | '''Australia''' NE coast of Australia suffers from a high number of multiple counted stations. Will be interesting to see if CHIRPS data changes much in v2.1 which will not include this practice. | ||
+ | |||
+ | '''Rchecks Plots''' Latin America average tied lows for CHIRPS mean and z-score means. March 2019 region average is similar to the driest years on record: March 1988 and 1991. 2019 was drier than March 1992 and 2000. Southern Africa came close to the previous low z-score mean. March 2019 region average is similar to March 2013 and a small set of other previously very dry Marchs. Other than that, pretty normal stats. | ||
+ | |||
+ | Contributors: Laura Harrison, Seth Peterson, Marty Landsfeld, Sari Blakeley, Will Turner, Pete Peterson | ||
+ | |||
+ | === February 2019 === | ||
+ | |||
+ | '''Panama''' CHIRPS Panama estimates will now include reports from around 23 stations, which is a major improvement from the 3 station reports that previous data relied upon. Since it was the first time including this source, we took a careful look. It looks like good data, and confirmed that northern South America and the Pacific-side of southern Central America were dry this month. | ||
+ | |||
+ | '''Southern Africa dryness continues''' Similar to previous months of the 2018-2019 season, February rainfall was below average for a large area of Southern Africa. February deficits are most expansive in western and central areas including southern Angola, Namibia, Botswana, southern Zambia, western Zimbabwe, and central-western South Africa. Parts of northern Mozambique and western Madagascar also were below average in February. In western and central areas named above and also western parts of South Africa's major maize growing area, December to February totals are 0.5 to 2.5 standard deviations below the local 1981-2018 means. | ||
+ | |||
+ | '''Ethiopia''' Inclusion of stations resulted in lower CHIRPS values than CHIRP in central and northern Ethiopia. February CHIRPS shows moderately below average rainfall in southern and central areas and moderately above average rainfall in the southwest. When February deficits, early-mid March deficits, and current forecasts for below average rainfall through end of March, plus a pessimistic forecast for April rainfall from some NMME models are considered, there is concern about a poor start and possibly of overall below average rainfall during Ethiopia's Belg season. This is the main season in southern central Ethiopia and pastoralists in that region are highly dependent on February to May rainfall performance. | ||
+ | |||
+ | '''Mozambique''' CHIRPS values may be overestimating rainfall in southern coastal Mozambique in Inhambane. Two GSOD stations reported 115mm and 103mm, but CHIRPS values are nearly 3x higher. The issue is probably due to a combination of CHIRP estimates being wetter than average there, influence of a very wet station report in southern Mozambique in Gaza that also deviates far from average, and the way this information is used to produce CHIRPS estimates. | ||
+ | |||
+ | '''Afghanistan''' CHIRPS captures extreme rainfall event that led to flooding in Herat in northwestern Afghanistan. A station reported 314mm with a z-score > 3. Given its extreme nature we examined this report carefully and compared to PERSIANN (did not agree with CHIRPS) and RFE2 (agreed with CHIRPS). The report, and CHIRPS values being above average there, are indeed correct: A news report documented extremely heavy rain, the most in over a decade. It caused flooding on Feb 12-13th that resulted in several deaths, traffic accidents, and collapsed houses. Link to article [https://www.tolonews.com/index.php/afghanistan/bad-weather-causes-havoc-herat here]. Flash floods have been reported in Herat province on [https://www.tolonews.com/index.php/afghanistan/bad-weather-causes-havoc-herat March 18th] as well... | ||
+ | |||
+ | ''' Papua New Guinea''' CHIRPS captures flooding in Papua New Guinea, East New Britian province. CHIRPS totals are 300-400mm above average and 800-900mm in total. The accuracy appears solely due to CHIRP, as there are no stations in this area. Link to article is [http://floodlist.com/australia/papua-new-guinea-east-new-britain-floods-february-2019 here]. | ||
+ | |||
+ | '''Australia''' CHIRPS missed a major rain event in Townsville, Australia. While CHIRPS has a large number of Australia stations and these are relatively dense in this region, there is no Townsville station. Many of the neighboring stations and also CHIRP show rainfall deficits. This extreme and localized rain event led to mass farm animal causalities. Link to the report is [https://www.independent.co.uk/news/world/australasia/australia-floods-cows-drown-queensland-townsville-rain-cattle-farmers-outback-a8769541.html here]. | ||
+ | |||
+ | '''Madagascar''' Large (100mm+) deficits in February in northwestern, northeastern, and southeastern areas. Most of the country shows below average rainfall. Exception is central and northern tip. The signal is coming from CHIRP and station reports, with the latter being responsible for the large deficit areas. | ||
+ | |||
+ | ''' India and Nepal''' PERSIANN and CHIRPs are in agreement about above average rainfall in far northern India, Jammu Kasmir, and Nepal. | ||
+ | |||
+ | '''Dominica (Caribbean)''' CHIRP had a high amount of rain across half of the island, but there was nothing in the news, and 2 stations with low totals for February largely corrected things. | ||
+ | |||
+ | '''U.S.''' Station significantly increased estimates in California and Oregon and the southern Appalacian regions. | ||
+ | |||
+ | Contributors: Laura Harrison, Seth Peterson, Marty Landsfeld, Sari Blakeley, Will Turner, Pete Peterson | ||
+ | |||
+ | === January 2019 === | ||
+ | |||
+ | '''Mozambique''' CHIRPS values are overestimating rainfall in central western Mozambique compared to a GSOD report in central Manica province. The station reports 265 mm but nearby CHIRPS values range from 400-600 mm. CHIRPS anomalies in central MZ are very large, from > 250mm in west to > 400mm above average along the coast. There are several stations in the country that show high amounts and above average rainfall, including in Tete province and along the coast, and CHIRP also shows above average The presence of higher than average rainfall in some areas is thus not disputed, but the concern is it may be overestimated in some due to overdue influence of these stations. | ||
+ | |||
+ | '''Turkey/Balkan Peninsula''' Deadly storm slams into the Balkan Peninsula and Turkey at the end of January. Progressed northeastward into Romania and Ukraine. Captured by CHIRP and stations. A link to the news article is [https://www.accuweather.com/en/weather-news/deadly-storm-slams-italy-balkan-peninsula-turkey-with-heavy-rain-and-snow-into-saturday/70007221 here]. | ||
+ | |||
+ | '''Spain''' Stations capture above average rainfall in northern Spain not captured by CHIRP. Outcome is substantially higher accuracy in final product than the satellite-only product (CHIRP). | ||
+ | |||
+ | '''Australia''' Stations did a good job at correcting CHIRP to CHIRPS in Southern Australia. CHIRP showed above average rainfall, where stations showed well below, and final product accounts for that. | ||
+ | |||
+ | '''Costa Rica''' Several of us had concern is that 2 stations with reports of 0mm are helping create major large negative anomalies on the Gulf side of the country (compared to CHIRP). The z-score in affected area of Gulf are not extreme, but are large. This is not a case of duplicate station, as is sometimes seen- seqnums indicate these 0mm reports are from two different GSOD stations near to each other. With goal of reducing influence on the Gulf side we requested one of these stations not be included this month. | ||
+ | |||
+ | '''Caribbean''' Noted during the checks was that in some islands with a climatologically dry side/wet side, an above average report on the drier side resulted in the wet side being estimated as having a very large anomaly. Consistent with how the algorithm operates (% of normal is interpolated) but it produced an unrealistic outcome here. | ||
+ | |||
+ | '''Z-scores reminder''' A reminder to be careful when interpreting z-scores (standardized anomalies) in CHIRPS data in low rainfall regions/periods. These fields are made available to users via the ftp site. In reality checks, z-scores are one field we look to when comparing station values to CHIRPS estimates. Example here is in Myanmar-- There is generally very little rain there at this time of year. Several stations reported 0mm, while CHIRP showed around 4 mm. Yet, by looking at z-scores in the region, if you weren’t careful to look at raw data, the stations overlaid on CHIRPS would look bizarre – exceptionally dry z-score value stations in the midst of an exceptionally wet z-score value CHIRPS field. | ||
+ | |||
+ | '''Reality Checks overview''' 21 stations were identified for removal from the final CHIRPS. 9 of these were in Brazil, due in part to the over influence attributed to them by the current CHIRPS processes step that allows for a single station to be counted multiple times. Not all these cases are grounds for station removal, only when they have a noticed and substantial impact on regional anomaly patterns. This problem is due to be fixed in version 2.1. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Emily Williams, Marty Landsfeld, Seth Peterson, Sari Blakeley, Pete Peterson | ||
+ | |||
+ | === December 2018 === | ||
+ | |||
+ | '''Missing GCHN-v2 stations''' US government shutdown may have impacted access to GHCN-v2 stations, which are considered high quality and an important source in CHIRPS. CHIRPS usually incorporates ~1,000 GCHN-v2 reports globally. Station count (all sources) used for December 2018 CHIRPS data is currently ~12,000. When GHCN-v2 become available, December 2018 CHIRPS data will be reprocessed. | ||
+ | |||
+ | '''Eastern Horn of Africa''' NOAA ARC2 and CHIRPS data have a different interpretation of December rainfall anomalies in eastern Kenya and southern Somalia. Differences can be seen in the figure [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/chirps%20vs%20arc%20east%20afr.PNG here]. CHIRPS, which includes ~16 SWALIM stations in southern Somalia, shows southeastern Somalia as above average. ARC2, which has no stations in Somalia, shows a mix of below average and above average here and in eastern Kenya. In eastern Kenya CHIRPS above average. This is primarily coming from CHIRP signal and stations in central Kenya and southern Somalia. The positive anomalies in the eastern Horn in CHIRPS are consistent with the above average rainfall estimated across equatorial East Africa in CHIRPS. | ||
+ | |||
+ | '''Switzerland and Austria''' Stations in CHIRPS capture storm that hit Switzerland and Austria during the holidays. A link to that article is [https://www.accuweather.com/en/weather-news/christmas-outlook-stormy-weather-to-bring-travel-hazards-for-millions-in-europe-leading-up-to-christmas-day/70006914 here]. | ||
+ | |||
+ | '''Argentina''' Rchecks has higher precipitation than CHIRP in northern Argentina. A website on commodity crops confirms December was wet. Link to article [https://www.graincentral.com/markets/summer-crop-samba-commences/ here]. | ||
+ | |||
+ | '''Southern Africa''' CHIRPS shows December 2018 rainfall as below average for much of Southern Africa. This is consistent with ongoing monitoring and reports in the region. December rainfall was near or above average in some smaller areas of eastern Botswana and northeastern South Africa. Evaluation of difference between CHIRPS Prelim and Final for Dec 2018: As indicated by comparison of anomaly maps: 1) Final is substantially drier in SW Zambia. 4 stations in this zone; 1 was removed for suspected false zero. 2) Final less dry than Prelim in south-central Angola. 3) Zimbabwe Final and Prelim estimates are similar, except that far western Zimbabwe is drier. 4) Areas in NE South Africa with above average in Prelim are still above average but closer to average now. The comparison can be seen here [Figure link coming soon]. | ||
+ | |||
+ | '''Central America and Hispanola''' Widespread dryness for the month on both the islands and most of C. Amer. Based on time series plots for the region, December 2018 CHIRPS mean and average z-score was a new low, compared to 1981-2018 data. Evaluation of difference between CHIRPS Prelim and Final for Dec 2018: No big changes in regional anomaly pattern. Both show below average in western region of Central America. CHIRPS is slightly drier than Prelim in Guatemala and slightly different dry anomaly pattern in Nicaragua. In far southeastern Mexico CHIRPS has a more expansive above average area. | ||
+ | |||
+ | '''West Africa''' Evaluation of difference between CHIRPS Prelim and Final for Dec 2018. Prelim showed below average near coast; Final shows less dryness and a more mixed pattern across this region. | ||
+ | |||
+ | '''United States''' Stations used in CHIRPS significantly increased estimates in the southeastern US. In the western US, a comparison of CHIRPS and Persiann estimates identified there are dramatic differences between these data sets for December 2018 rainfall. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Will Turner, Seth Peterson, Sari Blakeley, Pete Peterson | ||
+ | |||
+ | === November 2018 === | ||
+ | |||
+ | '''Southern Africa''' The inclusion of station reports into CHIRPS resulted in a (more) negative assessment of November 2018 rainfall across much of southern Africa (compared to CHIRP and CHIRPS Preliminary). [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/southernAfrica_chirps%20final%20vs%20prelim%20zscore_postRChecks.PNG See comparison here]. CHIRP and CHIRPS Preliminary for November 2018 were already showing deficits across these areas. Numerous stations (~100) from multiple sources (SASSCAL, GTS, GHCN-v2 monthly) indicate substantial deficits in November 2018 for Botswana, South Africa, Lesotho, Namibia, Zambia, Angola, and in southern Madagascar, southern Mozambique, and southern Tanzania. As usual Zimbabwe does not have stations reporting to CHIRPS. A result is that CHIRPS in Zimbabwe is influenced by neighboring country stations and thus CHIRPS deficits are larger than what is shown in CHIRP and CHIRPS Prelim. It is notable that the difference between the southern Africa CHIRPS and CHIRP means is larger (more negative) than for any previous November in CHIRPS record. This also speaks to the value of the SASSCAL contributions to CHIRPS. | ||
+ | |||
+ | '''Missing GSOD stations''' For a ~5 day period in late November, thousands of GSOD station reports were not available in the main GSOD data repository. This resulted in only a fraction of the usual reports being considered for inclusion into CHIRPS. The reason being is that with this many missing days, the criteria for >27 days of reports to make a monthly total was not met at thousands of locations. In CHIRPS processing, if other sources e.g. GTS were available, those were used to fill in for missing GSOD monthly totals. This filling-in occurred in many regions. Stations counts in Portugal, France, and Spain were notably lower than normal because of the missing GSOD reports. Portugal normally has ~14 GSOD reports; this month Portugal had 0 GSOD reports and only 1 station report guiding CHIRPS. | ||
+ | |||
+ | '''Ethiopia''' The value of Ethiopia NMA's sharing of 50+ stations was clearly shown in November 2018 CHIRPS. CHIRP and CHIRPS Prelim, in central and northern Ethiopia, showed a mixed signal of above and below normal rainfall. Inclusion of numerous NMA stations into CHIRPS changed this signal to show a more widespread pattern of above average rainfall, and with larger positive anomalies. | ||
+ | |||
+ | '''Central America''' The stations that were included in CHIRPS show a similar story as did CHIRPS Prelim—- a below average November. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/centralAmerica_chirps%20final%20vs%20prelim%20zscore.PNG See comparison here]. It would be ideal to have more stations reporting to CHIRPS in this region, but there are ~30 stations in total for the region from south of Mexico to Caribbean to Panama. For monitoring and early warning it is helpful that these stations in CHIRPS were in general agreement with the low latency CHIRPS Prelim. | ||
+ | |||
+ | '''Somalia''' Three station reports were given extra scrutiny due to having reported low values (compared to CHIRPS background estimates). The 2018 Deyr rains have been given careful attention in the FEWS NET community, given deficits being previously reported and estimated. A fruitful Reality Check was to compare daily reports at these stations to daily rainfall time series from NOAA's ARC2 rainfall data. ARC2 does not have stations in Somalia-- we used it as indication of timing and magnitude of potential storms near these scrutinized stations. The comparison yielded support for two of these reports (25mm in Baardheere and 0mm in Mogadishu). The third (0mm) was considered potential false zero and removed from CHIRPS. There are typically ~9 SWALIM stations contributing to CHIRPS estimates in southern Somalia and 30+ SWALIM stations in northern Somalia- making a higher station count in CHIRPS than any other global product. | ||
+ | |||
+ | '''South America''' There is a general trend of higher precipitation in the south of the equator ITCZ in CHIRP but the addition of the stations raises the precipitation values a little, bringing them more in line with those from CMORPH. This feature stretches from Peru through western Brazil, northern Bolivia, Paraguay, and a portion of northern Argentina. | ||
+ | |||
+ | '''California''' Two erroneous stations identified (Bode and Redwood City). These were removed from CHIRPS. Interesting that CHIRP shows average to below average in central and northern California, and inclusion of stations corrected this to an above average signal. | ||
+ | |||
+ | '''Sierra Leone''' Anomaly sign flips in CHIRP vs. CHIRPS, probably due to influence from a wet station in Guinea | ||
+ | |||
+ | '''India''' Stations and CHIRPS Prelim both show below average for most of India (~50 stations). Zscores are -0.5 to -1.5. | ||
+ | |||
+ | '''Japan''' Below average November rainfall, based on Prelim and stations (~50 stations). Anomalies range from ~-20mm up to large deficits of -100—150mm along the west coast. | ||
+ | |||
+ | '''Australia''' Northeastern and eastern coast areas were below average according to Prelim and stations. Through central Australia the stations substantially increased estimated rainfall compared to Prelim, changing that area from average to below average to average to above average. | ||
+ | |||
+ | '''China''' In southeast China stations led to a change in anomaly sign. Prelim was showing a mix of below and above average; stations (~30) being included changed CHIRPS to above average in this region. | ||
+ | |||
+ | '''Indonesia/Papua New Guinea''' Signal in CHIRPS is different than CHIRPS Prelim, despite there being no station reports on this island. Thus it is due to influence of stations in other areas. The change is that the drier than normal southern areas appear drier in CHIRPS Final, and the wetter than normal northern areas are closer to average or below average in a few locations. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Will Turner, Seth Peterson | ||
+ | |||
+ | === October 2018 === | ||
+ | |||
+ | '''East Africa''' Given high level of concern about below normal rainfall in the eastern Horn's OND season thus far, and importance of CHIRPS products in monitoring this event, we took care to notice the data in this region. Here are some features: There is a spot in southern Somalia where ARC2 registers high rain total in a small area, but CHIRPS does not. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/EAfr_values_ARC2_CHIRPSp_oct2018.PNG Compared to ARC2 rainfall estimates], CHIRPS shows higher October 2018 rainfall values in the eastern Horn and has a more realistic looking spatial pattern. A previous analysis [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/October%202018%20CHIRPS%20Prelim%20and%20Somalia%20station%20reports.pdf comparing October 2018 CHIRPS Prelim to SWALIM stations] (which are used in CHIRPS Final) showed that reports matched values well in Bay region, where there were concerns about cropping. Closer to Kenya border we have less confidence in CHIRPS values as some areas may have had localized rainfall. In dry areas we have seen CHIRPS struggle with such cases in the past. One of the SWALIM stations in southwestern Somalia reported 0mm for October. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/africa_arc_90day_bxts_403.gif ARC2 daily] indicated rain in several days, totaling ~20mm for the month, so we took a cautionary route-- we assumed this SWALIM report was a 'false zero' and recommended it not be included in CHIRPS Final. We appreciate FAO SWALIM providing reports early this month-- these were helpful for assessing conditions in the region and providing early warning. | ||
+ | |||
+ | '''Spain, France, Italy''' Stations capture heavy storms throughout northern Spain, southern France, and Italy, which left at least 11 dead in Italy and thousands without electricity. The severity of these storms were not originally captured by CHIRP. News reports about Italy storms [https://www.euronews.com/2018/10/29/at-least-six-dead-as-heavy-rain-flooding-hits-italy here] and [https://www.washingtonpost.com/world/europe/at-least-9-dead-as-violent-storms-buffet-italy/2018/10/30/7ebe16da-dc38-11e8-8bac-bfe01fcdc3a6_story.html?noredirect=on&utm_term=.7ea8b711426c here]. | ||
+ | |||
+ | '''India''' According to news reports, October 2018 was the [https://weather.com/en-IN/india/monsoon/news/2018-11-03-this-october-was-the-driest-in-india-since-1976/ driest October in India since 1976]. CHIRPS also shows October as being drier than normal for large area of the country-- making it the 2nd month in a row with widespread deficits and 3rd month with deficits in some areas. [https://www.bloomberg.com/news/articles/2018-11-08/pests-and-drought-seen-cutting-india-s-sugar-output-from-record Sugar cane yield is projected to decrease, and price to increase]. This dry spell was captured by CHIRP and supported by station data. | ||
+ | |||
+ | '''Sri Lanka''' CHIRP captures [http://floodlist.com/asia/sri-lanka-floods-october-2018 devastating flooding] in Sri Lanka from early October that left 9 dead and 5,000 displaced. | ||
+ | |||
+ | '''United States''' Station values really [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/CHIRP_CHIRPS_compare_s_usa.png contributed to CHIRPS] in the southern Applachians as well as Texas where flooding was an issue in October. | ||
+ | |||
+ | '''Western United States''' CHIRPS anomalies show the [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/ continuing drought] of the west coast states | ||
+ | |||
+ | '''Central America and Haiti''' Below average October rainfall in areas that have experienced rainfall deficits for several months: parts of Guatemala, Honduras, El Salvador, and Haiti. High rain totals and above average signal along Pacific coast, Nicaragua to Costa Rica. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/cmorph_Oct2018-Oct2018_car_anom.gif CMORPH also shows this]. Probably associated with hurricane activity. | ||
+ | |||
+ | '''South Korea and Japan''' Really interesting [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/south%20korea%20vs%20japan.PNG anomaly pattern]. South Korea showing anomalous high rainfall across country while Japan shows opposite. Signals are backed by numerous stations. | ||
+ | |||
+ | '''Southern Africa''' October 2018 is a new low in terms of how much rainfall occurred in the wettest location of southern Africa (lowest CHIRPS Maximum of 1981-2018). Below average rainfall was seen across much of the region. CHIRPS mean for this region indicates October 2018 is [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_africa.stats.2018.10.png among one of the driest Octobers of 1981-2018]. | ||
+ | |||
+ | '''Kenya''' During Rchecks we looked into a potentially odd pattern in western Kenya. There were reports of highly above average rain close to reports of below average rain. Compared to the [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Oct2018-Oct2018_af_anom.gif October 2018 ARC2 anomaly map]. It shows same pattern. | ||
+ | |||
+ | '''West Africa''' CHIRPS shows above normal October rain in Burkina Faso, Niger, and Nigeria. The signal is coming from some numerous station reports and with some agreement from CHIRP. eMODIS NDVI shows [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/2018/wa1831stmdn.png higher than normal vegetation productivity] in early November in that region. Potentially an outcome of above normal October rains. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Marty Landsfeld, Sari Blakeley, Seth Peterson | ||
+ | |||
+ | === September 2018 === | ||
+ | |||
+ | '''Ethiopia''' CHIRPS Prelim (and CHIRP) were wetter than CHIRPS Final. This is due to influence of average to below average station reports in some areas of NW and much of central Ethiopia that were included in final version of CHIRPS. | ||
+ | |||
+ | ''' Philippines''' CHIRPS shows very high rainfall in northern Philippines where [https://phys.org/news/2018-09-nasa-rainfall-analysis-super-typhoon.html Typhoon Mangkhut] passed through. Heavy rainfall from Mangkhut led to a mudslide that killed at least 66 people. At monthly time scale, CHIRP only picked up on moderate magnitude above normal rainfall, but reports from stations in that area produced large (wetter) values in CHIRPS. An extreme station report is 1220mm for the month; others report 300-500 mm. | ||
+ | |||
+ | '''Japan''' CHIRPS shows high amounts of rainfall associated with [https://www.theguardian.com/world/2018/sep/04/typhoon-jebi-japan-hit-by-strongest-storm-for-25-years Typhoon Jebi]. This is coming from both CHIRP and station reports. | ||
+ | |||
+ | '''Cayman Islands''' There is a co-registration issue with small islands, we can see that the shape of the island in vector format is different from the area that is modeled in CHIRP/CHIRPS. In this month this caused an issue because the station value was compared against a (low) ocean rainfall value rather than a (high) land rainfall value, which caused the already high land value (Tropical Storm Isaac) to become even higher. | ||
+ | |||
+ | '''Eastern Caribbean''' Kind of odd, regarding influence of Tropical Storm Kirk on the data: In CHIRP, Barbados has lower rainfall, but the island chain E of it is high rain. From the stations, Barbados got hammered and the island chain was neutral (though stations not positioned the best to capture Kirk effects). In CHIRPS, even with the high station value Barbados rainfall didn't get corrected very much. So this is a different small island phenomenon than for the Caymans. Seems like interpolating from 5 station values is not ideal when rainfall from tropical storms can be so localized. | ||
+ | |||
+ | ''' Costa Rica and Nicaragua''' CHIRP is quite wet in central, western Costa Rica, and western Nicaragua. CHIRPS (with stations) is quite a bit drier than CHIRP. CMORPH is drier than CHIRP as well. | ||
+ | |||
+ | '''Northern India'' In far northern India, CHIRP and stations showed anomalous high rainfall in Himachal Pradesh Mountains. Station reports (but not CHIRP) showed a wet signal also to the south, and this was carried through into CHIRPS. | ||
+ | |||
+ | '''India and SE Asia''' CHIRP and stations show below average rainfall in much of India and many arts of SE Asia. Interesting feature, which we are not sure if is accurate, is an area of above average rainfall in NE India/Bhutan area. Seems to be mainly coming from CHIRP. PERSIAN-CCS also shows below average across this region. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Seth Peterson, Marty Landsfeld | ||
+ | |||
+ | === August 2018 === | ||
+ | |||
+ | '''India''' Northern India recieved higher than average rainfall in August 2018, based on reports of amounts 350mm to 700 mm above normal at several stations in the lower elevation areas of the Himalayas. The wet signal is also shown in PERSIANN-CCS data and CHIRP. | ||
+ | |||
+ | '''Hawaii''' Wow! Two stations near Hilo reported 73 and 48 inches of rain in August. That is 4-6 FEET of rain. CHIRPS Prelim did a decent job of showing spatial pattern of enhanced rainfall on that part of the island but the added stations in CHIRPS Final really upped the magnitude. Tropical Storm Lane was responsible for much of the monthly total and produced record breaking rainfall for August. [http://bigislandnow.com/2018/08/25/hilo-sets-rainfall-record-for-august/ Read the story here] | ||
+ | |||
+ | '''Haiti''' CHIRPS shows below average August rainfall particularly in southern areas. This signal is coming from CHIRP and possibly also also influence of a substantially below normal (z-score ~2.6) report in southwest DR. Three other stations in DR show below normal (but closer to normal). Haiti has no reporting stations. CHIRPS final similar to CHIRPS Prelim for August 2018. | ||
+ | |||
+ | '''Brazil''' Near the coastline south of Salvador, Brazil shows a large increase in rainfall from CHIRP to CHIRPS, going from ~200 to 400mm. However there aren't any visible stations causing this, the only visible stations (in EWX version of CHIRPS Rchecks) have neutral to slightly negative anomalies. Not sure what is going on here. | ||
+ | |||
+ | '''Liberia''' There is a spot of low rainfall in central Liberia that stands out as "off." This is present in August CHPclim, teh CHIRPS climatology, and likely the cause. | ||
+ | |||
+ | '''Sudan''' No stations reporting in Sudan. Last month there were 14. Previous Rchecks month/years shows the number of stations varies a lot from month to month. | ||
+ | |||
+ | '''More about RChecks''' 23 cases were carefully examined during Rchecks, and this led to 10 stations being removed from global August 2018 CHIRPS final data. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Sari Blakeley, Seth Peterson | ||
+ | |||
+ | === July 2018 === | ||
+ | |||
+ | '''Ethiopia''' Ethiopia CHIRPS data based on > 30 stations. These generally confirm the pattern of below average rainfall in southern, central and northern Ethiopia as shown in CHIRP and CHIRPS Prelim. CHIRPS and stations show above average rainfall in two localized areas: a small zone in central Oromia and at border of Amhara and Afar. The drier than normal July signal is more severe in CHIRPS than CHIRP and Prelim in some areas. | ||
+ | |||
+ | '''Greece''' CHIRPS data, due to incorporation of stations, captures series of flash floods towards the end of July, following the [https://www.accuweather.com/en/weather-news/at-least-60-people-killed-by-fast-moving-wildfires-near-athens-greece/70005584 deadly wildfires in Athens, Greece.] | ||
+ | |||
+ | '''West Africa coast''' An area along coast that usually has a station (GTS or GSOD) is not reporting. This results in the countries of Guinea, Sierra Leone, and Liberia having no station reports. End result is that CHIRPS data is mimicking the CHIRP signal and is somewhat influenced by stations outside the area, which lowers confidence in CHIRPS estimates of below average in that area. However, CHIRPS is not the only data showing this dry signal. TAMSAT and PERSIANN data also show below average here. This is a curious area because recent months have also registered as below average in CHIRPS but ARC2 data has been showing the opposite in all except May. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/Jul2018/West%20Africa%20coast_CHIRPS%20and%20other%20data%20anomalies_July2018.PNG July 2018 anomalies from multiple data sets shown here.] | ||
+ | |||
+ | '''Mexico and Central America''' According to CHIRPS July 2018 rainfall was below average for a large region including central and southern Mexico and through Central America to western Costa Rica. For this region: In comparison to July 2015, the summer of drought leading up to the major 2015/16 El Nino, this July (2018) had lower rainfall in many areas and the spatial extent of the below average precipitation signal appears larger, in part due to much of Mexico being affected in 2018. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/Jul2018/CAM_CHIRPS_anomaly%20July_2018vs2015.PNG Comparison of July 2018 (left) to July 2015 (right) CHIRPS here.] | ||
+ | |||
+ | '''Mozambique''' Multiple stations in Mozambique and southern Malawi report higher than average rainfall in July 2018. To some extent this is supported by ARC2 data, which shows above average rainfall at spots in these areas. The spottiness of ARC2 here is likely problematic for users of that data. In comparison the signal in CHIRPS data is coming from >10 stations of different sources and shows a more geographically expected precipitation pattern. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/Jul2018/Mozambique_CHIRPS_ARC2_July2018.PNG July 2018 data for CHIRPS and ARC2 can be seen here.] | ||
+ | |||
+ | '''Uganda''' The drier than normal July signal in northern Uganda looks less severe in CHIRPS than CHIRPS Prelim. There are two stations in vicinity (NW Kenya and central Uganda) which both show standardized anomalies of -1.7 and -0.5, respectively). CHIRPS shows standardized anomalies of -0.5 to ~-2 in some areas. Reason for more severe signal in Prelim may be CHIRP and preliminary GTS stations. | ||
+ | |||
+ | '''Senegal''' Multiple data sets, including CHIRPS, show below average July 2018 rainfall in western Senegal. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/Jul2018/West%20Africa%20coast_CHIRPS%20and%20other%20data%20anomalies_July2018.PNG July anomalies can be seen here.] This area has been highlighted in FEWS NET weekly and seasonal monitoring as an area of concern for poor cropping conditions and potential food security issues. | ||
+ | |||
+ | '''Switzerland''' Stations capture continued drought in eastern Switzerland. [https://www.thelocal.ch/20180719/switzerlands-driest-summer-for-more-than-a-decade-threatening-water-supplies 'Driest summer for more than a decade'] | ||
+ | |||
+ | '''Serbia''' Stations capture intense storms and flooding throughout Serbia for the month of July. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Sari Blakeley, Seth Peterson | ||
+ | |||
+ | === June 2018 === | ||
+ | |||
+ | '''Haiti and Dominican Republic''' A station in southern coast of DR was removed from CHIRPS because it seem to have adverse influence in Haiti, where a dry signal was shown by CHIRPS, other stations, and other rainfall and vegetation products. This station reports highly above average rainfall (total 221mm, anom ~130mm). Upon comparison to CMORPH it might be from some on-land influence of an offshore area of above average rainfall (related to storm Beryl?). The value itself is thus believable but the influence seems to be such that precipitation in Haiti is markedly changed from CHIRP anomaly, which shows below average across Hispanola and agrees with CMORPH June anomaly. [ftp://ftp.cpc.ncep.noaa.gov/fews/haiti_threats/haiti_20180719.pdf Drought conditions] have been recently reported in Haiti | ||
+ | |||
+ | '''Kenya''' CHIRPS in western Kenya show large positive anomalies. While stations to the northwest and southeast do show above average precipitation, there are no stations within the area that has very large positive anomalies. The signal is coming from CHIRP and probably also influence from the stations outside the area, plus the area's higher climatology, as described below in the Columbia and Ecuador entry. | ||
+ | |||
+ | '''Southern Africa''' Coastal areas of Southern Africa shows a weak below average precipitation pattern that comes from station reports. These are generally enhancing the signal shown by CHIRP. Interesting that CHIRP anomalies offshore are stronger below average than on land. Together the stations and CHIRP indicate a region-wide drier than average signal. | ||
+ | |||
+ | '''Columbia and Ecuador''' Contribution of stations into CHIRPS increases the magnitude of the negative anomaly shown by CHIRP in coastal Ecuador and Columbia. The influence seems to be coming from inland stations that have large negative standardized anomalies. There are no stations on the coast here, and in fact the nearest coastal station, at the northern edge of the coastal area, has a positive anomaly. This case might be a result of a feature of CHIRPS algorithm that applies closest 5 stations' percent of normals to the local pixel's climatology to estimate local precipitation. The climatology in this area is relatively high, which means that a drier than normal signal from elsewhere would be amplified. | ||
+ | |||
+ | '''India''' CHIRP shows above average and high rainfall totals along western coast of peninsula. 8 stations along this zone also report very high amounts. The station totals tend to be higher than CHIRP totals, but not in all cases. Result is CHIRPS totals of 750mm-1500mm in this zone, maybe some pixels are even higher than 1500mm. | ||
+ | |||
+ | '''Mariana Islands''' CHIRPS estimate of 3270mm here is an all time high CHIRPS value. This is the same island chain that produces extremely high z-score values (10^11). This needs to be investigated and resolved in CHIRPS 3.0. | ||
+ | |||
+ | '''Afghanistan''' RFE2 and CHIRPS data in agreement about localized higher than normal precipitation in southeast Afghanistan. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Lilian Yang | ||
+ | |||
+ | === May 2018 === | ||
+ | |||
+ | '''Continuation of wet conditions in some of East Africa''' CHIRPS May 2018 data shows positive rainfall anomalies in interior areas (from western Kenya north to South Sudan and western central Ethiopia) and eastern areas (coastal Tanzania and Kenya, southern Somalia, and northwest Somalia). This is consistent with [https://reliefweb.int/sites/reliefweb.int/files/resources/UNICEF%20Kenya%20Floods%20Response%20Update%20-%2031%20May%202018.pdf flooding] and landslide-related disasters, large numbers of displaced people, and many fatalities in some of these areas. In Kenya the number of fatalities is [http://floodlist.com/africa/kenya-flooding-death-toll-march-may-2018 at least 186 people during this extremely wet March to May season.] | ||
+ | |||
+ | '''China (south east)''' [http://www.scmp.com/news/hong-kong/health-environment/article/2148803/hong-kongs-dry-spell-continues-are-drought-fears Severe drought continues] in south east China (including Hong Kong). CHIRPS May 2018 data shows large magnitude deficits. Subtropical Hong Kong gets an average of 2,400mm of rain a year, about a tenth of which comes in May. But since January this year, less than 170mm has fallen on the city, under half the normal average for this period. Low rainfall, coupled with high heat has begun to deplete reservoirs, which farmers rely on for irrigation. Some crop failure and wilting has been reported. | ||
+ | |||
+ | '''Guinea and Sierra Leone''' Substantially below avg. rainfall (~100mm deficits) indicates [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/will/Season_WRSI_Monitoring/West_Africa/CurrentSOSTimeliness_asof_2018June1.png multiple week delay] to growing season rainfall. NDVI anomaly maps had indicated vegetation impacts. More extreme in CHIRPS than CHIRP. Careful though. Biggest signal is in areas without stations but with higher climatology (e.g. central Guinea); surrounding stations are leading to increased deficits in some areas. However, CHIRP does show deficits of ~80mm. | ||
+ | |||
+ | '''India (southwest coast)''' CHIRP and stations both capture early monsoon arrival on the southwest coast of India. CHIRP fails to identify [https://www.cnn.com/2018/05/29/asia/monsoon-deaths-india-intl/index.html deadly storms] in northern India (Uttar Pradesh), though they are captured by several stations | ||
+ | |||
+ | '''Armenia''' High rainfall amount in CHIRPS confirmed by [http://hetq.am/eng/news/89180/lernagogs-floods-residents-are-still-assessing-yesterdays-damage.html flooding report] | ||
+ | |||
+ | '''Bangladesh''' CHIRP and stations both capture [https://www.firstpost.com/world/bangladesh-floods-officials-say-over-900000-people-displaced-rescue-work-underway-3779405.html devastating floods in Bangladesh] | ||
+ | |||
+ | '''Thailand''' Stations capture [http://www.chiangmaicitylife.com/news/teacher-drowns-in-chiang-rai-floods/ flooding in northern Thailand] (Chiang Rai) that caused a fatality | ||
+ | |||
+ | '''Tasmania''' CHIRP and stations fail to identify extreme rain events in southeast Tasmania. Rain and thunderstorms brought exceptionally high rainfall to the southeast of Tasmania, in particular to Hobart and the nearby Wellington Range where almost all sites reported their highest May daily rainfall on record. The daily totals of 236.2 mm at kunanyi (Mount Wellington Pinnacle) and 226.4 mm at Leslie Vale are now ranked two and three in the list of [http://www.bom.gov.au/climate/current/month/tas/summary.shtml highest May daily rainfalls ever recorded in Tasmania.] | ||
+ | |||
+ | '''Ethiopia''' May CHIRPS shows below avg rainfall through northern and central regions. The signal comes from NMA station reports and CHIRP. The stations enhance the deficits compared to CHIRP but show similar pattern. Rchecks identified that multiple stations (from SWALIM and NMA)indicated dryness in eastern area and that instead of reflecting this, the first version of CHIRPS was showing an above average signal. Further analysis indicated that a single highly anomalous wet station reporting ~300mm from a mountain top in the area, along Somalia border, may have been positively swaying the regional signal. Comparisons were done to dekadal rain totals and anomaly maps from Ethiopia's MapRoom- these did not show such high rainfall. The station was omitted from CHIRPS final based on concern it was casting too much weight. [https://reliefweb.int/disaster/tc-2018-000059-som Tropical Cyclone Sagar] did pass across parts of northern Somalia, and other remaining anomalous wet stations still show its impact. | ||
+ | |||
+ | '''Somalia''' Overall CHIRPS appears to have good estimates for Somalia. Areas of below average rainfall in the eastern Horn (from stations) are showing up in CHIRPS, as are above average rainfall estimates in southern and northern areas. CHIRP is consistent in some of these areas but stations are having clear role. Note that several stations report below average rainfall in southern Somalia and CHIRPS may be overestimating in these areas due to wetter stations nearby. [https://reliefweb.int/map/somalia/tropical-cyclone-sagar-warning-n11-may-19-2018-1130-am Tropical Cyclone Sagar] in early May had some role in heavy rainfall in northern Somalia. | ||
+ | |||
+ | '''Mozambique''' There is a single station in coastal central MZ creating a below avg. signal that propagates towards interior. CHIRP does not indicate this. We compared to ARC2 to find that ARC's May 2018 anomalies and May climatology pattern is odd looking (spotty) in southern Africa. There is a large difference between CHIRPS and ARC2 May climatology in this central coast area in particular-- CHPclim shows the area receives from 25-80 mm on average. Hence why the CHIRPS anomaly propagate through this area. The station report was deemed as potentially being accurate-- ARC2 also shows a below average spot there. | ||
+ | |||
+ | '''Niger''' There is an incorrect blob of rainfall in northern Niger data, which is usual for May CHIRPS. The feature comes from a wet feature in the climatology (CHPclim) being perturbed by estimated percent of normal to produce CHIRPS estimates. Sometimes remote stations have enough influence to perturb it towards substantial rainfall values, which is what may explain this month's estimates of 25-50mm (+10-25mm anomalies). CHIRP anomalies are close to zero. | ||
+ | |||
+ | '''Ghana''' In northern Ghana a positive anomaly at a rain gauge seems responsible for an area of enhanced positive anomaly to its south. Little influence from other rain gauges for explaining this rainfall event, but rather a likely influence of it working with the higher climatology to produce a larger anomaly in that area. | ||
+ | |||
+ | '''Republic of Congo and DRC''' The rain gauges are on either side of the border between Republic of Congo and DRC, but they have about 200 mm of rainfall difference. There might be an influence of topography. | ||
+ | |||
+ | '''Brasil/Argentina/Uruguay''' There are 3 separate stations in the Iguazu falls area that all show low rainfall. The other stations in the general vicinity and CMORPH all show very high rainfall. | ||
+ | |||
+ | '''United States''' In eastern US, CHIRP did not pick up the very heavy rain amounts in the Appalachain mtns but stations corrected that in the CHIRPS product. CHIRPS overestimated rainfall in the Pacific NW but many low value station readings corrected this in the CHIRPS product. | ||
+ | |||
+ | '''CHIRPS algorithm issues''' May 2018 data in Kenya has a clear example of why it is problematic to make estimates based on a deviation from monthly climatology when the climatology is near zero. November or October 2017 data had same problem in northwestern Kenya. In May 2018 data two stations, in northern and eastern Kenya (179mm and 48mm), report substantial and highly anomalous rainfall; its is reasonable to think this may have occurred through the climatologically dry corridor in northern to eastern Kenya. CHIRPS estimates however are near zero throughout the whole area, including at the 48mm station location. This is because CHPclim is near zero. CHIRP shows average to below average in the area so there is an odd effect where the stations exhibit highly anomalous wet rainfall (zscores >3) but CHIRPS indicates average to below. Being highly anomalous, it is possible that these stations are influencing estimates elsewhere but it is difficult to detangle their influence from other wet stations across the region. | ||
+ | |||
+ | '''Other CHIRPS info''' There were no statistical outliers to report this month. In southern Tanzania, a blocky pattern in anomalies is coming from CHIRP. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Sari Blakeley, Marty Landsfeld, Seth Peterson | ||
+ | |||
+ | ===April 2018=== | ||
+ | |||
+ | '''East Africa''' Consistent with reports of much higher than normal rainfall, which led to a number of disasters and impacts in east Africa, CHIRPS shows highly above average rainfall in April 2018. Extreme rains (>100 mm in 24 hrs) and flash flooding were reported on several days in cities across the country, incl. Marsabit (4/13-4/14), Garissa (4/16-4/17), and Kitui (4/23-4/24). Between 4/9-4/26 the Red Cross estimates 211,000 people were evacuated and 50 people were killed by damages [http://floodlist.com/africa/kenya-thousands-displaced-flooding-april-2018 Floodlist]. Final April 2018 CHIRPS data is based on a relatively high number of stations in Kenya- more than normal- and CHIRPS estimates and stations are in general agreement, albeit in some areas CHIRPS is probably overestimating to some degree (see other entries below). CHIRPS data shows April rainfall was >100 mm above average in many areas of southern Ethiopia, southern Somalia, Kenya, Uganda, and Tanzania. Anomalies ~ 300mm are shown in some of the high elevation zones. The spatial pattern and size of anomalies are overall similar to those shown in ARC2 data. | ||
+ | |||
+ | '''Somalia SWALIM and Ethiopia NMA contributions to CHIRPS''': SWALIM and Ethiopia NMS stations were highly influential for CHIRPS- reports in some areas of southern Somalia, southern Ethiopia, and eastern Kenya were ~100mm lower than CHIRP estimates. Result is that while CHIRPS shows above average precip across region, some of these areas anaomlies are weaker than otherwise would be based on satellite estimate (e.g. ~54 mm vs 180 mm) | ||
+ | |||
+ | '''China''' Stations were important for correcting CHIRP estimates in central-northern china and southeastern china. ~60 stations reported contrasting anomalies to CHIRP, with above average rainfall in central-northern china and below average rainfall in southeastern china. CHIRP showed below average across most of southern china. Could not find news reports to validate, but number of stations in agreement give support for CHIRPS accuracy. | ||
+ | |||
+ | '''Southeast Asia''' Stations were important for correcting CHIRP to above average rainfall in Thailand and northern area of Laos. ~25 stations show general agreement about this. | ||
+ | |||
+ | '''CHIRPS improvements''' During Rchecks on the first version of CHIRPS Final, it was identified that were substantially fewer stations than usual in east Africa and that CHIRP was overestimating rainfall in some areas. The combination of these factors gave concern that it might be reducing accuracy of CHIRPS data this month. Rcheckers and Pete Peterson, data curator, worked together to identify why so few stations were getting through (explained below). After these efforts, which resulted in a more stations being included and other positive outcomes, the final CHIRPS final is regarded with confidence. Including of a higher number of stations helped correct CHIRP overestimation in some areas e.g. coastal Kenya now shows ~150mm as opposed to ~300mm, which is more in line with stations, and Kilimanjaro shows values closer to ICPAC-blended data from bulletins. Positive outcomes of these efforts are better station coverage in east Africa in April 2018, identification of a screening step that needs to be evaluated more closely, and some of the added stations were in support of CHIRPS estimates, which is always great see. The reason for the initial lack of stations was identified- it was a data quality screening step (false-zero screening) that reduced 26 available GTS stations to 2. GSOD were reduced also such that Kenya only had 4 stations in CHIRPS. The hypothesis is that two factors in processing reduced number of days with reports to below the required threshold for them to be used for monthly totals. One factor was that there were no GTS reports on the GTS ftp site for one day (4/29), which counted against the monthly tally for the stations. Two, there may have been days where reports of 0mm were incorrectly identified as false, potentially b/c of extremely high CHIRP values. To get the stations back in Pete omitted the false zero screening step in east Africa countries. Screening steps are one of the processing features that will be revisited in the planned CHIRPS v3.0. In the meantime, an extra check may be introduced to processing prevent this type of problem. | ||
+ | |||
+ | Contributors: Laura Harrison, Will Turner, Marty Landsfeld | ||
+ | |||
+ | ===March 2018=== | ||
+ | |||
+ | '''East Africa''': CHIRPS, CHIRP, and station reports show a convergent story-- anomalous wet conditions occurred in March across the region, with largest anomalies (>100 mm) in Uganda, Kenya, Burundi, Rwanda, and Tanzania. This led to major flooding problems in [http://floodlist.com/africa/uganda-floods-mbarara-march-2018 Uganda,] [http://floodlist.com/africa/burundi-landslide-bujumbura-march-2018 Burundi,] and [http://floodlist.com/africa/kenya-floods-mid-march-2018 Kenya]. | ||
+ | |||
+ | '''Mediterranean''': Stations included in CHIRPS reported the anomalous high rainfall that led to major flooding in northern Algeria, Gibraltar, [https://www.accuweather.com/en/weather-news/spain-portugal-brace-for-more-rain-and-flooding-following-storm-emmas-wrath/70004304 Portugal] and [https://www.euroweeklynews.com/news/on-euro-weekly-news/spain-news-in-english/1471919-watch-storm-felix-slams-into-spain-bringing-rain,-flooding-and-high-winds Spain] from Storm Emma and Storm Felix, which was not previously represented in CHIRP. | ||
+ | |||
+ | '''Balkans''': Stations also showed the high rainfall associated with Storm Emma that caused flooding in [https://www.aljazeera.com/news/2018/03/rain-quick-thaw-brings-flooding-balkans-180310090055585.html the Balkans.] | ||
+ | Contributors: Marty Landsfeld, Will Turner, Laura Harrison | ||
+ | |||
+ | '''Madagascar''': CHIRPS, thanks to CHIRP and a couple stations) shows the heavy above average rainfall in northern Madagascar associated with Tropical Cyclone Eliakim that caused [http://floodlist.com/africa/madagascar-eliakim-floods-march-2018 flooding and damages]. | ||
+ | |||
+ | '''South America data''' Return of CHIRP data in southern Chile/Argentina. Satellite input had stopped contributing several years ago. | ||
+ | |||
+ | Contributors: Laura Harrison, Marty Landsfeld, Will Turner | ||
+ | |||
+ | ===February 2018=== | ||
+ | |||
+ | '''Southern Africa''': Reversal of rainfall signal between January and February 2018 for a large region. This was noted during weekly FEWS NET Hazards monitoring, and CHIRPS data confirms. After an extremely dry January across large parts of southern Africa south of 10 S, extreme wet conditions were seen in February in Zambia, Zimbabwe, central-south Mozambique, northeast Botswana, and northern South Africa. As noted below, there were no stations reporting to CHIRPS in Zambia and Zimbabwe (fewer than normal were in Moz too). This wet signal is coming from several wet stations and CHIRP. Is also corroborated by other products (PERSIANNE-CCS, ARC2). | ||
+ | |||
+ | '''Tanzania''': According to CHIRPS, a drier than normal February prevailed across Tanzania, with large negative anomalies (< -100 mm) in southern Morogoro province (also in northern Mozambique). This is consistent with CHIRP, ARC2, and PERSIANNE. After noticing that there was a station in southern coastal TZ that was being duplicated in CHIRPS, Rcheckers recommended removal of this station to prevent the duplication from artificially enhancing the dry signal (the duplication is a known problem in current processing method and is schedule to be fixed in next version). This station was not removed during processing of CHIRPS-final, so unfortunately it may be having a negative impact on the CHIRPS data by artificially enhancing dryness in the locale of Mtwara (TZ) and northeast Cabo Delgado (MZ). | ||
+ | |||
+ | '''Kenya''': Station in east central Kenya removed. This station, at 52mm, was wetter than would be expected, given that a station next to it had ~5mm. To assess, we looked to IGAD/ICPAC dekadal bulletins for February. For their data they improve CHIRP data by blending it with many stations provided by some GHA countries. IGAD dekadal bulletins reported all three dekads had < 5mm each in that area. Thus the GHCN-v2 station was deemed inaccurate and removed. Note that this station does not consistently report and when it does it usually shows substantially higher rainfall than its GTS neighbor. The IGAD/ICPAC website was added to the 'Helpful Links' list so that all Rcheckers can quickly access the website for future checks. | ||
+ | |||
+ | '''Zimbabwe''': No stations reporting again. Like in January 2018, no station reports went into CHIRPS. GTS stations did share reports for some stations but only for ~18 days. This was not enough to meet the requirement to go into CHIRPS (27 days) to make a monthly total. | ||
+ | |||
+ | ''' Zambia''': No SASSCAL stations reporting. This was concerning, as we typically receive ~10 stations and incorporate these into CHIRPS. According to the SASSCAL website (http://www.sasscalobservationnet.org/), these stations have not reported to them in around a month. | ||
+ | |||
+ | '''Artifacts in CHIRPS''': Arcs and blockiness are visible in data, anom, z-scores in south-central to south-eastern areas of Africa. This was seen during Rchecks; Rcheckers notified CHIRPS data curator. Same artifacts came though in final version of product too. | ||
+ | |||
+ | '''Example of Rchecks''': Here is an example of the type of process that occurs during CHIRPS Reality Checks. ''Compared to CHIRP, several stations created rainfall in southern Burkina Faso and Ghana. CHIRPS shows it as wetter than average for Feb 2018. One of the stations (GSOD, 277149) is especially high at 93 mm. This station we have not seen in CHIRPS in past year... so is suspicious. However, ARC2 also shows a signal of above normal rainfall, so suggest to not remove any of these stations.'' | ||
+ | |||
+ | '''South America''': CHIRPS shows an anomalous pattern of dry-wet-dry for the areas around southern Columbia (dry), northern-central Brazil (wet), and southern Brazil/Uruguay/Argentina (dry). Some of the anomalous dryness was due to enhancement of CHIRP signal by stations. Each of these regions had >25 stations with convergent reports, expect for southern columia which had the extreme dry coming from ~15 stations. Persianne data also shows this pattern of anomalous dry-wet-dry. INMET brazil site also shows high > 250mm rainfall in same area as CHIRPS (http://www.inmet.gov.br/portal/index.php?r=tempo2/mapasPrecipitacao). Overall, the pattern and station reports appear robust. | ||
+ | |||
+ | '''Western Australia''': As a result of [http://www.abc.net.au/news/2018-02-18/lives-and-homes-under-threat-from-cyclone-kelvin-as-it-hits-wa/9459192 Cyclone Kelvin], CHIRPS station data was much higher than CHIRP estimates, especially across the central and southern regions of Western Australia. | ||
+ | |||
+ | Contributors: Laura Harrison, Libby White, Marty Landsfeld | ||
+ | |||
+ | ===January 2018=== | ||
+ | |||
+ | '''Overview''': There are no wiki entries this month. However, a full Rchecks was done on the January 2018 data. 14 stations were identified as problem data. All 14 recommendations were taken-- these stations were removed from the final version of January CHIRPS. For more information, we point you to the January 2018 section of the CHIRPSv2 station [https://docs.google.com/spreadsheets/d/1GK86wSQdJwMp6Sa-ySvOM7fP_StVG0xmVg9Iv_b_gxk/edit?usp=sharing watchlist], which has comments and group discussions from the Rchecks. | ||
+ | |||
+ | Contributors: Laura Harrison, Sari Blakeley, Will Turner, Marty Landsfeld | ||
+ | |||
+ | ===December 2017=== | ||
+ | |||
+ | '''Southern Africa dryness in December 2017''': As the dryness is shown across large area of southern Africa, comparison of z-scores from CHIRP vs CHIRPS is helpful for gauging extremity of situation. In CHIRP, Dec rainfall was around -0.5 standard deviation in parts of Botswana, all of Zimbabwe, southern Zambia, central and southern Mozambique, northern and southern South Africa, and parts of Namibia; in CHIRPS the pattern is more defined spatially, with December dryness being more focused and intense (z of -1 to -2) in parts of the area covering central/southern Botswana, northern SA, to central/eastern Zimbabwe and western areas of Mozambique. Also parts of Namibia and southern South Africa. Anomalies show below average Dec rainfall across most areas of southern Africa south of 15S. Exception is in an area in eastern South Africa. Something to also note is that there is quite good station coverage in Namibia (~40) and South Africa (~50) | ||
+ | |||
+ | '''East Africa dryness in December 2017''': Below average Dec rainfall in Uganda, Kenya, northern Tanzania, much of Ethiopia and Somalia according to both CHIRP and from stations (CHIRPS). | ||
+ | |||
+ | '''Ethiopia''': A note on the relatively large number of stations that report to CHIRPS in Ethiopia, which is typically undersampled in global precipitation data sets. There are consistently around 30 stations in Ethiopia in Dec (and November, October), thanks to contributions from Ethiopia NMA. Really nice to see this amount of measured rainfall coming into CHIRPS. Note that these are all 0mm in December, as expected based on climatology, but that in previous months there was more variability. | ||
+ | |||
+ | '''Southern Mozambique''': December CHIRPS shows below average rainfall in central and southern MZ, with average anomalies aorund 75mm. This follows a below average November in southern MZ. | ||
+ | |||
+ | '''Central Kenya''': Two instances of station duplication resulted in removal of the stations. One was near Mt. Kenya (triple counted) and one was to south (2x counted). The latter was removed because it had a moderate-large z-score (~ -2.6) and we did not want this to have more influence on regional CHIRPS than other stations, which also showed below average December 2017 rainfall but to a lessor magnitude. | ||
+ | |||
+ | '''Zimbabwe''': 0 stations reporting; normally we have 5-15 GTS and GSOD. CHIRPS shows anomalies of 125-150mm in central and eastern areas of the country and below average by 10-50mm for most other areas of the country. Compared to CHIRP, CHIRPS anomalies are amplified by approx 10-30mm in most areas, and in some areas of central eastern areas with large anomalies, by 50-60mm. Given that there are no stations in Zimbabwe contributing to these estimates, this amplification is due to station(s) in other countries. CHIRPS estimates in Zimbabwe should be considered uncertain for this reason. | ||
+ | |||
+ | '''Brazil''': Several stations in the western portion of Brazil's Amazon rainforest and the northern portion of Bolivia identified an anomalously wet December that was not represented in CHIRP. The station values were congruent with each other, and the resulting wet patterns in CHIRPS are congruent with patterns seen in December PERSIANN data (made available by CHRS, http://chrsdata.eng.uci.edu/). | ||
+ | |||
+ | '''Europe''': | ||
+ | All of Spain (except for the Northern coast) showed below average rainfall in CHIRPS for December, continuing a dry trend from the months before. | ||
+ | Northeastern Italy has a station reporting surprisingly low values (added to station watchlist - #201424). | ||
+ | |||
+ | '''North America''': | ||
+ | The Pacific Coast - from the top of CHIRPS (Vancouver island) stretching down to the California Bay Area, and then inland along the Sierra Nevadas, down to Sequoia National Park - shows extremely dry conditions in CHIRP, the stations, and CHIRPS. December was a particularly dry month, with many stations reporting 0mm of rainfall, following from a relatively normal November and dry October. The stations pick up very dry conditions along the Central Coast (in Santa Barbara and then stretching to LA, San Diego, and to the Inland Empire). | ||
+ | Several surprising blotches of high rainfall values in New Hampshire and West Virginia present only in the r-checks file (@ -79.8, 38.7 & @-71.1,44.4) | ||
+ | |||
+ | '''CHIRPS algorithm issues to explore and fix:''' Issue of station duplication was explored in more depth. Analysis showed that throughout the CHIRPS time series (back to 1981) there are typically 300 to 1400 stations that are included in CHIRPS more than once in a given month. This reoccurs in some known areas, like Kenya and southern Brazil, but analysis showed that it also occurs in areas of the African Sahel, eastern South America, the US, Australia, southern Africa, and elsewhere. Many instances were not visible in Rchecks because of location overlap. Steps to stop this duplication were discussed more, and consensus was that it would require an algorithm correction and reprocessing of CHIRPS to a newer version 2.1. Other improvements could also be implemented. More discussion will continue. | ||
+ | |||
+ | Contributors: Laura Harrison, Emily Williams, Will Turner, Marty Landsfeld, Libby White | ||
+ | |||
+ | ===November 2017=== | ||
+ | |||
+ | '''Northeastern Kenya/Southern Somalia''': Very high amounts of rainfall occurred in early November 2017 in some parts of this region, as reported by FAO SWALIM stations. CHIRP also shows above average conditions in NE Kenya and across the northern parts of southern Somalia, though CHIRP anomalies are much smaller (up to 35 mm above average). Two Bay region (Somalia) stations reported around 400 mm rainfall, and that most of it came between Nov 1 and Nov 12. Nearby SWALIM stations reported much lower amounts ranging from 65mm to 185mm. Support for anomalous wet rainfall in that area also comes from ARC2, which shows positive anomalies for most of southern Somalia. Several important points are: 1) These storms do not seem to have affected southern areas of eastern Kenya and southern Somalia, 2) Despite the storms in some areas, products indicate below average rainfall for the October to December period for much of eastern Kenya and southern Somalia [https://edcintl.cr.usgs.gov/downloads/sciweb1/shared/fews/web/africa/east/pentadal/chirps/seasaccumanom/octdec/lta/graphics/ea_anom_octdec_1769_lta.png CHIRPS prelim] [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Oct-Dec_ea_anom.gif ARC2], 3) For agriculture, the below average October and below average conditions after these early November storms are concerning. | ||
+ | It should also be noted that the CHIRPS reality check process was especially useful in this case. Those two Bay stations interacted with the CHIRPS algorithm to produce an artificially widespread area of highly above average rainfall across the region. Discussions and experimentation yielded a solution. These stations were not included in CHIRPS, though other wet SWALIM stations were, and the extent of the anomalous rainfall became smaller. By not including these extreme stations in November 2017 data, CHIRPS is able to portray a more accurate pattern at the regional scale. | ||
+ | |||
+ | '''Stats''' | ||
+ | |||
+ | New CHIRPS - CHIRP high for all of Africa. This is may be plausable since areas of Somalia, Madagascar, S. Africa, Kenya and Gabon were increased by the stations observations. | ||
+ | |||
+ | New CHIRPS - CHIRP low for all of the Great Lakes region. This looks reasonable since many stations in Wisconsin lowered the values for the CHIRPS product. | ||
+ | |||
+ | '''CHIRPS algorithm issues to explore and fix:''' | ||
+ | |||
+ | ''1) Perhaps interpolation oddness to correct in V3.'' On the east coast of South Africa there are 4 stations on the coast showing high rainfall (~260) whereas CHIRP says ~120. Because there are no stations in the ocean to bolster the coastal ones the inland stations dominate and the high stn values essentially aren't being used. [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/people/laura/RChecks_figures/Zaf_nov.PNG CHIRPS with these stations overlaid] | ||
+ | |||
+ | ''2) See influence of extreme stations in top entry.'' Could be that larger impacts are in cases where a) stations are added in 2nd step e.g. SWALIM vs. anchor stations, which are included in 1st step, b) stations are in drier areas with larger decorrelation distance or deviations from average are very pronounced, c) other. Should be looked into more for V3. Note that initially, anomalously wet double-counted stations on Mt. Kenya were thought to be the main cause, but removing these had nearly no impact on the data. | ||
+ | |||
+ | '''Perth, Australia''': There is a thick cluster of stations in Perth (fGTS amd fGSOD), some of which may be double counted or overlapping. | ||
+ | |||
+ | '''Andaman Islands''': There is widely varying pixel values over this area due to the influence of the CHPclim. There is only one station on the Andaman Islands. | ||
+ | |||
+ | Contributors: Africa: Marty Landsfeld, Will Turner, Laura Harrison; Europe, India: Will Turner; East Asia and Oceania: Libby White; Middle East: Marty Landsfeld; South America: Seth Peterson | ||
+ | |||
+ | ===October 2017=== | ||
+ | |||
+ | '''Current East Africa IPC Acute Food Insecurity Phase Level 3 & 4 (Crisis & Emergency) areas http://www.fews.net/''': October rainfall was below average and led to late start of the OND 2017 season by 10 to up to 30 days in some areas of southern Somalia. Some of these areas have experienced [http://www.fews.net/sites/default/files/documents/reports/FEWS_NET_Horn_of_Africa_June%202017_Drought_Map_Book.pdf multiple back to back below average major rainfall seasons in 2016-2017.] | ||
+ | |||
+ | '''Kenya''': In northwest Kenya CHIRPS shows a large area of near zero values. In reality, substantial rainfall occurred her in October (and station report shows supports this). The reason CHIRPS does not show this rainfall is the estimates are a deviation from climatology in the CHIRPS algorithm, and teh climatology is near zero. Next version of CHIRPS will improve this aspect of algorithm so that extreme wet events are better captured. | ||
+ | |||
+ | '''Panama''': Along the southern coast of Panama, CHIRP and RCHECKs shows wetter than average conditions; however, the CHIRPS prelim show it as drier than average. May be being forced by stations in Columbia or further north. | ||
+ | |||
+ | |||
+ | ''Contributors: Africa: Marty Landsfeld, Will Turner, Laura Harrison; East Asia and Oceania: Libby White; Caribbean, North & Central America, Europe: Emily Williams; Middle East: Laura Harrison; and South America: Seth Peterson | ||
+ | |||
+ | ===September 2017=== | ||
+ | |||
+ | '''Current East Africa IPC Acute Food Insecurity Phase Level 3 & 4 (Crisis & Emergency) areas http://www.fews.net/''': September rainfall was mildly below average by 10-20 mm in some of these areas in Ethiopia (southern Oromia and central Somali), Somalia (Bakool in north part of southern Somalia), and Kenya (coastal zone). Rainfall in the next 1-2 months is most important to the current season in these IPC Phase 3+ areas, but average to below average September rainfall is not a good start. Some of these areas have experienced [http://www.fews.net/sites/default/files/documents/reports/FEWS_NET_Horn_of_Africa_June%202017_Drought_Map_Book.pdf multiple back to back below average major rainfall seasons in 2016-2017.] | ||
+ | |||
+ | '''Nigeria''': There is a rather large disparity between CHIRPS and ARC2 in Nigeria for the month of September - CHIRPS is relatively wet in central/northern Nigeria, and relatively dry in the southern portion of the country; ARC2 shows nearly opposite anomalies in the same regions, with a large wet anomaly in far south/coastal area. RFE2 anomalies in Nigeria are similar to CHIRPS. Floodlist (http://floodlist.com/africa/nigeria-floods-kogi-september-2017) reports considerable flooding in central Nigeria, supporting the anomaly values from CHIRPS. Floodwaters from the Niger and Benue Rivers put downstream cities at risk (Sarkin Noma, Lokoja and Ibaji in Kogi State). | ||
+ | |||
+ | '''East Africa''': Across a large area of continental eastern Africa June to September rainfall accumulations were above average. This includes southern Chad, Sudan, South Sudan, Uganda, Ethiopia, and western Kenya. In some Ethiopia and Kenya highland areas the June to September totals were around 2.5 standard deviations above normal. Above average rainfall in September contributed to these seasonal wet anomalies in parts of all these countries. | ||
+ | |||
+ | '''West Africa''': For a large area of West Africa, CHRPS shows September rainfall was below average. This occurred in Ghana, Togo, Benin, Senegal, southern Mali, eastern Guinea, Burkina Faso, Niger, northern and southern Nigeria. According to CHIRPS, it was a continuation of dryness that also occurred in August in some of those areas (eastern Guinea, southern Mali, parts of Burkina Faso, Niger, and northwest Nigeria). Burkina Faso and eastern Guinea also had a drier than average July. | ||
+ | |||
+ | '''Australia''': Two stations were removed, one in Victoria and the other in Queensland. There were also several climatology artifacts across Australia. | ||
+ | |||
+ | '''Fiji''': One station was removed as it was much, much lower (4mm) than CHIRP climatology showed. Station did not impact CHIRPS much. | ||
+ | |||
+ | '''Philippines''': Station values are in agreement in CHIRPS, but show higher precipitation (sometimes upwards of 1,000mm as opposed to 500mm) than in CHIRP. The ~20 stations in the Philippines greatly influenced CHIRPS. | ||
+ | |||
+ | '''Taiwan''': Station values are in agreement across the island, show significantly lower values than in CHIRP. However, we only have station data for the lower elevations, and most of the precipitation shown in CHIRP is in the higher elevations. | ||
+ | |||
+ | '''Japan''': Station values in agreement but show less precipitation than in CHIRP. The station values seem to have had a high impact this month. | ||
+ | |||
+ | '''North & South Korea''': There is a sharp contrast between the CHIRP (higher than average precipitation) and the CHIRPS (lower than average precipitation). Stations appear to be in agreement with each other, so values were kept. | ||
+ | |||
+ | '''Spain and Portugal''': CHIRPS shows September rainfall was below average across both countries, which continued a [https://elpais.com/elpais/2017/08/29/inenglish/1504014135_340158.html severe drought] in some areas. More recently, [http://www.cnn.com/2017/10/16/europe/portugal-spain-wildfires/index.html massive wildfires] in northern Portugal and northwest Spain have consumed forests and killed at least 39 people. | ||
+ | |||
+ | '''France''': Northern France (in the Cotentin Peninsula, in the Caen region) has a noticeable artifact. This artifact is present for all months in CHIPClim. | ||
+ | |||
+ | '''Croatia''': The coastal part of Croatia had a large positive rainfall anomaly that is captured in CHIRP, but is intensified with the rain gauges in the region. | ||
+ | |||
+ | '''CHIRPS algorithm issues to explore and fix''': Rchecks efforts identified 18 stations to be removed from the pre-final version of CHIRPS. Some of these were stations with what appeared to be possible bad values, and the values were applied to two or three locations. This procedure of allowing a station value to be used in more than one location needs to be corrected (stopped). It is especially problematic in areas with low station density. | ||
+ | |||
+ | ''Contributors: Africa: Laura Harrison, Will Turner, Emily Williams; East Asia and Oceania: Libby White; Europe and Middle East; Sari Blakeley; Caribbean, Central, and South America: Marty Landsfeld; North America: Laura Harrison | ||
+ | |||
+ | ===August 2017=== | ||
+ | |||
+ | '''Ethiopia''': In northern Ethiopia, data shows a swath of above average rainfall. No stations reporting there. Anomaly values agree with ARC2: 125-200mm above average. Between CHIRPS and ARC2 there are differences in spatial extent of wet anomalies- CHIRPS has them focused on north-central areas, ARC2 has them across northwestern areas. Overall JJA CHIRPS anom is above average because of anomalous August rainfall. Rainfall in late July and August is important for seasonal totals; June-July were deficit months. | ||
+ | |||
+ | '''Coastal West Africa''': Above average August precipitation; consistent with reports of flooding in Guinea/Sierra Leone (Africa hazards report: (ftp://ftp.cpc.ncep.noaa.gov/fews/threats/afrhaz20170831.pdf) | ||
+ | |||
+ | '''Côte d'Ivoire''': A station in southern Ivory Coast was put on the watchlist for having a much higher value than both nearby stations and CHIRP (333mm vs. ~160mm). | ||
+ | |||
+ | '''Nigeria''': Three Kukua stations were drastically lower than CHIRP and surrounding stations (~16mm vs. ~200mm). These stations were removed. | ||
+ | |||
+ | '''Tanzania''': Data show above average rainfall in some areas of northeastern Tanzania including along coast and islands. Based on 4 stations and CHIRP to a minor extent. | ||
+ | |||
+ | '''DR Congo''': Data shows strange blob of below average rainfall in east Congo. Possible from a weak below average signal in CHIRP; maybe from additional influence of moderate below avg stations in Rwanda/Burundi? | ||
+ | |||
+ | '''Southern Mexico, Guatemala, Belize''': CHIRPS shows below average rainfall in these areas; based on ~50 stations in Mexico, several stations to the south of Guatemala, and to a lessor extent CHIRP. 0 stations in Guatemala and Belize contribute reports to CHIRPS. | ||
+ | |||
+ | '''Australia''': The south eastern Australian coast is somewhat dryer according to station data when compared with CHIRP. | ||
+ | |||
+ | '''Indonesia''': Northwestern Papua had a station removed because it was showing inconsistently lower rainfall than CHIRP and the surrounding stations. | ||
+ | |||
+ | '''Brunei''': A station just outside Brunei was provisionally removed because it reported over 1,000mm of rain vs. ~400mm in CHIRP and surrounding stations. | ||
+ | |||
+ | '''China/the Koreas''': Hubei, Anhui, Jinlin, and most of both North and South Korea station data reported heavier rainfall than CHIRP. Hubei and Anhui stations reported twice as much and Jinlin and the Koreas reported roughly half again as much as CHIRP. | ||
+ | |||
+ | '''Hurricane Harvey''': CHIRPS shows the extreme rainfall associated with Hurricane Harvey in Texas, Louisiana, Oklahoma, and Arkansas. Stations increased the above average signal in CHIRP. CHIRPS anomalies are +300mm for large areas. | ||
+ | |||
+ | '''CHIRPS algorithm issues to explore and fix''': 1) Double-counting stations 2) SETH'S MYSTERY. 1) Currently, when a report from a station is not available, the algorithm looks to a neighboring station to fill it. This can result in the same station value being counted two or more times. This method can cause large problems when double-counted values are bad values; in less extreme cases is still hard to assess what data is right or wrong. Overall, there should be a catch implemented to prevent double-counting. 2) SETH"S DESCRIPTION : in coastal central Brazil, near the town of Salvador, CHIRP shows relatively low rainfall, all of the nearby stations also show low rainfall, somehow RCHECKS/CHIRPS showed a massive increase in rainfall 180 to 373mm, 101 to 219mm are two examples. | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa & North & Central America; Libby White, Africa & East Asia and Oceania; Will Turner, Africa & Eurasia; Seth Peterson, South America | ||
+ | |||
+ | ===July 2017=== | ||
+ | |||
+ | '''Ethiopia''': Below normal rainfall in July 2017 in north eastern Ethiopia. A consistent story across data products (CHIRPS, CHIRPS and stations, ARC2, PERSIANNE, NMA mid-season assessment) | ||
+ | |||
+ | '''Sudan''': V artifact in Sudan (from CHIRP) | ||
+ | |||
+ | '''Japan''': Hokkaido stations report slightly dryer conditions than indicated in CHIRP. | ||
+ | |||
+ | '''Australia''': There is a strange square artifact in New South Wales. | ||
+ | |||
+ | '''Central America''': Above average July rainfall in eastern Honduras, eastern Nicaragua, northern Costa Rica, Panama. Below average in western areas, southern Mexico, Guatemala, Belize, some coastal areas of Mexico (Pacific and Gulf). Overall agreement with PERSIANNE data in terms of this pattern of anomalous rainfall. There are gaps in station reports in Central America this month. Guatemala has 0 stations. Same for June 2017. In May and earlier in 2017 typically had 2 or more (GTS & GSOD). Honduras, Costa Rica, 0 stations. Panama, 3 GTS. Honduras typically has 2 GHCN-v2, Costa Rica has 2 (GTS and GSOD). | ||
+ | |||
+ | '''Southern Mexico/Guatemala central border area and Belize''': Circular below average features. Coming from CHPclim, which has higher climatology in those areas (% of normal applied to higher values translates into larger anomalies). No stations in these areas to compare to. | ||
+ | |||
+ | '''Northern US and British Columbia''': In western areas, CHIRPS shows a swath of below average rainfall for July (1 to 2 standard deviations below normal). Similar area as [https://www.nytimes.com/2017/07/10/us/western-wildfires.html recent wildfires.] Anomalies are average in most of Western US (no rain), with exception of Arizona (and NW mexico) with above average by 25-75mm. Above average rainfall in SE Colorado, SE Oklahoma, and regions near Lake Michigan and Lake Erie including Ohio, Indiana and southern Wisconsin. Also above average in mid Atlantic seaboard. Below average mixed with average in much of SE US, southern Texas, and central US. | ||
+ | |||
+ | '''CHIRP issues in Indian Ocean''': Artifact in CHIRP climatology in July—mottled rainfall pattern across southern Indian Ocean including Madagascar area. June also has a (different) mottled pattern in CHIRP climatology. This needs to be addressed before offering CHIRPS data or CHIRP-based data products over ocean. | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa & North & Central America; Marty Landsfeld, South America and regional stats; Libby White, East Asia and Oceania; Sari Blakeley, Africa & Eurasia; Will Turner, Africa | ||
+ | |||
+ | ===June 2017=== | ||
+ | |||
+ | '''Ethiopia''': | ||
+ | Inclusion of stations enhanced the magnitude of June rainfall anomalies in some areas, compared to satellite-based estimates from CHIRP. Across Oromia and central Ethiopia anomalies increased from ~ -20 mm (in CHIRP) to ~-50 to -70 mm (in CHIRPS). In northwestern highlands area, including the stations led to the extension of anomalously wet conditions from east Sudan into and across the NW highlands of Ethiopia. | ||
+ | |||
+ | '''West Africa''': | ||
+ | CHIRPS shows there was a good start to the JJAS rainfall season, based anomalously wet conditions in the June data. In regard to the positive rainfall anomalies, stations and satellite-based estimate (CHIRP) were in general agreement across Gulf of Guinea region; stations added information in Senegal, Burkina Faso, and Niger. | ||
+ | |||
+ | '''Senegal''' | ||
+ | In Senegal, there was evidence of high rainfall in the interior (near Tambacounda) through ANACIM’s rainfall page (http://www.anacim.sn/ and http://www.anacim.sn/meteorologie/produits-du-gtp/). | ||
+ | |||
+ | '''Madagascar''': | ||
+ | Madagascar has some very high rainfall amounts along the eastern coast. There is elevated rainfall along this zone in the CHPclim, and two stations nearby with high rainfall amounts probably contributed to the overall high rainfall along the eastern coast. To note- this data should be used with caution. | ||
+ | |||
+ | '''Georgia (country)''': | ||
+ | Very high rainfall has occurred in southern Russia along the border with Georgia. There are news articles supporting above average rainfall in Georgia here (http://www.bbc.com/news/world-europe-33125879). | ||
+ | |||
+ | '''Central Kalimantan, Indonesia''': Oddly low station (150.8 mm) among higher satellite and other station readings (~200-400 mm), but could be due to Geography. Station was put on watchlist but not removed from CHIRPS. | ||
+ | |||
+ | '''Jakarta, Indonesia''': Values in CHIRPS much higher than CHIRP - station itself did not seem to have unreasonable values, but because it was counted twice it seemed to be influencing the calculations to an unreasonable degree. The station was removed. | ||
+ | |||
+ | '''10 stations removed, 15 added to watchlist''' Also, the need for an improvement in the CHIRPS algorithm was highlighted by a case in Rwanda where a station report was double-counted (and that station happened to have a bad value). Station was removed and issues was noted with data curator. | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa & North & Central America; Marty Landsfeld, South America and regional stats; Libby White, East Asia and Oceania; Sari Blakeley, Africa & Eurasia; Will Turner, Africa | ||
+ | |||
+ | ===May 2017=== | ||
+ | |||
+ | '''SouthEast Asia:''' | ||
+ | Thailand, Cambodia, Southern Vietnam and Southern Laos as well as Sumatra and Indonesia are wetter than usual by 100 mm or more. | ||
+ | Northern Vietnam, Taiwan, West Coast of Myanmar and the Chinese provinces of GuangDong, Fujian and Jiangxi are dryer than usual by 100 mm or more. | ||
+ | |||
+ | '''Australia:''' | ||
+ | |||
+ | '''Southern coastal Angola:''' SASCAL stations report above average rainfall, with totals of 20-60mm. | ||
+ | |||
+ | '''Tanzania:''' As part of an above average rainfall signal along coastal TZ and SE Kenya in May 2017, a GTS station in Zanibar reports 638 mm. In terms of standardized anomaly at a station (z-score of 3.2), this is one of most extreme reports of global stations. Something also to note is that there are some extremely large values in CHIRPS (>1000 mm) in this area. CHIRPS anomalies are mainly 200-300 mm above average, but there are a few pixels with anomalies 500-900 mm. They are a product of the algorithm, as CHIRP rainfall totals are around 600-800 mm and anomalies are 300-400 mm. | ||
+ | |||
+ | '''East Africa, Lake Victoria area:''' High rainfall values- from 200-460 mm reported by 4 stations. Several others nearby also report positive anomalies. | ||
+ | |||
+ | '''Niger, Chad, Sudan:''' Data artifacts in northern parts of country. These are from the CHIRPS climatology, CHPclim. New TAMSAT v3 data also has them because they also use CHPclim as their climatology. Artifacts previously noted in this wiki. Needs attention in next version of CHIRPS/CHPclim. | ||
+ | |||
+ | '''Kenya:''' A bad station value at a GCHN-v2 station in Garissa was identified and removed from CHIRPS. It was identified using a report of MAM 2017 rainfall from the [http://www.meteo.go.ke/pdf/seasonal.pdf Kenyan Met Agency]. A neighboring GTS station reported 13 mm, which is more realistic. | ||
+ | |||
+ | '''Argentina:''' Above average rainfall in NE (see Brazil entry). In western part of Argentina CHIRPS data has a visible north-south artifact line. | ||
+ | |||
+ | '''Brazil:''' In southern Brazil and NE Argentina CHIRPS is correctly showing an area with concentrated high rainfall values. This is based on comparison to Argentina Met Agency maps. In northern Brazil and eastern Columbia, CHIRPS shows a widespread below average rainfall signal. This comes from ~11 stations and in part of the anomalous area, CHIRP. Circular data artifacts are seen in southern Brazil. These artifacts were previously noted in this wiki. Needs attention in next version of CHIRPS. | ||
+ | |||
+ | '''N. America:''' Stations had a large effects in the midwest and eastern seaboard. CHIRP did not do well in these regions but the station adjustments corrected that. | ||
+ | |||
+ | '''Italy''' removed a false zero in south central region. | ||
+ | |||
+ | '''Regional Statistics checks''' The [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.africa.stats.2017.05.png Africa] region contained a new high for the maximum value in the region of 1716.9 on the island of Zanzibar. | ||
+ | [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.global.stats.2017.05.png Globally], a new high for the maximum value of nearly 2400 was detected near Chichi-jima Island south of Japan. | ||
+ | |||
+ | ===March 2017=== | ||
+ | |||
+ | '''Madagascar''': Northern Madagascar has highly above average rainfall in March CHIRPS, with anomalies on the order of 200 mm to 500 mm and March totals up to 900 mm (35"). This information comes from stations and the satellite-based CHIRP. In the first week of March a strong tropical cyclone named Enawo made landfall in northern Madagascar. Enawo is the strongest cyclone to make landfall in Madagascar in 13 years. It was equivalent to a Category 4 hurricane. [https://weather.com/storms/hurricane/news/tropical-cyclone-enawo-madagascar-forecast 20,000 homes were destroyed]. | ||
+ | |||
+ | '''Angola''': CHIRPS shows below average rainfall for large area in central western Angola. This information is coming from one station (which has a reasonable rain value) and also CHIRP. The satellite-based products ARC2 and CHIRP both show below average rainfall in that area. According to CHPclim this area typically gets 200-250 mm in March (ARC2 shows 150-200 mm in its climatology). The station and CHIRPS report 100-130 mm in the area. Persistent dryness has been an outgoing issue in this part of Angola for the October to May season, with [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Dec2016-Feb2017_af_anom.gif suppressed rainfall since December]. | ||
+ | |||
+ | '''East Africa''': CHIRPS shows below normal rainfall across much of this region: In Kenya, northern Tanzania, southern Somalia, and southern Ethiopia. This indicates a poor start to the March to May rainy season. The negative anomalies are supported by 40+ stations (many of these are in Somalia), by CHIRP, and also by [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Mar2017-Mar2017_af_anom.gif ARC2]. Concern for the season due to the poor start is detailed in the [http://blog.chg.ucsb.edu/?p=194 CHC blog]. | ||
+ | |||
+ | '''Northern Somalia''': An area with one station reporting 41 mm rain that is near stations reporting 0 mm rain was examined. Support for the idea that this mix actually occurred came CHIRP and RFE2, which showed that satellites also picked up on some rainfall there. Should be noted that CHPclim shows this area is typically wetter than surroundings. | ||
+ | |||
+ | '''Honduras''': An area of northeastern Honduras, near San Pedro Sula, has three GSOD stations that report above average rainfall. One of those has a very high rain total of 411 mm, another reports 206 mm. Together, and with input from CHIRP, they are responsible for above average rainfall in CHIRPS in this area. The anomaly at the very wet station was ~300mm. Given such a large magnitude wet anomaly, and convergence from these stations, we expected to find support for a wet event in other data sources. CHIRP shows a small wet anomaly. Otherwise, no support comes from PERSIANN or [http://www.cpc.ncep.noaa.gov/products/international/cmorph/cmorph_Mar2017-Mar2017_car_anom.gif CMORPH rainfall] products. No news reports were found online. These stations seem to report on a semi-monthly basis, rather than monthly, and tend to report high rainfall values. We retained these stations in CHIRPS, but added them to the watchlist for future review. | ||
+ | |||
+ | '''Australia''': Despite [record breaking rainfall in March http://www.news.com.au/technology/environment/the-wettest-march-in-recent-history-is-on-the-cards-as-sydney-clocks-up-16-rainy-days-and-more-than-a-week-to-go/news-story/988409de59d01a92197439139509d007], including a particularly intense [cyclone https://www.washingtonpost.com/news/capital-weather-gang/wp/2017/03/28/cyclone-debbie-roars-ashore-in-australia-with-160-mph-wind-gusts-and-30-inches-of-rain/?utm_term=.0603b199256a], there were a few very low/zero value stations that we tossed out. | ||
+ | |||
+ | '''China''': Heilongjian and Altay China had several stations that were showing unfeasible high values (300mm+) in relatively dry regions. No evidence of localized weather events could be found to support them, so they were tossed out. Similarly, Jiangxi had some suspiciously low values (~40mm), especially when viewed in anomaly, so they were tossed out as well. | ||
+ | |||
+ | '''Argentina''' contained two stations that were outliers, compared to their neighbors, and were removed. One GSOD station had a z-score of 5.28. | ||
+ | |||
+ | '''South America''' had the highest mean CHIRPS value for March in our records. The [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2017.03.png CHIRPS Mean regional statistics] shows the highest mean value on record and by far the highest Maximum CHIRPS value on record. We investigated these values and found the there were record rains reported along the Peru/Ecuador border by [https://www.theatlantic.com/photo/2017/03/peru-suffers-worst-flooding-in-decades/520146 The Atlantic] and [http://earth-chronicles.com/natural-catastrophe/flooding-in-ecuador.html Earth Chronicles] websites. | ||
+ | |||
+ | '''19 stations removed, 25 added to watchlist''' 19 stations were removed from the preliminary version of CHIRPS due to being identified as unrealistic values during the Rchecks process. | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa, Central America; Marty Landsfeld, North, South & Central America; Libby White, East Asia and Oceania; Sari Blakeley Africa & Eurasia'' | ||
+ | |||
+ | ===February 2017=== | ||
+ | |||
+ | '''South Africa''' Two very wet stations in northeast (near 24.5S, 30E) attracted our attention. The wetter was more than 350mm above average with a value of ~ 550mm. These are on the eastern edge of mountain range. Conditions were wetter than normal across the region. Due to these factors, the station values were deemed ok and retained in CHIRPS. If these station are indeed accurate, they are valuable to have in CHIRPS because captures the impact of orographic rainfall enhancement in the region. Will keep an eye on them going forward. | ||
+ | |||
+ | '''Tanzania''' A GHCN station in Tabora (central TZ) was removed. It reported ~15mm and seemed to be responsible for surrounding negative anomalies in CHIRPS. In comparison, CHIRP doesn’t show a negative anomaly- it shows near average in the area; RFE2 shows above average. ARC2 daily time series shows rain for many days in February (~100mm total). | ||
+ | |||
+ | '''Northern Mozambique''' Large negative anomalies. Station and CHIRP in agreement. Drought has affected this region for most of the past several months [ftp://ftp.cpc.ncep.noaa.gov/fews/threats/afrhaz20170316.pdf]. | ||
+ | |||
+ | '''Australia''' Very wet February in western Australia. Stations and CHIRP show the extreme conditions. In Perth, Feb 2017 was the wettest in decades at many sites. According to [http://www.bom.gov.au/climate/current/month/wa/perth.shtml Australia's BoM]: Monthly rainfall totals were in the 80-140 mm range across Perth, and were more than five times higher than normal. Perth Metro's monthly total was the second-highest February rainfall total on record at the site and the wettest for 62 years, since the record high of 166.3 mm in February 1955. | ||
+ | |||
+ | '''California, USA''' CHIRPS shows the extreme rainfall that helped to end the drought for a majority of California [http://www.latimes.com/local/lanow/la-me-drought-gone-20170223-story.html]. Atmospheric river events in February brought flooding, landslides, and damaging winds. | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa, North America, East Asia and Oceania; Marty Landsfeld, Africa, South & Central America; Sari Blakeley Africa & Eurasia'' | ||
+ | |||
+ | ===January 2017=== | ||
+ | |||
+ | '''Southern-Eastern Africa rainfall dipole continues''' January CHIRPS shows the anomalous wet (dry) conditions in southern (eastern) Africa that persisted since November. The dipole was most prevalent in December and January. January CHIRPS shows rainfall 150mm+ above average in Botswana, South Africa, southern Malawi, Zimbabwe, and Mozambique, with the largest anomalies (250mm-400mm) in eastern Zimbabwe/central Mozambique. Deadly flooding occurred in Limpopo and Mpumalanga (South Africa) [http://floodlist.com/africa/south-africa-floods-limpopo-mpumalanga-january-2017]. CHIRPS shows northern Mozambique and Madagascar with January totals that are 100-250mm below average. Rainfall was more than 2.5 standard deviations from the norm in some of these areas. In Tanzania rains were 50-75mm below average across much of the country. | ||
+ | |||
+ | '''Kenya''' Rchecks identified three stations that reported questionable values in western and southern Kenya, and these were not included in CHIRPS final. Two appeared to be false zeros, and one appeared to have an erroneous high value that would have influenced data near Nairobi and over Mt. Kilimanjaro in Tanzania. | ||
+ | |||
+ | '''Ethiopia''' Many near-zero value stations earned a closer look. They seemed reasonable given January is a relatively dry month in most areas. In SW Ethiopia, where there typically is rain, CHIRPS and stations showed agreement with CHIRP and RFE2 about the area being below average by ~20mm in SNNPR. | ||
+ | |||
+ | '''Western Sahara''' On the coast of Western Sahara there are several artifacts that must be a part of CHPCLIM. | ||
+ | |||
+ | '''Thailand''' Southern Thailand's extreme wet January rainfall was one of the most extreme locations globally in the CHIRPS domain (50S to 50N). Five Thailand stations had rain reports that were more than 2.7 standard deviations from the norm. These stations measured 500mm-800mm (~20"-30") rainfall. CHIRPS shows that some areas received 500mm above average rains. Extreme values in CHIRPS are corroborated by NASA GPM data [http://floodlist.com/asia/thailand-nasa-rainfall-totals-january-2017]. In mid January, 43 people had been killed and 1.6 million people were affected [http://floodlist.com/asia/thailand-south-floods-43-dead-january-2017]. | ||
+ | |||
+ | '''Pakistan''' Unusually high rainfall amounts in Pakistan were observed in January, in line with reporting of floods and high snowfall in the mountains.The Pakistan government has requested aid from the Pakistan Red Crescent Society. http://reliefweb.int/disaster/fl-2017-000017-pak | ||
+ | |||
+ | '''California, USA''' CHIRPS shows above average rainfall across the state, with wettest anomalies in the northern Coast Ranges and Sierra Nevada mountains. Much was attributed to [http://www.latimes.com/local/california/la-me-live-winter-weather-california-here-s-how-california-went-from-drought-1483832931-htmlstory.html] a series of atmospheric river storm systems [https://weather.com/science/weather-explainers/news/atmospheric-river-explained]. The wettest station along the central coast was in Big Sur, which received 19" rain, as was forecast [http://www.montereyherald.com/article/NF/20170103/NEWS/170109944]. | ||
+ | |||
+ | '''Queensland, Australia''' One zero value CHCNd station surrounded by higher value stations was tossed out. | ||
+ | |||
+ | '''Taiwan''' One zero value fGSOD station among stations reporting higher values was tossed out. | ||
+ | |||
+ | '''21 stations removed, 30 to watchlist''' Rchecks examination identified these stations as having values that were not accurate, based on careful comparison to other data, neighbor stations, and to reports. Past reports from these stations were also incorporated in decisions. See the watchlist for more details. [https://docs.google.com/spreadsheets/d/1GK86wSQdJwMp6Sa-ySvOM7fP_StVG0xmVg9Iv_b_gxk/edit?ts=5716aea2#gid=0] | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa, North & Central America; Marty Landsfeld, Africa, North, South & Central America; Libby White, East Asia and Oceania; Sari Blakeley Africa & Eurasia'' | ||
+ | |||
+ | ===December 2016=== | ||
+ | |||
+ | '''Tanzania, northern Mozambique, northern Zambia, Madagascar, southern Kenya and Uganda''': CHIRPS shows drier than normal conditions across this large region. Largest deficits are 100-150 mm. The CHIRPS anomalies come from reports by approximately 20 stations and also from the CHIRP satellite signal. Central/southern Tanzania and northern Mozambique were the epicenter of deficits according to CHIRP. The combined influence of stations and satellite resulted in December rainfall estimates that are 1.5 to 2 standard deviations below average across the region. | ||
+ | |||
+ | '''Zimbabwe, east Botswana, southern Mozambique, northeast South Africa''': Above average rainfall in these areas. Multiple products (CHIRPS, ARC2, TAMSAT, CHIRP) are in agreement about this dipole pattern of rainfall [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2016/Rainfall%20dipole.png]. Stations in Zimbabwe and South Africa were especially scrutinized because of high variability. Several stations in this region, and the Kenya/Tanzania/Zambia region, were removed due to extreme values. See our [https://docs.google.com/spreadsheets/d/1GK86wSQdJwMp6Sa-ySvOM7fP_StVG0xmVg9Iv_b_gxk/edit?ts=5716aea2#gid=0 station watchlist] for more information. | ||
+ | |||
+ | '''Ethiopia''': A GHCN-v2 station that reported extreme wet value was removed (36.8E, 7.7N) | ||
+ | |||
+ | '''Nigeria''': Removed station with strange value at a station (=110204); an error from new station source (Kukua) that made it past pre processing. | ||
+ | |||
+ | '''Nicaragua, Honduras''': Large wet anomaly along eastern coast, with CHIRPS showing show areas recieved 650mm (200 mm above average). A feature from CHIRP, as there are no stations reporting in area. The PERSIANNE-CCS precipitation dataset also shows this wet feature. | ||
+ | |||
+ | '''Argentina''': Three GCHN-v2 stations in different locations report the same value (267 mm). Curious and questionable. Added these to station watchlist to keep an eye on in future; based on previous months, there are no known issues at these stations. | ||
+ | |||
+ | '''Australia''': A few stations with suspicious zero values were thrown out in Western Australia and Queensland. | ||
+ | |||
+ | '''Kochi, India''': Suspicious zero value station was removed. | ||
+ | |||
+ | '''Various CHPclim artifacts''': CHIRPS is being repeatedly affected by the following December CHPclim problems: Extreme value on Canary Island, striping in western Sahara, small wet area in Algeria near 1E, 29N creates strange symbol-like feature in CHIRPS. Also a large artifact in Egypt (a 1.5 degree radius splotch of low values). | ||
+ | |||
+ | ''Contributors: Laura Harrison, Africa & Central America; Marty Landsfeld, Africa, North, South & Central America; Libby White, East Asia and Oceania; Sari Blakeley Africa & Eurasia'' | ||
+ | |||
+ | ===November 2016=== | ||
+ | |||
+ | '''NW Argentina''': Area is generally dry except for an area of high precipitation around the village of San Miguel de Tucuman. A newspaper report from November 7th notes that a soccer/futbol game was canceled because there was water on the field.[http://lgdeportiva.lagaceta.com.ar/nota/706624/deportes/debido-fuertes-lluvias-se-suspendio-partido-atletico.html] | ||
+ | |||
+ | '''Italy''': In north-western Italy there is a wet anomaly, and then a dry anomaly to the east; various reports back this up [https://watchers.news/2016/11/24/italy-flood-liguria-piedmont-november-2016/ ] [http://www.aljazeera.com/news/2016/11/heavy-rain-floods-northern-italy-161125092401356.html ] [https://www.wunderground.com/history/airport/LIMS/2016/11/12/MonthlyCalendar.html] | ||
+ | |||
+ | '''Czech Republic''': There is a dry anomaly in Ceske Budejovice, checks out according to sources [https://www.wunderground.com/history/airport/LOWL/2016/11/21/MonthlyHistory.html?req_city=Ceske%20Budejovice&req_state=&req_statename=Czech%20Republic&reqdb.zip=00000&reqdb.magic=4&reqdb.wmo=11546] | ||
+ | |||
+ | '''Alanya, Turkey''': Dry along southern coast [https://www.wunderground.com/history/airport/LTFG/2016/11/21/MonthlyHistory.html?req_city=Alanya&req_state=&req_statename=Turkey&reqdb.zip=00000&reqdb.magic=1&reqdb.wmo=17310] | ||
+ | |||
+ | '''Iran''': The east tends to be dry, but there was a station that showed an increase in 14 cm of rain (small amount); this showed up as an extremely positive z-score. | ||
+ | |||
+ | '''India''': Southern India (into Sri Lanka) is showing up as extrememly dry, which is correct and backed up by sources indicating the monsoon season has had few rain days and ran a large deficit by the end of the month [http://www.skymetweather.com/content/weather-news-and-analysis/performance-of-northeast-monsoon-rainfall-in-india-2015/] [http://www.accuweather.com/en/weather-news/india-tamil-nadu-chennai-flooding-continues-wet-november/53943597] [http://www.skymetweather.com/content/weather-news-and-analysis/chennai-rains-remain-over-50-percent-deficient-despite-three-cyclones/][http://www.newindianexpress.com/states/tamil-nadu/2016/nov/24/no-sign-of-rain-is-chennai-staring-at-poorest-monsoon-1542022.html] | ||
+ | |||
+ | |||
+ | ''Contributors: Emily Williams, Eurasia; Marty Landsfeld, North & Central America; Libby White, East Asia and Oceania'' | ||
+ | |||
+ | ===October 2016=== | ||
+ | |||
+ | '''Somalia and east African horn''': CHIRPS and stations show expansive areas of below average rainfall in October. Areas of largest deficits are in southern Somalia (more than 100 mm below average) and central Kenya, near Meru (more than 200mm below average). The deficits are highly concerning in Somalia as the October is generally one of the wettest months of a very short cropping season. | ||
+ | |||
+ | '''Gabon''': CHIRP and 3 stations in agreement about below average rainfall in western Gabon. | ||
+ | |||
+ | '''Sudan''': No stations are reporting to CHIRPS in Sudan this month. The number of stations reporting in this country seem to oscillate between either 0 or around 10. | ||
+ | |||
+ | '''Southern India''': CHIRPS shows deficits of 100-200 mm in southern India. The data correctly indicate widespread drought conditions, which have been reported to be negatively impacting water resources for agriculture and other uses. In Kerala state, "most of the water reservoirs across the state have recorded a water deficit of 50 per cent. The South West monsoon has been deficit by 34% while the North East monsoon is expected to be deficit by 69%." [http://www.ndtv.com/world-news/drought-in-kerala-reservoirs-half-empty-deficit-rainfall-1587110 news report] | ||
+ | |||
+ | '''Indonesia''': Stations in the region are generally high value and backed up by weather reports; however, a few stations showed great variation with their neighbors, some over 300mm higher. | ||
+ | |||
+ | '''China''': Several stations around Qinzhen and Shenzhen showed ~300mm higher values than their neighboring stations. | ||
+ | |||
+ | '''Yonaguni, Japan''': One station shows a value ~250mm higher than its neighboring values. | ||
+ | |||
+ | ''Contributors: Marty Landsfeld, North and Central America and Africa; Libby White, Oceania and East Asia; Seth Peterson, South America and Africa; Sari Blakeley, Europe; Laura Harrison, Africa and Oceania'' | ||
+ | |||
+ | ===September 2016=== | ||
+ | |||
+ | '''New Zealand''': the pattern in CHIRPs of North Island wet, South Island dry is correct [http://www.stuff.co.nz/national/84859833/more-thunder-and-lightning-on-the-way-bursts-of-heavy-rain-and-westerlies] | ||
+ | |||
+ | '''Ethiopia''': the pattern in CHIRPs of the SW part of the country being dry is correct [http://reliefweb.int/report/ethiopia/ethiopia-key-message-update-september-2016] | ||
+ | |||
+ | '''Brazil''': southern Brazil was indeed dry in September [https://www.dtnpf.com/agriculture/web/ag/perspectives/blogs/south-america-calling/blog-post/2016/09/26/brazilian-soybean-season-starts-slow] | ||
+ | |||
+ | ''Contributors: Marty Landsfeld, Europe and West Asia; Seth Peterson, South America, Australia, NZ, & Africa; Sari Blakeley, North America & Africa'' | ||
+ | |||
+ | ===August 2016=== | ||
+ | |||
+ | '''Japan''': A few stations were able to capture the heavy rains on Japan's east coast better than CHIRP alone (~400mm - 500mm as opposed to CHIRP's less than 200mm on average). [http://www.japantimes.co.jp/news/2016/08/16/national/heavy-rain-forecast-typhoon-threatens-kanto-tohoku-hokkaido/#.V_U6quArKHs] [http://www.straitstimes.com/asia/east-asia/japan-braces-for-heavy-rain-and-landslides-as-2-typhoons-approach] | ||
+ | |||
+ | '''Shandong, China''': Two stations reported nearly 500mm in rain, while surrounding stations and CHIRP report less than 200mm (on average). Weather reports do not indicate high levels of localized rain in that region. | ||
+ | |||
+ | '''Hainan, China''': [http://news.xinhuanet.com/english/2016-08/18/c_135611889.htm Typhoon Dianmu] seems to be responsible for the very high (847.59mm) precipitation recorded, though CHIRP did not capture this rainfall as well (reported between ~200mm to ~500mm). | ||
+ | |||
+ | ''Contributors: Marty Landsfeld, Europe and West Asia; Libby White, Oceania & East Asia; Seth Peterson, South America & Africa; Sari Blakeley, North America & Africa'' | ||
+ | |||
+ | ===July 2016=== | ||
+ | |||
+ | '''Somalia''': Many stations reported zero or near-zero values, while CHIRP estimated non-trivial values but it was decided that since CHIRP will over-estimate low values in these conditions that the station data probably was correct. Having viewed July estimates of ARC2, the decision was supported. | ||
+ | |||
+ | '''Madagascar''': Discontinuous patterns of precipitation, especially anomaly and z-score values, were noted but Pete explained how this is part of the climatology and will hopefully be fixed in the next version of CHIRPS. | ||
+ | |||
+ | '''Multiple countries''': 17 stations with suspect values were added to the watch list. It was determined that their effects were minimal so were not removed to create another version. | ||
+ | |||
+ | '''Central America''': Good overall agreement with ARC2 product. It was noted that there are only 5 stations for all of Honduras, Nicaragua, El Salvador & Panama which unfortunately is typical. | ||
+ | |||
+ | '''Brazil''': Many zero values new Sao Paulo/Rio area that generate "dimples" in the product but viewing precipitation map from INMET website confirmed dryness. | ||
+ | |||
+ | '''Mexico''': Station data reduced CHIRP values south of Mexico City and near Santa Cruz. | ||
+ | |||
+ | '''China''': Stations in Hubei, Shanghai, and Shanxi picked up on heavy rains not present in CHIRP [http://www.dailymail.co.uk/news/peoplesdaily/article-3673259/Football-stadium-giant-bathtub-heavy-rain-leaves-flooded-China.html] [http://www.reuters.com/article/us-china-floods-idUSKCN103074] | ||
+ | |||
+ | '''''Time Series Statistics Plots''''': All regions within normal ranges with the exception of [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_africa.stats.2016.07.png southern Africa] which tied CHIRPS Maximum value. It was a very localized occurrence and accepted. | ||
+ | |||
+ | ''Contributors: Marty Landsfeld, North America and Africa; Libby White, Oceania & Asia; Seth Peterson, South America & Africa; Sari Blakeley, Europe & Africa'' | ||
+ | |||
+ | ===June 2016=== | ||
+ | |||
+ | '''Colombia''': Colombia was generally drier before stations added, stations made it wetter. One station (20758) led to a z-score about -4.5 (value of 30mm, where surrounding area was 200-300mm), and was therefore temporarily removed. | ||
+ | |||
+ | '''Guyana''': A station (205606) reported 1380.6mm of rain on the coast; while there were a couple of reports of flooding [http://www.stabroeknews.com/2016/media/photos/06/21/efforts-continue-bring-flood-relief-region-5/], none matched the magnitude of the station, and was therefore temporarily removed. | ||
+ | |||
+ | '''Brazil''': Several stations (205639, 205664, 205655, 205651, 205645) all had values of over 1000mm in climatologically drier areas. All were removed. A station in SE Brazil (285717) had a high rainfall value in a climatologically wet area, creating a wet “bubble” in anomaly space, and was temporarily removed. | ||
+ | |||
+ | '''Southern Chile''': Dry anomalies/z-scores, which match up with TRMM. | ||
+ | |||
+ | '''Costa Rica''': A station in Costa Rica/Nicaragua shows a high positive anomaly, where CHIRP and TRMM shows negative. Weather Underground reports 242mm [https://www.wunderground.com/history/airport/MRLB/2016/6/29/WeeklyHistory.html?req_city=&req_state=&req_statename=&reqdb.zip=&reqdb.magic=&reqdb.wmo=] , matching the CHIRP value but not the station value. Therefore is temporarily removed. | ||
+ | |||
+ | '''Mexico''': Tropical storm Danielle caused flooding, shows up in CHIRPS well [http://www.accuweather.com/en/weather-news/mexico-tropical-development/58227788] ; Mexico City showed up with z-score of 4.34. | ||
+ | |||
+ | '''United States''': In California and Nevada, the z-scores for CHIRP are high for slightly high anomalies, explained by their having very dry climatologies. In West Virginia heavy rain showed up in CHIRPS, backed up by national forest alert [http://www.fs.usda.gov/alerts/gwj/alerts-notices] | ||
+ | |||
+ | '''Indonesia''': There was heavy rain on the island of Java, leading to flooding [http://www.reuters.com/article/us-indonesia-floods-idUSKCN0Z60TZ], as well as on Sulwesi. This matches with reports [http://floodlist.com/asia/indonesia-floods-landslides-north-sulawesi-june-2016]. | ||
+ | |||
+ | '''Taiwan''': A station (203670) off the northern coast of the island reported 1440.40mm, while another station (203682) on the island reported 1383.09. Super Typhoon Nepartak came through in June, reportedly dumping 154 mm in one day [http://www.taipeitimes.com/News/front/archives/2016/06/03/2003647758] . TRMM reports high anomalies in the area (300-500mm extra) [http://www.cpc.ncep.noaa.gov/products/international/trmm/trmm_Jun2016-Jun2016_sea_anom.gif], but not nearly as high as the station values. | ||
+ | |||
+ | '''Oceania''': New South Wales was hit with an intense storm system, ranging from Brisbane to Sydney and even reaching Tasmania. [http://www.abc.net.au/news/2016-06-04/queensland-flooding-hits-brisbane-as-extreme-weather-moves-south/7476794] [https://www.theguardian.com/australia-news/2016/jun/05/wild-weather-thousands-of-calls-for-help-as-storm-batters-new-south-wales] | ||
+ | |||
+ | '''Ethiopia''': New stations! The addition this month is ~25 stations from Ethiopia’s National Meteorology Agency. The stations had particular influence on CHIRPS in the northern Oromia region. Here, CHIRP estimated below average rainfall but the station observations showed the deficiency was larger in magnitude—at three stations June anomalies were 116-130 mm below average. Across climatologically wet parts of Ethiopia, the final CHIRPS product shows N/S oriented swaths of above average rainfall along the Sudan border region, below average June rainfall along western highland areas (anomalies -30mm to -90 mm), and average to slightly above average June rainfall in eastern highlands areas. | ||
+ | |||
+ | '''Guinea/Sierra Leone''': The GSOD station 276516 (Data=688.59 mm, CHPclim ~ 350 mm) at Conakry, Guinea was checked due to its large positive rainfall anomaly. It was deemed ok to retain in CHIRPS based on convergence with NOAA’s ARC2 data, which also shows above average rainfall in the Guinea and Sierra Leone area in June. Compared to ARC2, CHIRPS shows smaller magnitude anomalies, which range from 50-200mm. ARC2 shows 300-500mm anomalies. | ||
+ | |||
+ | '''Madagascar''': Some visible block patterns in CHIRPS data. These are also seen in CHIRPS Prelim and CHIRP. Note that there is blockiness in CHIRPS data in many low rainfall areas in the general region, but these stand out in Madagascar because of some high rainfall values mixed in. | ||
+ | |||
+ | '''Europe''': CHIRPS shows above average rainfall in June across large areas of western Europe, southern Europe (excluding Spain, Portugal), and parts of south eastern Europe (especially Romania). In some areas, based on the CHIRPS standardized anomalies (z-score maps), the magnitude of rain received in June 2016 classified as 1 in 7 year to 1 in 50 year events. Photos and descriptions of some of the damage can be seen here: [http://strangesounds.org/2016/06/floods-apocalypse-world-usa-mexico-russia-china-france-germany-belgium-ukraine-romania-photo-video.html] | ||
+ | |||
+ | '''China''': Heavy rainfall and reports of flooding in southern and eastern China [http://floodlist.com/asia/china-15-dead-10-missing-floods-continue-south ], plus the reports from >50 stations substantiate the above average rainfall shown in CHIRPS (100-200mm anomalies). | ||
+ | |||
+ | '''Japan'''. CHIRPS shows positive rainfall anomalies of 50-200mm in southern Japan. These are substantiated by ~30 stations and Floodlist reports of deadly floods and landslides. On June 21st for example, Kosa in Kumamoto prefecture received over 180 mm rain in two hours: [http://floodlist.com/asia/japan-deadly-floods-landslides-kumamoto-june-2016] | ||
+ | |||
+ | '''**Due to Rchecks**''' 26 station reports were removed from the final June 2016 CHIRPS product. Please see the R Checks STATION WATCHLIST for more information (under Helpful Links) | ||
+ | |||
+ | ''Contributors: Emily Williams, Americas & some of Oceania; Libby White, Oceania; Laura Harrison, Africa Europe & Asia'' | ||
+ | |||
+ | ===May 2016=== | ||
+ | |||
+ | '''Columbia''' Comparing CHIRP and CHIRPS, CHIRPS has more negative anomalies on the western coast and positive anomalies on the eastern border. There is a station near the Panama/Columbia border with a low value which drives the area down, but it’s confirmed in a separate precipitation report [https://www.wunderground.com/history/airport/SKLC/2016/5/25/MonthlyHistory.html?&reqdb.zip=&reqdb.magic=&reqdb.wmo= ]. | ||
+ | |||
+ | '''Brazil''' There is a station in the Southeast with a very high value (1107.0) that is surrounded by low value stations. CHIRP shows low rainfall values for that area. The addition of the station led to a circular artifact in the area, and was subsequently removed. It was a GTS station, with seq-num of 205708. | ||
+ | |||
+ | There are two more stations in Southern Brazil also creating circular artifacts; however, their values are not high enough to warrant removal. They have been added to the watchlist (205722). | ||
+ | |||
+ | '''Central America''' It is very, very dry with a historical low maximum temperature, however, nothing looks out of place [http://www.cpc.ncep.noaa.gov/products/international/trmm/trmm_May2016-May2016_car_anom.gif]. | ||
+ | |||
+ | '''Liberia''' The CHIRP and CHIRPS products both show dry anomalies inland and wet anomalies along the coast; however RFE and ARC2 [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_90day_ptts_Monrovia_Liberia.gif] show the opposite. After adding up precipitation values from a site (not verified for accuracy)[ http://www.accuweather.com/en/lr/monrovia/361788/may-weather/361788?monyr=5/1/2016&view=table], the values reached 84 mm, which backs up the ARC2 story. However, there were some flooding reports for Monrovia [http://allafrica.com/stories/201605191107.html ] [http://liberianobserver.com/news/paynesville-monrovia-flooded-wednesday ]. Overall, it is unclear as to whether or not CHIRPS is right on this one so we should watch trends in Liberia in the future. | ||
+ | |||
+ | |||
+ | ''Contributors: Emily Williams, Liberia & Central & South America; '' | ||
+ | |||
+ | ===April 2016=== | ||
+ | |||
+ | '''Central America''' Dry along Eastern coast of Costa Rica and Panama. Station on S. coast of Panama shows anomalously high value but seems to match with TRMM [http://www.cpc.ncep.noaa.gov/products/international/trmm/trmm_Apr2016-Apr2016_car_anom.gif]. Weather underground report says in April it got 4.59 inches, or 116 mm [https://www.wunderground.com/history/wmo/78795/2016/4/17/MonthlyHistory.html?req_city=Santiago&req_state=&req_statename=Panama&reqdb.zip=00000&reqdb.magic=1&reqdb.wmo=78795]. Didn’t have visual impact on CHIRPS so can leave it. | ||
+ | |||
+ | '''United States''' April was the record wettest in southern plains, and the record warmest in northwest; [https://weather.com/news/climate/news/record-warm-wet-april-2016];CHIRPS shows this very clearly. Station near Wichita Falls, Texas was permanently thrown out as it showed a super dry anomaly in the middle of very wet anomalies, and has historically given anomalously low values [http://w2.weather.gov/climate/getclimate.php?date=&wfo=OUN&sid=SPS&pil=CF6&recent=yes&specdate=2016-04-30+11%3A11%3A11]. Station near Jarbidge, Nevada reported a high positive anomaly (138.0 mm) where adding up the daily rain amounts gives us 56mm [https://weather.com/weather/monthly/l/USNV0046:1:US]. Topographically, however, it could make sense, so it goes on the watchlist but isn’t thrown out. | ||
+ | |||
+ | '''Tanzania, south eastern Kenya, Uganda, South Sudan''' | ||
+ | CHIRPS shows above average rainfall over large areas of the region, with April values 100-200 mm above average. Kilimanjaro (TZ) shows 400 mm above average. CHIRP and ~15 stations contributed to these data. Extreme rainfall was reported in many of these areas. Some of the most damaging events were in [http://floodlist.com/africa/kenya-floods-building-collapses-huruma-nairobi Nairobi] and [http://floodlist.com/africa/kenya-floods-mombasa-april-2016 Mombasa] (KN), [http://floodlist.com/africa/uganda-1000-displaced-floods-kasese-kampala Kasese and Kampala] (UG), Mbeya, Zanzibar, [http://floodlist.com/africa/tanzania-floods-mbeya-zanzibar-kilimanjaro Kilimanjaro], and [http://floodlist.com/africa/tanzania-floods-morogoro-region-leave-5-dead-april-2016 Morogoro] (TZ). | ||
+ | |||
+ | '''Angola''' There is a station on the West coast just inland of another station that shows half the value of the coastal one. The station seems to be anomalously low for flooding reports in the area and the values CHIRP assigns to the area. It is on the watchlist. | ||
+ | |||
+ | '''Madagascar''' Tropical cyclone Fantala skirted Madagascar’s northern coast, resulting in the extremely high station value [http://phys.org/news/2016-04-nasa-category-tropical-cyclone-fantala.html]. There is another station on the SE coast that reported a high value where CHIRP reported low values-it is now on the watchlist. | ||
+ | |||
+ | '''Ethiopia''' There is a station in the NW of the country that is reporting a high rainfall value in the middle of very low values; it doesn’t have an impact on the final CHIRPS product, but will go on the watchlist to see what happens next month. | ||
+ | |||
+ | '''Chile''' | ||
+ | Two stations, CHIRP, and CHIRPS final show above average rainfall in the Santiago area. Anomalies are 20-100 mm, which put rainfall in the 95th percentile (2+ standard deviations from the April mean). [http://floodlist.com/america/chile-santiago-floods-landslides-april-2016 Floodlist reported] that heavy rains and floods in Santiago left 2 people dead and 10 missing | ||
+ | |||
+ | '''Southern Brazil, Uruguay, Eastern Argentina''' | ||
+ | CHIRPs final, from support by 30+ stations and CHIRP showed rainfall anomalies of 150-300mm in this region. CHIRPS totals in south Brazil are similar to INMET April accumulations (150-500mm). [http://www.inmet.gov.br/mapas_chuva/2016/04/Prec-Acum-30d_20160401.png Link to report] CHIRP shows a SE-NW oriented swath of heavy rain. The heavy rainfall was associated with several extreme events through the month, with greatest impacts in Uruguay. | ||
+ | [http://floodlist.com/america/argentina-uruguay-floods-april-2016 In early April], Argentina media reports claimed that over 500 mm of rain has fallen in some areas, including Alejandra in Santa Fe, San José de Feliciano in Entre Ríos, in the space of 4 days. Uruguay River rose to concerning levels. | ||
+ | Then [http://floodlist.com/america/uruguay-severe-weather-leaves-7-dead-3000-displaced in mid April], more heavy rain occurred in Uruguay (150-180mm in 24 hours) and was accompanied by a tornado. 7 people died and 3,000+ people were displaced. Continuation of the severe conditions led to more flooding and displacement of 10,000 people. | ||
+ | |||
+ | '''Brazil''' | ||
+ | Below average rainfall for much of the country (exceptions are south and north regions). CHIRPS shows rainfall as 25 to 75mm below average for most areas, with enhanced deficits (up to 150 mm anomalies) in States of Tocantins, Maranho, and Para. This general pattern is similar to the anomalies shown by INMET, Brazil’s Instituto Nacional de Meteorologia: [http://www.inmet.gov.br/webcdp/climatologia/chuva_desv_men/mapas/201604.png Link to map] | ||
+ | |||
+ | '''Australia''' | ||
+ | While mostly dry, there were some moderate rains (more rain that usual - ~10-20 mm more on average) in Western Australia. [http://www.bom.gov.au/climate/drought/drought.shtml] | ||
+ | |||
+ | '''South East Asia''' | ||
+ | Despite an overall drought across South East Asia[http://reliefweb.int/disaster/dr-2015-000180-vnm][http://www.wsj.com/articles/el-nino-wreaks-havoc-across-southeast-asia-1463587502], Papua New Guinea experienced higher than normal rain in the north [http://www.onepng.com/2016/04/heavy-rains-in-aitape-causes-flooding.html]. CHIRPS shows more precipitation in Indonesia (Sulawesi Selatan and Kalimantan Barat) than CHIRP alone, although not significantly above average. | ||
+ | |||
+ | '''Eastern China & Southern Japan''' | ||
+ | Heavy rains in China and Japan are reflected in the CHIRP as well.[http://www.shanghaidaily.com/nation/China-renews-blue-rain-alert/shdaily.shtml][http://www.cctv-america.com/2016/05/16/el-nino-brings-heavy-rain-to-southern-china] | ||
+ | |||
+ | '''Taiwan''' | ||
+ | EWX classifies Taiwan as China (likely due to GAUL) - worth noting that while the PRC would be happy with that classification, Taiwan would not. | ||
+ | |||
+ | '''**Reality Checks update**''' Several station reports were removed from CHIRPS final product for April 2016. A list of these stations can be found on the Station WATCHLIST (link under Helpful Links at top of page) | ||
+ | |||
+ | ===March 2016=== | ||
+ | |||
+ | '''Somalia''' CHIRPS has 50 new stations reporting rainfall observations in Somalia, thanks to [http://www.faoswalim.org/ FAO SWALIM]. Previously, CHIRPS relied on satellite information (CHIRP) and influence from stations in the general region to give information about Somalia rainfall. The new stations were helpful in portraying how Somalia's MAM 2016 rainy season began. Parts of southern Somalia began with negative March anomalies of ~20 mm. This is corroborated by analyses based on other data that indicate poor March and April rainfall in the region. See [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2016/africa_hazard_Apr2016.pdf FEWS NET Hazards Report] and discussion below for more information. Another benefit of the Somalia station addition is that some stations contributed information in northeast Kenya (shown by the March decorrelation distance map in EWX). | ||
+ | |||
+ | '''Kenya, southeast Uganda, northern central Tanzania''' | ||
+ | CHIRPS shows below average rainfall by 25 to 50 mm, with some areas like Kilimanjaro (TZ) up to 100 mm below average. General agreement with ARC2 March anomalies. A station near Kilimanjaro at Moshi (37.1E,3.4S) reports only 13 mm rainfall in March, with an anomaly of -90 mm. The exception to CHIRPS and ARC2 agreement is central TZ, where ARC2 shows average to slightly above average and CHIRPS shows average leaning to below average. In that area CHIRPS uses two stations (32.8E,5S and 35.7E, 6.2S). These report anomalies of -32 mm and 9 mm, respectively. | ||
+ | |||
+ | '''Ethiopia''' The pattern for March rainfall anomaly looks similar to [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Mar2016-Mar2016_af_anom.gif NOAA's ARC2] and Ethiopia [http://www.ethiometmaprooms.gov.et:8082/maproom/Climatology/Climate_Monitoring/index.html?monitAna=cumul&T=21-31%20Mar%202016®ion=bb%3A40.1%3A10%3A40.2%3A10.1%3Abb&startDay=1%20Mar NMA Maproom data]. March rainfall was below average by 25 to 50 mm across southwest to north central Ethiopia. A minor difference between Ethiopia NMA data and CHIRPS (and ARC2) is that Ethiopia data shows slightly above average rainfall in areas along west boundary with Sudan and South Sudan. | ||
+ | |||
+ | '''South Africa and Lesotho''' | ||
+ | Near Lesotho and Free State (South Africa), several stations report low values that are below average. [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Mar2016-Mar2016_af_anom.gif ARC2] shows similar below average March rainfall in these areas. | ||
+ | |||
+ | '''Angola''' | ||
+ | SASSCAL station at 13.4E, 14.8S reported much higher rainfall value than its neighbor. Happened in Feb 2016 also. Checked and explained by topographic gradient (~1000 m higher than its neighbor). | ||
+ | |||
+ | '''Namibia''' | ||
+ | SASSCAL station value at 17.3E, 20.4S removed due to reporting 0 mm next to neighbor station report of 72 mm. Same issue occurred in Feb 2016. Station is now on watch list. | ||
+ | |||
+ | '''Brazil''' | ||
+ | Southeastern Brazil, along the coast, received very heavy rainfall, leading to flooding [http://floodlist.com/america/brazil-24-dead-after-floods-and-landslides-in-sao-paulo]. In general, the Amazon got more rainfall this month than it has in past months – however some of the values are suspiciously high. INMET, the Brazilian met agency, reports values closer to 300-400 mm, but CHIRPS is reporting values 400-700 [http://www.inmet.gov.br/portal/index.php?r=tempo2/mapasPrecipitacao]. | ||
+ | There are two stations in the Amazon that drove this value up, both due to our own methodology – both stations had several days missing and we interpolated the values. One station (seq num 205630) reported 618mm but we filled in 709mm; the other (seq num 205638) reported 608mm but we filled in 650mm. | ||
+ | We recommend taking out a different station in Brazil, in the north east (seq num 21432). This station has historically been lower than it should and significantly alters CHIRP into lower CHIRPS values. This month, the value was 21mm, surrounded by 200-400mm. The area should be wetter in the final CHIRPS. This station report was removed from CHIRPS March 2016 and the station is now on the watch list. | ||
+ | |||
+ | '''Columbia''' | ||
+ | The round egg-shaped feature is still in Columbia, an artifact of smoothing with the station value. There are also quite a few stations reporting 0mm along the northern coast, backed up by other station data [http://www.cpc.ncep.noaa.gov/products/international/gts/gts_30day_sam_prcp_rep.gif]. | ||
+ | |||
+ | '''Peru''' | ||
+ | CHIRPS reports a lot of rain in the north, not backed up by TRMM [http://www.cpc.ncep.noaa.gov/products/international/trmm/trmm_Mar2016-Mar2016_sam_anom.gif ]. However, flooding reports back up CHIRPS in catching this flooding event [http://floodlist.com/america/peru-10000-people-still-affected-by-floods-in-tumbes-department]. | ||
+ | |||
+ | '''Pakistan and surrounding region''' Above average rainfall, comes from ~18 stations. Other areas nearby that CHIRPS shows with above average rainfall are far northern India (~5 stations), Afghanistan (0 stations), and Jammu Kashmir (0 stations), and eastern Oman (~11 stations). Spatial extent can be attributed to CHIRP and to influence of stations mentioned above. Pakistan’s heavy rain was reported via [http://reliefweb.int/map/pakistan/pakistan-torrential-rainfall-quetta-5-march-2016 reliefweb.int] in early March in parts of Balochistan, with concerns of flash flooding. The [http://floodlist.com/asia/pakistan-100-killed-heavy-rain-floods-march-2016 storms continued into mid March] across 6 provinces and led to flash floods, inland floods, and landslides that collapsed houses and other buildings. In the first half of March 121 people were killed and 127 were injured in Pakistan. | ||
+ | |||
+ | '''Balkan Peninsula countries''' Serbia, Montenegro, Macedonia, Bulgaria and Greece. CHIRPS shows above average rainfall (25 mm to 100 mm above average). Largest anoms were in Serbia and Montenegro. More than 50 stations reported the wet conditions across the region. According to Floodlist.com, heavy rainfall in early March created [http://floodlist.com/europe/serbia-emergency-declared-floods-force-hundreds-evacuate emergency situations] in Serbia after flooding and landslides damaged homes and transportation links in central and eastern parts of the country. By the end of March over 1000 families received [http://reliefweb.int/disaster/fl-2016-000025-srb aid from the Red Cross]. | ||
+ | |||
+ | '''Switzerland, Austria, and parts of Italy, Spain, and Portugal''' CHIRPS shows rainfall was 10 to 50 mm below average. Supported by ~50 stations in total and CHIRP. | ||
+ | |||
+ | '''Southeast Asia''' Above average rainfall in Indonesia indicated in CHIRPS was backed up by news reports of flooding [http://floodlist.com/asia/indonesia-2-dead-bandung-floods-march-2016]. | ||
+ | |||
+ | '''Australia''' ~6 stations, especially in the west and all from the GHCN dataset, showed either zero or significantly lower values that surrounding stations, CHIRP, or weather reports. | ||
+ | |||
+ | ''Contributors: Emily Williams, South America; Laura Harrison, Europe and Central Asia; Libby White, Southeast Asia and Oceania.'' | ||
+ | |||
+ | ===February 2016=== | ||
+ | |||
+ | '''Tajikistan, Kyrgyzstan, Uzbekistan, Afghanistan, Pakistan''' The general area around Tajikistan has very suppressed precipitation, with z-scored ranging from -1.5 to -3. Reports detail that this level of supressed rainfall may lead to a drought, impacting the water supply to neighboring countries [ http://www.azerbaijannews.net/index.php/sid/241799989]. The values are verieid by reports (ex/Dushanbe, Tajikistan at 7.40mm for hte month [ https://www.wunderground.com/history/airport/UTDD/2016/2/16/MonthlyCalendar.html?req_city=Dushanbe&req_statename=Tajikistan&reqdb.zip=00000&reqdb.magic=1&reqdb.wmo=38836]). | ||
+ | 'Note: The decorrelation map has a strange V-like artifact over Tajikistan, which may be impacting the correlation of the stations.' | ||
+ | |||
+ | '''Indonesia & Malaysia''' Significant rainfall and flooding has been reported across Indonesia and Malaysia. Values have been verified by various reports [http://floodlist.com/asia/malaysia-indonesia-floods-force-evacuate-february-2016 ] [http://floodlist.com/asia/indonesia-43-killed-floods-landslides-jan-feb-2016]. Some pixels in Indonesia show negative anomalies in a sea of positive anomalies (when working in anomaly space), but when the actual precip values are added up for the month at that station (ex//Semarang [http://www.wunderground.com/history/station/96837/2016/2/28/WeeklyHistory.html?req_city=&req_state=&req_statename=&reqdb.zip=&reqdb.magic=&reqdb.wmo= ]), we find that the values are ok. | ||
+ | |||
+ | '''Philippines''' The Philippines are several months into a significant drought, backed up by reports [https://www.irinnews.org/news/2016/02/19/el-ni%C3%B1o-hits-philippines-farmers-drought-rats]. | ||
+ | |||
+ | '''Angola''' There is a large positive anomaly in Angola. The southern tip of it has a report of flooding [http://floodlist.com/africa/angola-floods-lubango-huila]. Much of the rain fell in the last dekad of February, with the first two showing negative or no anomalies. | ||
+ | |||
+ | '''Madagascar''' The northern tip recieved 121mm of rain in one day [http://floodlist.com/africa/poor-distribution-rainfall-leads-floods-droughts-southern-africa ]; 700,000 people in the south were impacted by the supressed rainfall, and 30,000 in the north by flooding [http://www.madagascar-tribune.com/30-000-sinistres-dans-le-Nord-et,21830.html]. | ||
+ | |||
+ | '''Mozambique''' Large are of high precipitation in Zambezi region observed in CHIRPS that was not seen CHIRP product. It was determined that a nearby station perturbed the climatology which corresponded to a land surface elevation gradient. | ||
+ | |||
+ | '''Brazil and Argentina''' CHIRPS compared well, visually, with the monthly Met Services of each country. | ||
+ | |||
+ | '''South American''' [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2016.02.png CHIRPS Mean regional] statistic hit a another new low for February which is consistent with the last 5 month. | ||
+ | |||
+ | ===January 2016=== | ||
+ | |||
+ | '''Zimbabwe, Mozambique, Madagascar''' January CHIRPS shows large negative rainfall anomalies in these countries, on the order of 100-200 mm below average. These are more than 2 standard deviations from the mean in southern Madagascar, Tete province (Mozambaique), Mashonaland provinces (Zimbabwe), and Southeast province (Zambia). Enhanced dryness in these areas is part of a spatially large and persistent condition affecting southern Africa that is due to El Nino. See the [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2016/Common_Statement_El%20Nino_10_February.pdf Joint EC, FAO, FEWS NET and WFP Statement on El Niño Impact in Southern Africa] | ||
+ | |||
+ | '''Tanzania, northern Mozambique, northern Madagascar''' CHIRPS reports wet anomalies of more than 100 mm. These were historically extreme (more than 2.5 standard deviations above the mean, in the ~98th percentile) in Mozambique's Cabo Delgado province and Tanzania provinces Mtwara, Lindi, and Morogoro. The largest anomalies were in Morogoro (+400mm) and areas in northern Madagascar including the Comoros Islands (150-300 mm). The very wet conditions is supported by 15+ stations. In Tanzania's [http://reliefweb.int/disaster/fl-2016-000011-tza Dodoma province] heavy rain, strong winds, and flooding from 17-18 January destroyed 145 houses and affected 2,800 people. Previously, [http://floodlist.com/africa/mozambique-floods-north-january-2016 extreme wet conditions] destroyed 1,500 homes in northern Mozambique. Due to the intensification of heavy rain in January, 5 fatalities occurred in Cabo Delgado province. | ||
+ | |||
+ | '''Gabon, Congo, and northern DRC''' CHIRPS shows rainfall as below average in January in western areas of central Africa. The estimates come from CHIRP and also ~12 stations in the area. NOAA's ARC2 data also reports a drier than normal January 2016 in this area. | ||
+ | |||
+ | '''More stations in Africa CHIRPS''' The station coverage has improved in southeast Africa. From November 2015 to January 2016 the number of reporting stations doubled in Botswana (7 to 14) and Zambia (8 to 17) and increased greatly in Angola (1 to 17). Improvements come from integration of the SASCAL dataset. | ||
+ | |||
+ | '''Brazil, Paraguay''' In central eastern and southern areas in Brazil and Paraguay CHIRPS reports wet anomalies of 100-150 mm and to +300 mm above average. More than 60 stations reported these conditions, in addition to CHIRP. According to FloodList more than 215,000 people were [http://floodlist.com/tag/brazil affected by flooding in January] in Rio de Janiero, Mato Grosso, and Parana states (Brazil). | ||
+ | |||
+ | '''South America (northern/eastern and Amazon area)''' CHIRPS estimates January rainfall as being around 100mm below average from the Atlantic coast, through northern Brazil, and into southern Columbia. Some coastal zones of French Guinea show 200-300mm dry anomalies. The spatial pattern of dryness in CHIRPS is similar to what the satellite-based CHIRP data estimates, but the dry anomalies are also sourced from approximately 20 stations across the region (mainly in Brazil and to the east) | ||
+ | |||
+ | '''Columbia''' Columbia's Pacific coast area show very dry anomalies (200-400mm below average). Caution should be applied to the data in this zone as the anomalies are historically extreme (more than 2 standard deviations below the mean) but there are no stations reporting in the immediate area. Interesting effects seem to be coming from CHIRP and neighboring stations. Influence from neighboring stations is heavy in the southern section, as CHIRP shows above average in that area. Dryness in the northern section, which climatologically is drier, seems to come mainly from CHIRP. | ||
+ | |||
+ | '''Florida (US) and Cuba''' Extreme wet conditions in January in southern Florida and parts of Cuba. Rainfall was 100-250 mm above normal. The dense station coverage in the United States supports these estimates. Many areas experienced rainfall higher than the 95th percentile. Some areas broke records for January. In [http://www.news-press.com/story/weather/2016/01/22/nws-beware-strong-thunderstorms-southwest-florida/79162734/ Fort Myers, FL] for example it rained more than 8.5 inches in January (average is less than 2 inches). This followed their hottest Christmas on record. | ||
+ | |||
+ | '''California (US)''' January CHIRPS shows above average rainfall in northern California, with 50-150mm positive anomalies for most areas north of 35N. These estimates come from CHIRP and more than 40 stations. Depending on location rainfall ranged from the 68th to 90th percentile compared to previous January CHIRPS estimates. | ||
+ | |||
+ | ''Contributors: Laura Harrison (Africa, South America, Latin America, U.S.); 2/19/16'' | ||
+ | |||
+ | ===December 2015=== | ||
+ | |||
+ | '''Zimbabwe''' | ||
+ | Thus far into the 2015-2016 season, [ftp://ftp.cpc.ncep.noaa.gov/fews/threats/afrhaz20151231.pdf drought conditions] have affected many countries of Southern Africa, including Angola, South Africa, Botswana, Zambia, Zimbabwe, Lesotho, Swaziland, and | ||
+ | Mozambique. This was due to a delayed start and erratic distribution of rainfall since the start of the season in October. December rainfall was a key contributor to season total deficits in Zimbabwe. CHIRPS shows large rainfall deficits across the country ranging from 50 to 150 mm below the December average. The largest deficits are in central-eastern and northern Zimbabwe. There is high confidence in CHIRPS data in Zimbabwe due to agreement from 7 stations, CHIRP, and ARC2 in most areas. | ||
+ | |||
+ | '''Mozambique''' | ||
+ | CHIRPS shows below average for most of the country, with anomalies in northern region of -15 to -75mm and larger deficits in the central and southern region (-75 to -150mm). The northern region dryness is in contrast to what NOAA’s ARC2 and RFE2 products show for December, which is above average rainfall (50-100 mm anomalies) in Cabo Delgado province. The CHIRPS dryness seems to be coming from CHIRP, and from influence of a station in northwest Mozambique. Another difference between CHIRPS and ARC2 is in central-southern Mozambique in southern parts of Manica and Sofala provinces. Here, ARC2 shows [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Dec2015-Dec2015_af_anom.gif rainfall surplus] and CHIRPS shows deficit. These deficits in Manica seem sourced mainly from CHIRP and from nearby Zimbabwe stations, as a GTS station in Manica did not report a large deficit. There is congruent evidence of very poor December rainfall in southern Mozambique, with reports of deficits from three stations and agreement with CHIRP and ARC2. | ||
+ | |||
+ | '''Zambia''' | ||
+ | CHIRPS shows that most of Zambia, in particular the southern parts, experienced below average December rainfall. Ten of the twelve stations reporting to CHIRPS in Zambia reported deficits. The worst deficit reported was near Lusaka at 181 mm below average. Poor December rainfall may have exacerbated [http://reliefweb.int/sites/reliefweb.int/files/resources/rvac-zambia_2015.pdf problems with food security] that were previously identified in western, southern, and eastern areas. Overall, ARC2 and CHIRPS are not in agreement in Zambia. ARC2 shows above average conditions in northwest and north central provinces. Both products agree that southeast province was below average. | ||
+ | |||
+ | '''Tamil Nadu, India''': CHIRPS continue to show the [http://floodlist.com/asia/cost-tamil-nadu-floods-347-lives-3-billion-dollars reported] continued anomalous rainfall in southern India. However, rainfall was not as severe as November, and most rainfall seems to have occurred early in December. Two stations in and around Puducherry, south of Chennai, reported 200-500 mm above the average rainfall. | ||
+ | |||
+ | '''Kazakhstan/Northwest China''': CHIRPS reported very wet conditions in Kazakhstan, especially near the border of China's Xinjian province. Rainfall appears to be two to three times the average, with one station on the border reporting six times the average rainfall. Seven stations in the area reported above average rainfall. CHIRP generally agreed with CHIRPS, but not to the extent of the station on the border. No news reports regarding especially heavy rainfall in the region were found. | ||
+ | |||
+ | '''Philippines''' | ||
+ | CHIRPS shows the very wet conditions that occurred in the Philippines in December due to multiple major storms. Rainfall surpluses of 250 to 900mm are shown in the data. December totals along the east coast ranged from 650 to 1400mm. According to a report from [http://www.emergencymgmt.com/disaster/200000-remain-displaced-as-toll-rises-to-45.html Emergency Management], the rain was caused by a cold front, dragged into the country by Typhoon Nona (international name: Melor) and Tropical Depression Onyok, which hit the country in succession in mid-December. The December storms were responsible for at least [http://www.theguardian.com/world/2015/dec/19/philippines-storm-death-toll-rises-as-rains-threaten-to-worsen-flooding 45 fatalities]. | ||
+ | |||
+ | '''East Indonesia/Papua New Guinea''' | ||
+ | CHIRPS shows large rainfall deficits that range from 150 mm to 300 mm below average for December. This area received only 30 to 70 percent of average December rainfall, based on the CHIRPs climatology. These conditions are consistent with those experienced for several months in the region. Drought and erratic rainfall here are linked with El Nino. [http://reliefweb.int/report/papua-new-guinea/papua-new-guinea-drought-iom-preparedness-and-response-situation-report-9 Impacts] through the end of 2015 were depletion of food sources and lack of water for household use. These problems have caused increased disease risk due to poor sanitation and use of non-sustainable coping mechanisms, such as households selling needed assets. | ||
+ | |||
+ | '''Southeast China''' | ||
+ | Above average rainfall in southeast China is due to more than 25 station reports and also CHIRP satellite-based estimates. The wet conditions are linked to the series of major storms, including Typhoon Nona/Melor that moved through the Philippines and the South China Sea. | ||
'''United States''' | '''United States''' | ||
− | + | The Midwest and Southeast US continued with above normal rains creating flooding in the Midwest. CHIRPS captured this rainfall with large areas of the country in excess of 150 mm for the month. | |
− | ''' | + | '''Colombia''' |
− | + | A large region in the center of the country, "the blob", was estimated to have received above normal rainfall after station values were applied. There was no indication of the blob in the CHIRP data field. A group of station on the northeast end of the blob may have caused the creation of this above normal rainfall pattern. There is a group of three stations with very low values of 2 mm and then one 30km to the west with a higher reading of 179mm. We think there may be some effect of the autocorrelation field causing this pattern when there is a large differential between these to estimates. The pattern is seen in the previous three months but to a lesser extent. The pattern is not seen in previous years since these data contain many more stations in the region and wash out the effect. We will continue to investigate this phenomenon. | |
− | ''' | + | South America |
− | + | '''Paraguay, Brazil, Argentina, Urugay''': Flooding in these four countries. Asuncion, Paraguay saw a lot of flooding shown in the r-checks file[[http://floodlist.com/america/flooding-rivers-uruguay-brazil-paraguay-argentina]] ; South Brazil saw flooding [[http://floodlist.com/america/flooding-rivers-uruguay-brazil-paraguay-argentina]]; these reports are backed up by TRMM [[http://www.cpc.ncep.noaa.gov/products/international/trmm/trmm_Dec2015-Dec2015_sam_anom.gif]]. | |
− | ''' | + | '''Sao Paulo, Brazil''': Report says that Sao Paulo received less than normal rain in December [[http://www.weather.com/science/environment/news/brazil-drought-sao-paulo-reservoir]]; pre-station CHIRPS labels the area as wet, but station data backs up a negative anomaly, and CHIRPS did a good job of incorporating the station data to drive down the final CHIRPS value in the immediate area. This lack of rainfall for December is very localized. |
− | |||
− | ''' | + | '''Brazil''': The northern parts of Brazil (part of the Amazon Basin) have been in a terrible drought in 2015, which has continued in December; this patterns is backed up by Brazil’s INMET [[http://www.inmet.gov.br/portal/index.php?r=tempo2/mapasPrecipitacao]]. |
− | |||
− | ''' | + | '''Peru''': Artifact of flooding in northern Peru backed up by reports [[http://floodlist.com/america/peru-floods-san-martin-december-2015; http://floodlist.com/america/heavy-rain-peru-landslides-floods]] |
− | |||
− | |||
− | |||
− | '''Brazil''' | + | '''Notes on CHIRPS in South America''' |
− | CHIRPS reports below average rainfall across much of the nation, with exception of heavy rainfall that occurred in Porto Alegre, Rio Grande do Sul state. Major flooding occurred in that area [http://floodlist.com/america/brazil-floods-1500-displaced-in-porto-alegre-rio-grande-do-sul]. The rainfall deficits during October covered much of the Amazon rain forest and are highly concerning given the magnitude and persistence of drought conditions since 2014. The Amazon drought is reported as the worst in the past 80-100 years [http://www.dailymail.co.uk/news/article-3288144/The-Amazon-drained-forest-Incredible-pictures-devastating-effect-drought-ravishing-Brazil-area-s-worst-dry-spell-100-years.html?ITO=1490&ns_mchannel=rss&ns_campaign=1490] and has created water shortages in major cities and rural areas [http://www.telesurtv.net/english/news/Military-Could-Step-in-Over-Brazil-Drought-Chaos-20150506-0040.html][http://www.telesurtv.net/english/multimedia/Severe-Drought-in-Brazilian-Amazon-Leaves-Boats-High-and-Dry-20151019-0044.html]. Reality Checks monthly CHIRPS comparison identified the South America mean rainfall in [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2015.09.png September 2015] and [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2015.10.png October 2015] as being the driest since 1981, when the CHIRPS record began, and Brazil deficits play a major role in these continental scale deficits. | + | ''Station artifacts'': There are circular artifacts in Southern Brazil and Paraguay, similar to the ones seen in previous months (see November's "Recurrent CHIRPS Issues"); they seem to be station-driven as they don’t exist in CHIRP. |
+ | |||
+ | '''Regional statistics''' | ||
+ | * [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.global.stats.2015.12.png Global CHIRPS Maximum] exceed 2200 mm for a new high for December. This is still under investigation. | ||
+ | * [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2015.12.png South American CHIRPS Mean] hit a new low for December but this is in agreement with reports from the continent. | ||
+ | * [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2015.12.png Southern Africa CHIRPS Max] hit a new low for December but this is in agreement with reports from the continent. | ||
+ | |||
+ | ''Contributors: Emily Williams (South America), Libby White w/Laura Harrison (Asia), Martin Landsfeld (U.S., Latin America, Statistics); 1/19/16'' | ||
+ | |||
+ | ===November 2015=== | ||
+ | |||
+ | '''United States''': CHIRPS shows the very wet conditions that occurred across the South and southern Midwest. November rainfall was | ||
+ | 100-200 mm above average in northeastern Texas, eastern Oklahoma, Arkansas, Missouri, and in Georgia, North Carolina, and South Carolina. Monthly totals in Arkansas and Missouri were the [http://www.ncdc.noaa.gov/sotc/service/national/statewidepcpnrank/201511.gif highest on record] in November 2015 (record dates to 1895). CHIRPS shows below average rainfall in coastal Oregon and coastal northern and southern California. | ||
+ | |||
+ | '''Mexico, Belize, Guatemala, El Salvador''': The region encompassing the Yucatan Peninsula and south to the Pacific received heavy, above normal rainfall. A Guatemala station near the Caribbean Sea, Puerto Barrios, reported 680mm, which is 15 inches above normal. [http://reliefweb.int/report/guatemala/echo-daily-flash-27-november-2015-guatemala-severe-weather-conred-wmo-insivumeh Reports from Guatemala] explain that much of the heavy rain occurred in the second half of November. It led to dangerously high river levels and flooded communities in Alta Verapaz region. [http://floodlist.com/america/floods-affect-1000s-in-guatemala-belize-and-mexico Flooding displaced thousands of people in Guatemala, Belize, and Mexico.]CHIRPS also shows Panama as receiving above average rainfall. | ||
+ | |||
+ | '''Southern Africa''': November CHIRPS shows widespread dryness across most of southern Africa, with anomalies of -30mm to -80mm. Some of the affected areas experienced below normal rainfall in October (South Africa, Zimbabwe, Mozambique, Angola). A below average rainfall season tends to occur in the region during El Nino conditions. The November dryness contributed to [http://www.cpc.ncep.noaa.gov/products/international/africa/africa_hazard.pdf substantial season-to-date negative anomalies] that pose a risk to cropping and pastoral activities. | ||
+ | |||
+ | '''Uganda, Kenya, Tanzania''': November totals were 75mm to 150mm above average across most of Uganda and the Lake Victoria Basin. Similar magnitude anomalies occurred in other areas of southern Kenya and east and west Tanzania. The November wetness marks the second consecutive month month of anomalous rainfall in Uganda and west Tanzania, according to CHIRPS and the NOAA ARC2 product ([http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Oct2015-Oct2015_af_anom.gif Oct ARC2]; [http://www.cpc.ncep.noaa.gov/products/international/africa_arc/africa_arc_Nov2015-Nov2015_af_anom.gif Nov ARC2]) | ||
+ | |||
+ | '''Qatar and Saudi Arabia''': Areas received record rainfall in November, but CHIRPS did not pick it up. Qatar's Met Department reported a year's worth of rain in Doho (80mm) on Nov 25th. There were no Qatar stations reporting in CHIRPS. The satellite-based CHIRP product did not show sign of the wet events. There were several stations in Saudi Arabia reporting to CHIRPS in [http://floodlist.com/asia/floods-riyadh-saudi-arabia-qatar-november-2015 areas with reported flooding], but only one of them had a large anomaly ([http://english.alarabiya.net/en/webtv/reports/2015/11/03/Heavy-rains-floods-Saudi-Hafr-Al-Batin-suspends-schools.html Hafr Al-Batin], at 90mm above normal). The influence of this particular station is not seen in the final CHIRPS product. Overall, CHIRPS shows a slightly wetter than average November in northern Saudi Arabia and no sign of the historic events noted here. | ||
+ | |||
+ | '''Southern Europe''': CHIRPS shows below average rainfall across the region. Italy was particularly dry, with northern Italy at 150mm below average. | ||
+ | |||
+ | '''India''': Exceptional amounts of rainfall were reported in southern India, and CHIRPS captured these anomalies well. Heavy rains occurred in areas that typically receive 150mm to 500mm in November, driving totals instead up to 2 times those amounts. The Chennai area received ~1000mm in November, according to news reports and to a GHCN-v2 monthly station that reported to CHIRPS. Some areas had the [http://www.accuweather.com/en/weather-news/india-tamil-nadu-chennai-flooding-continues-wet-november/53943597 wettest November in 20 years.] | ||
+ | |||
+ | '''East Asia''': CHIRPS reported very wet conditions in southeast China, stretching from Guangi to the East China Sea coast near Shanghai. Anomalous wet conditions are also shown in Japan, South Korea, and the DPRK. | ||
+ | |||
+ | '''Indonesia''': While most of Indonesia has below average rainfall values in November CHIRPS, there is an interesting rainfall dipole feature. Eastern Malaysia, Brunei, and western parts of Kalimantan, Indonesia show above average rainfall. The wetness is reported by multiple station observations and from CHIRP. | ||
+ | |||
+ | '''Brazil''': Dryness persisted across the Amazon Basin in November. See October and September posts below. CHIRPS shows positive rainfall anomalies of ~100mm in areas of southeast Brazil (Sao Paulo and Rio de Janeiro). The wet November coincided with the [http://www.wsj.com/articles/brazil-dams-failure-flooded-region-with-toxic-wastes-u-n-report-says-1448494712 collapse of a dam] that released massive amounts of sludge and some toxic waste through the Rio Doce. | ||
+ | |||
+ | ===December 2015=== | ||
+ | Recurrent CHIRPS issues | ||
+ | #Circular-shaped artifacts are seen in the data, anomalies, and z-scores of CHIRPS data in southern Brazil. These tend to be centered at station locations. The issue needs more evaluation, but the origin seems to be from the CHPclim, which has similar but smaller features in the region. These features may increase in size according to the spatial influence of stations. | ||
+ | #Coastal data artifact along North America's west coast. CHIRPS is generally a land-only product, but in some areas the coverage extends 1 to 3 pixels beyond the coastal boundary. Along the West Coast these pixels have lower climatological mean values than the data on land. This results in substantially different rainfall estimates and anomalies. The differences may be due to extension of coverage of the CHPclim based on TRMM, and should be examined further. In the meantime, CHIRPS users may want to consider clipping their data to coastal boundaries to remove the artifact. | ||
+ | |||
+ | ''Contributors: Laura Harrison; 12/21/15'' | ||
+ | |||
+ | ===October 2015=== | ||
+ | |||
+ | '''United States''': A storm complex that tapped into the moisture from Hurricane Joaquin off the south-eastern coast of the US hit the Carolina's, dumping 12-24 inches of rain (picked up in CHIRPS)[http://www.accuweather.com/en/weather-news/tropical-storm-joaquin-east-coast-track-heavy-rain-deluge-flash-flooding-atlantic/52672710 ]. Louisiana and Texas, in addition, were hit with the remnants of Hurricane Patricia, receiving a lot of rain (also visible in r-checks) [http://www.reuters.com/article/2015/10/26/us-texas-flood-idUSKCN0SI0M920151026].Finally, a dry-spell it the midwest showed up as well [http://www.aerisweather.com/blog/wheres-october-rain-upper-midwest/]. | ||
+ | |||
+ | '''Mexico''': Hurricane Patricia hit the south-west coast of Mexico, and rapidly downgraded, as shown in CHIRPS and backed up by FEWS early warning data [http://earlywarning.usgs.gov/fews/product/28]. Two stations however reported very low values (4 and 5 mm) along the northern border of Patricia's path. One of them, 400141, is blocked by mountains so might have a rain shadow. The other, 400984, however, is on the coast and is a station to keep an eye on. The path of Patricia can be seen here [http://www.nytimes.com/interactive/2015/10/23/world/americas/hurricane-patricia.html?_r=0]. | ||
+ | |||
+ | '''El Salvador, Honduras, and Nicaragua''': The bay bordered by these three countries (where Choluteca is) has a very high station next to a low one. This is right where a severe gradient is that goes from high precipitation quickly to low. The mountains around this bay might act as a rain shadow. In El Salvador and Honduras, we see a similar pattern as the mountains block rain coming up from the south and a steep gradient occurs from high rain to very low. | ||
+ | |||
+ | '''Haiti''': Haiti is showing a positive rain anomaly in the north west. While this area has been doing well, other reports show average instead of a positive anomaly. Might be good to keep an eye on it. [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/camerica/Gonaives_Haiti_90day.gif] | ||
+ | |||
+ | '''East Africa''': October CHIRPS is in general agreement with rainfall estimates from NOAA CPC ARC2 and RFE2 datasets in east Africa. Differences in magnitude occur in [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2015/plot_GHA_October_mean_precip_diff_CHIRPS_vs_ARC_RFE.png parts of Sudan and South Sudan], where CHIRPS estimates are approximately 30% lower than ARC2 and RFE. The products are all in agreement that October rainfall was above average in Sudan, South Sudan, and Uganda ([ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2015/chirps-oct2015-anomaly-eastAfr-subset.png CHIRPS], [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2015/africa_arc_Oct2015-Oct2015_af_anom.gif ARC2], and [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/2015/rfe2-oct2015-anomaly-eastAfr-subset.png RFE2]). The source of lower CHIRPS values may be (1) a drier climatology in October CHIRPS compared to ARC2 climatology and (2) features in the CHIRPS algorithm that lead to conservative estimates and low bias. Also, in an area of reported heavy rains with flooding (border of Ethiopia, Sudan, and South Sudan) there appears to be a drying influence of two GHCN-v2 stations in southeast Sudan used in CHIRPS- these reported low but reasonable values locally, but reduced the CHIRP estimate in the high rainfall area. Ethiopia contained 8 stations this month, a big improvement from the past few months. | ||
+ | |||
+ | '''West Africa''': In October 2015, most of the station reports that contribute to CHIRPS in West Africa are from GHCN-v2, a source of monthly data that is highly ranked due to its quality control. CHIRPS compared well with CPC 30 day anomaly from the FEWS Hazards Report, 10/29/15, except in Guinea and Sierra Leone where CHIRPS is much drier. | ||
+ | |||
+ | '''South Africa''': Stations between Lesthoso and Swaziland reported lower values than CHIRP estimated. The stations reduced the final CHIRPS which is in agreement with the FEWS Africa Hazards Report, 10/29/15, abnormal dryness polygon over the region. | ||
+ | |||
+ | '''Brazil''': CHIRPS reports below average rainfall across much of the nation, with exception of heavy rainfall that occurred in Porto Alegre, Rio Grande do Sul state. Major flooding occurred in that area [http://floodlist.com/america/brazil-floods-1500-displaced-in-porto-alegre-rio-grande-do-sul]. The rainfall deficits during October covered much of the Amazon rain forest and are highly concerning given the magnitude and persistence of drought conditions since 2014. The Amazon drought is reported as the worst in the past 80-100 years [http://www.dailymail.co.uk/news/article-3288144/The-Amazon-drained-forest-Incredible-pictures-devastating-effect-drought-ravishing-Brazil-area-s-worst-dry-spell-100-years.html?ITO=1490&ns_mchannel=rss&ns_campaign=1490] and has created water shortages in major cities and rural areas [http://www.telesurtv.net/english/news/Military-Could-Step-in-Over-Brazil-Drought-Chaos-20150506-0040.html][http://www.telesurtv.net/english/multimedia/Severe-Drought-in-Brazilian-Amazon-Leaves-Boats-High-and-Dry-20151019-0044.html]. Reality Checks monthly CHIRPS comparison identified the South America mean rainfall in [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2015.09.png September 2015] and [ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.s_amer.stats.2015.10.png October 2015] as being the driest since 1981, when the CHIRPS record began, and Brazil deficits play a major role in these continental scale deficits. | ||
− | '''Asia''' | + | '''Asia''': CHIRP did not perform well with Typhoon Mujigae, between Hong Kong and Hainan on Oct. 5-7th. The stations reported the precipitation amounts and CHIRPS estimates were increased in the area. |
− | CHIRP did not perform well with Typhoon Mujigae, between Hong Kong and Hainan on Oct. 5-7th. The stations reported the precipitation amounts and CHIRPS estimates were increased in the area | ||
− | |||
− | |||
− | + | A GSOD station on northern border of Pakistan recorded 529 mm for the month. A neighboring station reported 179 mm. [http://www.reuters.com/article/2015/10/26/us-pakistan-landslides-idUSKCN0SK0L820151026#HssUvbrXthuKrDJk.97 A news report] claimed record rainfall in the area so we decided to keep the measurement. | |
− | + | ''Contributors: Laura Harrison (South America), Marty Landsfeld (Asia), Emily Williams (North and Central America, Hispanola), all-of-the-above and Shrad Shukla (Africa); 11/17/15'' | |
− | === | + | ===September 2015=== |
− | '''Vietnam''' Tropical Storm Vamco brought a lot of rainfall to central/northern Vietnam/Laos/Thailand (300+ mm with flooding and fatalities). CHIRPS picked up significant rainfall in Northern Vietnamn (around Hanoi), but CHIRPS's pattern is a bit north of the reports. [http://english.vietnamnet.vn/fms/society/141794/social-news-20-9.html] [http://phys.org/news/2015-09-nasa-heavy-rainfall-tropical-storm.html] | + | '''Vietnam''': Tropical Storm Vamco brought a lot of rainfall to central/northern Vietnam/Laos/Thailand (300+ mm with flooding and fatalities). CHIRPS picked up significant rainfall in Northern Vietnamn (around Hanoi), but CHIRPS's pattern is a bit north of the reports. [http://english.vietnamnet.vn/fms/society/141794/social-news-20-9.html] [http://phys.org/news/2015-09-nasa-heavy-rainfall-tropical-storm.html] |
− | '''China and Taiwan''' Typhoon Dujuan brought torrential rainfall to Northern Taiwan and Eastern China; CHIRPS shows it in E. China but not much in Taiwan. [http://www.accuweather.com/en/weather-news/tropical-storm-dujuan-may-thre/52554977] [http://mashable.com/2015/09/27/dangerous-typhoon-dujuan-taiwan/#eov5al5odiqk] Stations, though, seem to be reporting well so may be an interpolation problem with the climatology. | + | '''China and Taiwan''': Typhoon Dujuan brought torrential rainfall to Northern Taiwan and Eastern China; CHIRPS shows it in E. China but not much in Taiwan. [http://www.accuweather.com/en/weather-news/tropical-storm-dujuan-may-thre/52554977] [http://mashable.com/2015/09/27/dangerous-typhoon-dujuan-taiwan/#eov5al5odiqk] Stations, though, seem to be reporting well so may be an interpolation problem with the climatology. |
− | '''Japan''' Lots of rain and flooding along Western coast and center [http://www.reuters.com/article/2015/09/11/us-weather-japan-floods-idUSKCN0RA0Q920150911]. | + | '''Japan''': Lots of rain and flooding along Western coast and center [http://www.reuters.com/article/2015/09/11/us-weather-japan-floods-idUSKCN0RA0Q920150911]. |
− | '''Malaysia, Indonesia, Papua''' Massive dry swaths; many large uncontrolled fires from slash-and-burn agriculture (''could be good to keep an eye on for next month''). | + | '''Malaysia, Indonesia, Papua''': Massive dry swaths; many large uncontrolled fires from slash-and-burn agriculture (''could be good to keep an eye on for next month''). |
− | ''' Columbia ''' Station in Cali, Columbia looks low but looked at previous months values and it looks fine. Diego confirmed it has been dry there in July and August. The rains are returning now he says. | + | ''' Columbia ''': Station in Cali, Columbia looks low but looked at previous months values and it looks fine. Diego confirmed it has been dry there in July and August. The rains are returning now he says. |
SQL commands: | SQL commands: | ||
select * from precip_monthly4 where station_seqnum=20777 | select * from precip_monthly4 where station_seqnum=20777 | ||
select * from precip_monthly4 where station_seqnum= 205576 | select * from precip_monthly4 where station_seqnum= 205576 | ||
− | ''' Brazil ''' Near Sao Pablo all the stations are higher than CHIRP estimate. INMET rainfall map confirmed the higher values. Brazilian rainfall map can be found at: | + | ''' Brazil ''': Near Sao Pablo all the stations are higher than CHIRP estimate. INMET rainfall map confirmed the higher values. Brazilian rainfall map can be found at: |
http://www.inmet.gov.br/portal/index.php?r=home2/index | http://www.inmet.gov.br/portal/index.php?r=home2/index | ||
Click the Mapas de Precipitacao tab and then the Plus button at the bottom of the map and an end date and time period can be selected (30 dias). | Click the Mapas de Precipitacao tab and then the Plus button at the bottom of the map and an end date and time period can be selected (30 dias). | ||
− | ''' *South America record rainfall deficit* ''' Station comparison graphs showed a very low CHIRPS mean for South America. | + | ''' *South America record rainfall deficit* ''': Station comparison graphs showed a very low CHIRPS mean for South America. |
/home/CHIRPS/diagnostics.etc/v2.0/marty/chirps.s_amer.stats.09.png | /home/CHIRPS/diagnostics.etc/v2.0/marty/chirps.s_amer.stats.09.png | ||
But examining the CHIRPS didn’t reveal any errors in processing and given such a strong El Nino and the warm water in the eastern Pacific to the north, it we decided it was a real phenomenon. Also, stations in NW Brazil and Columbia verify the low precip values. | But examining the CHIRPS didn’t reveal any errors in processing and given such a strong El Nino and the warm water in the eastern Pacific to the north, it we decided it was a real phenomenon. Also, stations in NW Brazil and Columbia verify the low precip values. | ||
− | ''' Ethiopia ''' Ethiopia contains only 3 stations. A special check was done on the contribution these stations had for CHIRPS data and anomalies. The 3 stations (2 were co-located) showed below average September rainfall and enhanced CHIRP deficits. As a result, CHIRPS September rainfall shows ~100 mm below average in Addis Ababa and Dire Dawa areas-- roughly 25% of average September rainfall. The CHIRPS September values were compared to data plotted with the Ethiopia Met Agency's MapRoom, which is described as being satellite estimates merged with ~600 stations for the country. Similar magnitude September 2015 anomalies are seen in CHIRPS and the Ethiopia data [http://www.ethiometmaprooms.gov.et:8082/maproom/Climatology/Climate_Monitoring/index.html?monitAna=cumul&T=21-30%20Sep%202015&startDay=1%20Sep#tabs-2] for these areas. The stations were retained in CHIRPS. | + | ''' Ethiopia ''': Ethiopia contains only 3 stations. A special check was done on the contribution these stations had for CHIRPS data and anomalies. The 3 stations (2 were co-located) showed below average September rainfall and enhanced CHIRP deficits. As a result, CHIRPS September rainfall shows ~100 mm below average in Addis Ababa and Dire Dawa areas-- roughly 25% of average September rainfall. The CHIRPS September values were compared to data plotted with the Ethiopia Met Agency's MapRoom, which is described as being satellite estimates merged with ~600 stations for the country. Similar magnitude September 2015 anomalies are seen in CHIRPS and the Ethiopia data [http://www.ethiometmaprooms.gov.et:8082/maproom/Climatology/Climate_Monitoring/index.html?monitAna=cumul&T=21-30%20Sep%202015&startDay=1%20Sep#tabs-2] for these areas. The stations were retained in CHIRPS. |
− | |||
− | |||
− | '' | + | '''Somalia, Uganda, Rwanda and Burundi''': All had 0 stations reporting |
− | + | ''Contributors: Emily Williams (Asia, Australia, Pacific Islands), Marty Landsfeld (South America, Africa), Laura Harrison (North and Central America, Africa); 10/19/15 - 10/23/15 '' | |
− | === | + | ===August 2015=== |
− | '''North Korea''' Removal of a GSOD station. DPRK experienced flooding associated with seasonal rains in early August, and from Tropical Cyclone Goni on 22-23 August, affecting South Hwanghae and North Hamgyong Provinces ([http://floodlist.com/asia/north-korea-floods-21-dead-9-missing],[http://floodlist.com/asia/north-korea-floods-40-dead-rason]) . The two GTS stations in the country are in these areas and reported heavy rains, which the CHIRPS reflects near these areas. GSOD stations (~12) in rest of the country report below average rain, making August an overall poor month for rain in DPRK. This has likely exacerbated the problems associated with late start to seasonal rainfall-- in June DPRK declared they were experiencing the 'worst drought in a century.' There have been major population impacts in the region, perhaps due to a combination of weather and political forces. Suggest removal of GSOD station #274228: Report is 9.19 mm in area with flooding. [http://reliefweb.int/sites/reliefweb.int/files/resources/DPR%20Korea%20Drought%20Snapshot_Final.pdf] | + | '''North Korea''': Removal of a GSOD station. DPRK experienced flooding associated with seasonal rains in early August, and from Tropical Cyclone Goni on 22-23 August, affecting South Hwanghae and North Hamgyong Provinces ([http://floodlist.com/asia/north-korea-floods-21-dead-9-missing],[http://floodlist.com/asia/north-korea-floods-40-dead-rason]) . The two GTS stations in the country are in these areas and reported heavy rains, which the CHIRPS reflects near these areas. GSOD stations (~12) in rest of the country report below average rain, making August an overall poor month for rain in DPRK. This has likely exacerbated the problems associated with late start to seasonal rainfall-- in June DPRK declared they were experiencing the 'worst drought in a century.' There have been major population impacts in the region, perhaps due to a combination of weather and political forces. Suggest removal of GSOD station #274228: Report is 9.19 mm in area with flooding. [http://reliefweb.int/sites/reliefweb.int/files/resources/DPR%20Korea%20Drought%20Snapshot_Final.pdf] |
− | '''South Korea''' CHIRPS dry anomaly confirmed. Stations show low August rainfall (verified by news reports), which has created an overall poor season there [http://www.usda.gov/oce/weather/pubs/Monthly/current.pdf]. Makes North Korea dryness believable also. | + | '''South Korea''': CHIRPS dry anomaly confirmed. Stations show low August rainfall (verified by news reports), which has created an overall poor season there [http://www.usda.gov/oce/weather/pubs/Monthly/current.pdf]. Makes North Korea dryness believable also. |
− | '''China''' Some cases of good stations not influencing CHIRPS local values. Saw several instances when neighboring stations swamped what looks like reasonable above average rainfall reports from some stations. Led to below average CHIRPS values in these areas. Examining monthly decorrelation distance maps may help identify scope of problem. | + | '''China''': Some cases of good stations not influencing CHIRPS local values. Saw several instances when neighboring stations swamped what looks like reasonable above average rainfall reports from some stations. Led to below average CHIRPS values in these areas. Examining monthly decorrelation distance maps may help identify scope of problem. |
− | '''Ghana''' Concern about station reports and conditions. Several stations reported 0-10 mm in August. These had some influence on CHIRPS. Were deemed ok stations as they had reasonable values in earlier months and seasonal rains have been below average due to active ITCZ enhanced rains in an abnormally northern position. Note: In July 2015 Ghana had only 1 reporting station in CHIRPS, as compared to 5-13 in other months. | + | '''Ghana''': Concern about station reports and conditions. Several stations reported 0-10 mm in August. These had some influence on CHIRPS. Were deemed ok stations as they had reasonable values in earlier months and seasonal rains have been below average due to active ITCZ enhanced rains in an abnormally northern position. Note: In July 2015 Ghana had only 1 reporting station in CHIRPS, as compared to 5-13 in other months. |
− | '''Ethiopia''' Exceptional dryness identified by ranked z scores. Z score=-2.6, station value=160 mm, Ethiopia highlands (10.33N, 37.740E). | + | '''Ethiopia''': Exceptional dryness identified by ranked z scores. Z score=-2.6, station value=160 mm, Ethiopia highlands (10.33N, 37.740E). |
Determined CHIRPS value in area was representative of conditions. Also that this is an area of potential concern that needs highlighting on Hazards report-- GeoWRSI shows crops were in reproductive phase in August; Prelim CHIRPS shows September 1-10 was below average; ARC2 shows below average thru September there also. | Determined CHIRPS value in area was representative of conditions. Also that this is an area of potential concern that needs highlighting on Hazards report-- GeoWRSI shows crops were in reproductive phase in August; Prelim CHIRPS shows September 1-10 was below average; ARC2 shows below average thru September there also. | ||
− | '''India''' Incorrect wet anomaly in northern India. India's Met Department shows below average ([http://www.imd.gov.in/section/hydro/dynamic/rfmaps/monthly/aug2015.jpg]), but CHIRPS shows strongly above average. Due to combination of: 0 India stations in area + very wet observation in NE Pakistan (verified by reports) + wet station in China + CHIRP shows wet anomaly. Otherwise, CHIRPS correctly identified August rainfall deficits across most of India and surplus in Bhutan. | + | '''India''': Incorrect wet anomaly in northern India. India's Met Department shows below average ([http://www.imd.gov.in/section/hydro/dynamic/rfmaps/monthly/aug2015.jpg]), but CHIRPS shows strongly above average. Due to combination of: 0 India stations in area + very wet observation in NE Pakistan (verified by reports) + wet station in China + CHIRP shows wet anomaly. Otherwise, CHIRPS correctly identified August rainfall deficits across most of India and surplus in Bhutan. |
− | '''Chile''' Atacama desert, possible problem. Reports say significant rain in Atacama desert ([http://www.weather.com/news/news/chile-deadly-storm-flooding-mudslides] ,[http://www.accuweather.com/en/weather-news/dry-spell-in-santiago-continue/51049727]) , which rounds to 15 mm instead of 5; CHIRPS isn’t really picking it up as it’s a very fine difference, but as that area is a desert area, that small increase in rainfall resulted in massive flooding and evacuation. CHIRPS showed significant precipitation inland of Concepcion, which agrees with rain and snow reports ([http://www.accuweather.com/en/weather-news/dry-spell-in-santiago-continue/51049727]). | + | '''Chile''': Atacama desert, possible problem. Reports say significant rain in Atacama desert ([http://www.weather.com/news/news/chile-deadly-storm-flooding-mudslides] ,[http://www.accuweather.com/en/weather-news/dry-spell-in-santiago-continue/51049727]) , which rounds to 15 mm instead of 5; CHIRPS isn’t really picking it up as it’s a very fine difference, but as that area is a desert area, that small increase in rainfall resulted in massive flooding and evacuation. CHIRPS showed significant precipitation inland of Concepcion, which agrees with rain and snow reports ([http://www.accuweather.com/en/weather-news/dry-spell-in-santiago-continue/51049727]). |
Santiago: CHIRPS wet anomaly confirmed. Report ([http://www.accuweather.com/en/weather-news/dry-spell-in-santiago-continue/51049727]) details increased rain, which is showing up in CHIRPS. | Santiago: CHIRPS wet anomaly confirmed. Report ([http://www.accuweather.com/en/weather-news/dry-spell-in-santiago-continue/51049727]) details increased rain, which is showing up in CHIRPS. | ||
− | '''Uruguay''' CHIRPS wet anomaly confirmed. CHIRPS recorded above average rainfall for Uruguay for August 2015. The rainfall throughout the country, according to CHPClim, tends to be between 60 and 90 mm; however, CHIRPS reported it ranging from 190 to 240 mm, with the south-eastern coast receiving between 300 and 340mm for the month. This increase in rainfall is backed up by reports, including one from “floodlist” ([http://floodlist.com/america/uruguay-4000-evacuated-floods-4-departments]). | + | '''Uruguay''': CHIRPS wet anomaly confirmed. CHIRPS recorded above average rainfall for Uruguay for August 2015. The rainfall throughout the country, according to CHPClim, tends to be between 60 and 90 mm; however, CHIRPS reported it ranging from 190 to 240 mm, with the south-eastern coast receiving between 300 and 340mm for the month. This increase in rainfall is backed up by reports, including one from “floodlist” ([http://floodlist.com/america/uruguay-4000-evacuated-floods-4-departments]). |
− | '''Burkina Faso (added 9/23/15)''' Station near capital (Ouagadougou) flooded in August, but CHIRPS didn’t pick it up. However, CHIRPS did pick up the rest of the flooding in the country. | + | '''Burkina Faso (added 9/23/15)''': Station near capital (Ouagadougou) flooded in August, but CHIRPS didn’t pick it up. However, CHIRPS did pick up the rest of the flooding in the country. |
− | ====Notes on Rchecks resources | + | ===September 2015=== |
+ | Notes on Rchecks resources | ||
− | Regarding the rchecks-2.files: Reminder | + | Regarding the rchecks-2.files: Reminder - The zscores in rchecks-2.files are not station zscores. They are zscores of CHIRPS data that has been placed at that station's pixel. Using the zscores in these files is helpful for identifying extreme CHIRPS that are caused by extreme station values. Using the zscores is not helpful for identifying stations that do not have influence much on CHIRPS BUT give bad reports (had concerns about this for some stations in Ghana, see above). We discussed routinely isolating a value that indicates this, so that we know which stations have issues. Basically we would do a sorting of the country information based on this value, like we do with the zscores (check.txt). Something to look into more. Also, we corrected a bug that limited the number of recheck text files. Now should have all countries. |
''Contributors: Laura Harrison, Marty Landsfeld, Emily Williams; 9/17/15'' | ''Contributors: Laura Harrison, Marty Landsfeld, Emily Williams; 9/17/15'' | ||
− | == | + | ===July 2015=== |
− | |||
− | |||
− | '''Ethiopia''' | + | '''Ethiopia''': July’s r-check had quite a few high z-scores. Upon analysis, these discrepancies were coming from the highlands, near Addis Ababa, and south of Addis Ababa. |
− | July’s r-check had quite a few high z-scores. Upon analysis, these discrepancies were coming from the highlands, near Addis Ababa, and south of Addis Ababa. | + | <br> |
Station (10.33, 37.74; in town of Debre Markos) reported much lower than CHIRP and CHPClim, in the same way it reported low for August 2015. Station (8.86, 39.92; in town of Metehara Merti, near Addis Ababa) also reported much lower than CHIRP and CHPClim. ARC2 tells a similar story; ARC2 dictates the area having received 200-300mm[http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jul2015-Jul2015_af_clim.gif]. ARC2’s anomaly map for July also roughly matched CHIRPS’ anomaly map, at a decrease of around -200m of normal[http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jul2015-Jul2015_af_anom.gif]. | Station (10.33, 37.74; in town of Debre Markos) reported much lower than CHIRP and CHPClim, in the same way it reported low for August 2015. Station (8.86, 39.92; in town of Metehara Merti, near Addis Ababa) also reported much lower than CHIRP and CHPClim. ARC2 tells a similar story; ARC2 dictates the area having received 200-300mm[http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jul2015-Jul2015_af_clim.gif]. ARC2’s anomaly map for July also roughly matched CHIRPS’ anomaly map, at a decrease of around -200m of normal[http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jul2015-Jul2015_af_anom.gif]. | ||
− | One report stated | + | <br> |
+ | One report stated [http://harambeetoday.org/index.php/economics/item/1597-el-nino-threats-may-worsen-food-insecurity-in-ethiopia/1597-el-nino-threats-may-worsen-food-insecurity-in-ethiopia “July’s seasonal rains did not come this year…” ], while [http://allafrica.com/stories/201508172221.html another confirmed] that "the rain condition was ok for the first ten days during the month of June. It gradually declined and we started experiencing shortage in rain in July. But conditions are good in August…it has occurred several times in the past, including in 2005.”. The July rains (that didn’t come this year) tend to climb north-east across the highlands throughout June, July and August, the area showing a shortage in rain. It seems the stations are correct and Ethiopia experienced a drought this summer. However, due to the decreased number of stations since August 2014, it is possible that these stations are overestimating the level of drought. | ||
− | '''Sudan''' | + | '''Sudan''': CHIRPS and CHIRP both indicate that in southwest Sudan, June was had normal rainfall, July was dry, and August returned to normal rainfall (aka summer rains came late). The proximity of the area to the Ethiopian highlands means it followed similar trends as seen in Ethiopia, as backed up by previous reports. HOWEVER, CHIRPS completely missed mass flooding in Darfur in July[https://www.dabangasudan.org/en/all-news/article/rains-damage-more-than-1-500-homes-in-darfur-camps]; for that same time of mass flooding, CHIRPS reported a ''decrease'' in rainfall. |
− | CHIRPS and CHIRP both indicate that in southwest Sudan, June was had normal rainfall, July was dry, and August returned to normal rainfall (aka summer rains came late). The proximity of the area to the Ethiopian highlands means it followed similar trends as seen in Ethiopia, as backed up by previous reports. HOWEVER, CHIRPS completely missed mass flooding in Darfur in July[https://www.dabangasudan.org/en/all-news/article/rains-damage-more-than-1-500-homes-in-darfur-camps]; for that same time of mass flooding, CHIRPS reported a ''decrease'' in rainfall. | ||
− | '''Burkina Faso''' | + | '''Burkina Faso''': We may have a faulty station (or stations) in northeast Burkina Faso. The two stations are located at (14.03, -0.033; stn 277004); one reported 482 mm of rain, CHIRP reported 129, and CHPClim 117; the other station seems to bring the number ranges from 0-10. These stations combined, though, are driving up the CHIRPS rainfall estimates. |
− | We may have a faulty station (or stations) in northeast Burkina Faso. The two stations are located at (14.03, -0.033; stn 277004); one reported 482 mm of rain, CHIRP reported 129, and CHPClim 117; the other station seems to bring the number ranges from 0-10. These stations combined, though, are driving up the CHIRPS rainfall estimates. | + | <br> |
One report does state that regular rain started mid-July [http://www.fews.net/west-africa/burkina-faso]. However, most reports indicate that the northeastern area had decreased, not increased, rainfall in July [http://reliefweb.int/sites/reliefweb.int/files/resources/wfp276458.pdf]; NOAA/FEWS NET reports for July show dryness as well in the west and southwest [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150702] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150709] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150716] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150723] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150730]. | One report does state that regular rain started mid-July [http://www.fews.net/west-africa/burkina-faso]. However, most reports indicate that the northeastern area had decreased, not increased, rainfall in July [http://reliefweb.int/sites/reliefweb.int/files/resources/wfp276458.pdf]; NOAA/FEWS NET reports for July show dryness as well in the west and southwest [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150702] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150709] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150716] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150723] [http://reliefweb.int/sites/reliefweb.int/files/resources/Global%20Weather%20Hazard-150730]. | ||
− | '''Guatemala''' | + | '''Guatemala''': CHIRPS is fairly accurately picking up a drought in Guatemala, but may be overestimating it in some areas. Station (-88.59, 15.74) has a high value (154) compared to CHIRP (104), and yet CHIRPS is drug down for that pixel (84). There is a neighboring station in Honduras that has an extremely low station value that is most likely over-influencing CHIRPS, creating exaggerated estimates of low rainfall for Guatemala. Reports confirm the drought's severity: TRMM (anomaly and time series) shows drought in the north and west of the nation (-100- -200), in concurrence with CHIRPS (-200- - 300), and written articles confirm the precip data [https://www.stratfor.com/analysis/central-america-how-drought-affects-migration] [ftp://ftp.cpc.ncep.noaa.gov/fews/cent_amer_threats/camerhaz20150723.pdf]. CHIRPS is picking up the drought around El Salvedor and in southern Honduras, but again might be overestimating the drought in Guatemala. |
− | CHIRPS is fairly accurately picking up a drought in Guatemala, but may be overestimating it in some areas. Station (-88.59, 15.74) has a high value (154) compared to CHIRP (104), and yet CHIRPS is drug down for that pixel (84). There is a neighboring station in Honduras that has an extremely low station value that is most likely over-influencing CHIRPS, creating exaggerated estimates of low rainfall for Guatemala. Reports confirm the drought's severity: TRMM (anomaly and time series) shows drought in the north and west of the nation (-100- -200), in concurrence with CHIRPS (-200- - 300), and written articles confirm the precip data [https://www.stratfor.com/analysis/central-america-how-drought-affects-migration | + | <br> |
− | + | [http://floodlist.com/america/350-evacuated-after-heavy-rain-causes-landslide-in-guatemala Flooding occurred in July in Chinaulta (southeast)] ; CHIRP and TRMM both reported higher than average rainfall in that area, but CHIRPS reported higher rainfall only along the coast and drought in Chinaulta. The underestimation of precipitation by CHIRPS might again be the influence of the station in the north of Honduras. It seems that stations are having too high an influence, especially when they are all reporting the same phenomenon and are then influencing another with the opposite (ex//drought all around, but flooding in Chinaulta). | |
− | |||
− | '''Honduras''' | + | '''Honduras''': ''see above'' |
− | ''see above'' | + | <br> |
CHIRPS shows a more extreme drought in the West than CHIRP shows, but TRMM reports similarly, suggesting CHIRPS is accurately reporting the drought and CHIRP underestimated it[http://www.cpc.ncep.noaa.gov/products/fews/central_america/anomalies/anomzoom_07.gif]. | CHIRPS shows a more extreme drought in the West than CHIRP shows, but TRMM reports similarly, suggesting CHIRPS is accurately reporting the drought and CHIRP underestimated it[http://www.cpc.ncep.noaa.gov/products/fews/central_america/anomalies/anomzoom_07.gif]. | ||
− | |||
− | |||
''Contributors: Emily Williams; 9/23/15 - 9/24/15'' | ''Contributors: Emily Williams; 9/23/15 - 9/24/15'' | ||
+ | ===June 2015=== | ||
− | + | '''Honduras''': CHIRPS reported Honduras having experienced flooding around the capital and the northern Caribbean coast. The flooding in the center was [http://floodlist.com/america/nicaragua-honduras-floods-8-dead-june-2015 backed up by reports]. However CHIRP reporting higher rainfall than the stations. Mid-June, Hurricane Bill formed along Honduras's northern coast, which could account for the flooding. However, NOAA/FEWS does not report any flooding, and in fact [ftp://ftp.cpc.ncep.noaa.gov/fews/cent_amer_threats/camerhaz20150625.pdf reports dryness along the Southwest of the country]. | |
− | + | '''Nicaragua''': CHIRPS picked up some significant rainfall (anomaly of +30-50mm) along Western Nicaragua. It was confirmed that the flooding seen in CHIRPS is roughly the pattern of flooding experienced on the ground [http://floodlist.com/america/nicaragua-honduras-floods-8-dead-june-2015]. NOAA/FEWS did not pick up this flooding in their reports [ftp://ftp.cpc.ncep.noaa.gov/fews/cent_amer_threats/camerhaz20150625.pdf]. | |
− | ''' | + | '''Costa Rica''': Costa Rica similarly experienced [ftp://ftp.cpc.ncep.noaa.gov/fews/cent_amer_threats/camerhaz20150625.pdf significant flooding in much of the country], also missed by NOAA/FEWS. However, it was picked up by TRMM. |
− | |||
− | ''' | + | '''Ethiopia''': CHIRPS reporting lower-than-average rainfall for Ethiopia's highlands, which seems to be in line with the summer's drought. Compared to [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jun2015-Jun2015_af_anom.gif ARC1 estimates], CHIRPS might be overestimating the drought at this point, but it is nonetheless present. NOAA/FEWS have not captured the severity and distribution, and even declared "no drought" in Ethiopia at the end of June [ftp://ftp.cpc.ncep.noaa.gov/fews/threats/afrhaz20150625.pdf]. |
− | CHIRPS | ||
− | ''' | + | '''Kenya''': Flooding in Nairobi that CHIRPS didn't catch [http://allafrica.com/view/group/main/main/id/00037158.html]. Other general trends in climate are echoed by ARC1 [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jun2015-Jun2015_af_anom.gif]. There is a station in the southeast of Kenya (in the town of Mombasa) which reported a higher-than-average value for CHIRPS, but a low station value; this same area was subject to flooding [http://www.dailymail.co.uk/wires/reuters/article-3126045/Mombasa-draws-master-plan-combat-worsening-flooding.html]. |
− | |||
− | |||
− | |||
− | |||
− | |||
− | |||
− | Flooding in Nairobi that CHIRPS didn't catch [http://allafrica.com/view/group/main/main/id/00037158.html]. Other general trends in climate are echoed by ARC1 [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Jun2015-Jun2015_af_anom.gif]. There is a station in the southeast of Kenya (in the town of Mombasa) which reported a higher-than-average value for CHIRPS, but a low station value; this same area was subject to flooding [http://www.dailymail.co.uk/wires/reuters/article-3126045/Mombasa-draws-master-plan-combat-worsening-flooding.html]. | ||
''In May, flooding in Mombasa, picked up by CHIRPS [http://www.standardmedia.co.ke/article/2000164176/mombasa-in-flood-chaos-as-heavy-rains-lash-coast].'' | ''In May, flooding in Mombasa, picked up by CHIRPS [http://www.standardmedia.co.ke/article/2000164176/mombasa-in-flood-chaos-as-heavy-rains-lash-coast].'' | ||
− | '''Madagascar''' CHIRPS reporting higher-than-average rainfall along Madagascar's eastern coastline | + | '''Madagascar''': CHIRPS reporting higher-than-average rainfall along Madagascar's eastern coastline. |
− | |||
− | |||
− | ''' | + | '''Senegal''': One station is reporting an abnormally low value (7mm) for June, when CHIRP puts it around 100mm. However, Arc2 shows a decline in rainfall for that area in June [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_Saraya_Senegal.gif]. The station looks okay for other months; may be good to keep an eye on though. |
− | ''' | + | '''Mali''': Station reporting a low value (99) in an area that tends to get 127; CHIRPS is reporting 139 for this area. The area is on the slope of a mountain, though, and on a rain gradient, so it's likely that the station is correct. |
+ | '''Ghana''': CHIRPS failed to pick up flooding in coastal town of Accra during [http://www.irinnews.org/report/101630/ghana-hard-hit-by-flooding-once-again "biggest storm in the past 20 years"]. The station failed to pick it up, which is probably why CHIRPS didn't get it (station said 154mm, while the report said 250 mm in only the first 3 days. | ||
''Contributors: Emily Williams; 9/28/15'' | ''Contributors: Emily Williams; 9/28/15'' | ||
+ | ===May 2015=== | ||
− | + | '''Guatemala''': There is a station in the far east of Guatemala which is reporting a significantly high rainfall value, but CHIRPS is reporting a value closer to CHIRP and CHPClim. There is, however, a station very near in Honduras which has an extremely low value which could be over-influencing CHIRPS at our station's location. | |
− | + | <br> | |
− | |||
− | |||
− | '''Guatemala''' | ||
− | There is a station in the far east of Guatemala which is reporting a significantly high rainfall value, but CHIRPS is reporting a value closer to CHIRP and CHPClim. There is, however, a station very near in Honduras which has an extremely low value which could be over-influencing CHIRPS at our station's location. | ||
TRMM total rainfall anomolyis reporting lower-than-average rainfall for that period of time, but then a positive anomaly for June which aligns with our station. | TRMM total rainfall anomolyis reporting lower-than-average rainfall for that period of time, but then a positive anomaly for June which aligns with our station. | ||
+ | <br> | ||
However, TRMM's total rainfall time series from station values agrees with our station that is reporting higher rain[http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/camerica/PuertoBarrios_Guatemala.gif], and disagrees with the Honduras station. | However, TRMM's total rainfall time series from station values agrees with our station that is reporting higher rain[http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/camerica/PuertoBarrios_Guatemala.gif], and disagrees with the Honduras station. | ||
− | '''Honduras''' The most notable station this month has a value of 1 in the North West of the country. However, the country as a whole had an anomaly of 100-200mm, lining up with TRMM values. The station is in a valley surrounded by mountains so it might be correct in that it received no rainfall there, but is something to keep an eye on. | + | '''Honduras''': The most notable station this month has a value of 1 in the North West of the country. However, the country as a whole had an anomaly of 100-200mm, lining up with TRMM values. The station is in a valley surrounded by mountains so it might be correct in that it received no rainfall there, but is something to keep an eye on. |
− | '''Tajikistan''' CHIRPS to picked up flooding in the Khatlon province of Tajikistan [http://reliefweb.int/disaster/fl-2015-000055-tjk]. | + | '''Tajikistan''': CHIRPS to picked up flooding in the Khatlon province of Tajikistan [http://reliefweb.int/disaster/fl-2015-000055-tjk]. |
− | '''Kenya''' CHIRPS is showing a high quantity of rain along the southern coast and boarder of Kenya. The ARC2 time series points | + | '''Kenya''': CHIRPS is showing a high quantity of rain along the southern coast and boarder of Kenya. The ARC2 time series points [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_Mombasa_Kenya.gifback up this claim], in addition to the [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_May2015-May2015_af_anom.gifMay estimates]. Additionally, the RFE anomaly backs up the claim of high rainfall in the south, and low in the northwest [http://earlywarning.usgs.gov/fews/product/119]. |
− | '''Tanzania''' CHIRPS and ARC2 both show an high positive anomaly of rain in Tanzania in the SE [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_May2015-May2015_af_anom.gif]. The RFE for the end of the month shows a negative anomaly for the same area [http://earlywarning.usgs.gov/fews/product/119], but a positive anomaly for the beginning [http://earlywarning.usgs.gov/fews/product/119]. Reports of flooding back up this claim [http://floodlist.com/africa/tanzania-floods-dar-es-salaam-may-2015]. | + | '''Tanzania''': CHIRPS and ARC2 both show an high positive anomaly of rain in Tanzania in the SE [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_May2015-May2015_af_anom.gif]. The RFE for the end of the month shows a negative anomaly for the same area [http://earlywarning.usgs.gov/fews/product/119], but a positive anomaly for the beginning [http://earlywarning.usgs.gov/fews/product/119]. Reports of flooding back up this claim [http://floodlist.com/africa/tanzania-floods-dar-es-salaam-may-2015]. |
− | '''Uganda''' CHIRPS shows dryness through much of the country except for a high incidence of rain in the south near the lake. RFE and ARC2 show similar trends. ARC2 time series shows both the dryness just north of the lake (in correspondence with the low station value) and then the wetness to the west of the lake [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_Masaka_Uganda.gif]. CHIRPS is correct for May. | + | '''Uganda''': CHIRPS shows dryness through much of the country except for a high incidence of rain in the south near the lake. RFE and ARC2 show similar trends. ARC2 time series shows both the dryness just north of the lake (in correspondence with the low station value) and then the wetness to the west of the lake [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_Masaka_Uganda.gif]. CHIRPS is correct for May. |
− | '''Madagascar'''Dry station on east (central/north) coast; ARC2 time series shows same dryness [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_Toamasina_Madagascar.gif]; ARC2 month shows the same [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_May2015-May2015_af_anom.gif]. However, CHIRPS showing a lot of wetness along the rest of the eastern coast, but not backed up by ARC2. ''It seems like the coastal stations have been overreporting rainfall for May-July.'' ARC2 timeseries and month-estimates, RFE, and reports [http://reliefweb.int/report/madagascar/situation-update-locust-crisis-madagascar-4-june-2015] show less rainfall than CHIRPS. | + | '''Madagascar''': Dry station on east (central/north) coast; ARC2 time series shows same dryness [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_Toamasina_Madagascar.gif]; ARC2 month shows the same [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_May2015-May2015_af_anom.gif]. However, CHIRPS showing a lot of wetness along the rest of the eastern coast, but not backed up by ARC2. ''It seems like the coastal stations have been overreporting rainfall for May-July.'' ARC2 timeseries and month-estimates, RFE, and reports [http://reliefweb.int/report/madagascar/situation-update-locust-crisis-madagascar-4-june-2015] show less rainfall than CHIRPS. |
− | '''Burkina Faso''' Country received high rainfall in West according to RFE and ARC2 [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_BoboDioulasso_Burkina.gif] [http://earlywarning.usgs.gov/fews/product/118]. Station in CHIRPS shows the same story; however CHIRP is showing dryness across the country. ARC May estimates agree there should be more rainfall in the West. Seems like this station is being drowned out by dry stations and should have a higher influence on the area to make it come up as wet instead of dry/average. | + | '''Burkina Faso''': Country received high rainfall in West according to RFE and ARC2 [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_180day_ptts_BoboDioulasso_Burkina.gif] [http://earlywarning.usgs.gov/fews/product/118]. Station in CHIRPS shows the same story; however CHIRP is showing dryness across the country. ARC May estimates agree there should be more rainfall in the West. Seems like this station is being drowned out by dry stations and should have a higher influence on the area to make it come up as wet instead of dry/average. |
− | '''Mali''' Station in south of country shows wet values but is also being drowned out by surrounding drought area, making the area look average instead of wet. | + | '''Mali''': Station in south of country shows wet values but is also being drowned out by surrounding drought area, making the area look average instead of wet. |
− | == | + | ===April 2015=== |
− | + | '''Cote D'Ivoire and Ghana''': CHIRPS is struggling again to pick up anomalous wet periods when surrounded by dry areas. There were stations reporting wet values surrounded by stations reporting dry values, and CHIRPS didn't allow for the high value to significantly impact the area around it; RFE [http://earlywarning.usgs.gov/fews/product/118] and ARC [http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/cf_test2/africa_arc/africa_arc_Apr2015-Apr2015_af_anom.gif] both indicate wetness for the southern part of the country, which CHIRPS under-reports. | |
− | + | '''Eastern Africa''': CHIRPS did a good job in picking up the significant wetness stretching along the Eastern coast of Africa. ARC and CHIRPS are in agreement, where RFE is reporting much drier conditions throughout Kenya and parts of Tanzania. | |
− | |||
− | '''Eastern Africa''' CHIRPS did a good job in picking up the significant wetness stretching along the Eastern coast of Africa. ARC and CHIRPS are in agreement, where RFE is reporting much drier conditions throughout Kenya and parts of Tanzania. | ||
'''Kenya''' Kenya was fairly wet in August. RFE and ARC show wet conditions in northern and western Kenya, though drier conditions in southern and eastern Kenya. CHIRPS isn't picking up the dryness. All the z-scores that stood out, however, are for stations that reported lower rainfall values than CHIRPS shows. Seems CHIRPS isn't heeding local station signals enough and relies too strongly to influences of surrounding precipitation conditions. | '''Kenya''' Kenya was fairly wet in August. RFE and ARC show wet conditions in northern and western Kenya, though drier conditions in southern and eastern Kenya. CHIRPS isn't picking up the dryness. All the z-scores that stood out, however, are for stations that reported lower rainfall values than CHIRPS shows. Seems CHIRPS isn't heeding local station signals enough and relies too strongly to influences of surrounding precipitation conditions. | ||
− | '''Honduras''' There is a station that received nearly zero rain in April, but this is backed up by the RFE time series points | + | '''Honduras''': There is a station that received nearly zero rain in April, but this is backed up by the RFE time series points. |
− | |||
− | |||
− | ''' | + | '''Dominican Republic''': CHIRPS picked up that very little rain fell along the northern and eastern coasts of the Dominican Republic. |
+ | '''Tajikistan''': CHIRPS shows lower-than-average rainfall in north along ridgeline, and higher-than-average rainfall in the western-central portion of the country. Stations are reporting higher values for rain than the weather records [http://www.wunderground.com/history/airport/UTDD/2015/4/16/MonthlyHistory.html?req_city=Dushanbe&req_state=&req_statename=Tajikistan&reqdb.zip=00000&reqdb.magic=1&reqdb.wmo=38836] (130 vs 71). Difficult to verify if CHIRPS is accurately reporting or not due to limited precipitation data to compare with. Would be good to have NOAA's RFE png blown up a bit to see better whether our results correlate [http://earlywarning.usgs.gov/fews/product/106]. | ||
''Contributors : Emily Williams, 10/16/15'' | ''Contributors : Emily Williams, 10/16/15'' |
Latest revision as of 10:07, 1 November 2024
CHIRPS v2.0 monthly Reality Checks
CHIRPS Reality Checks (rchecks) occur across the many steps to create CHIRPS and on the final product itself.
Contents
- 1 Background
- 2 Helpful Links
- 3 Rchecks Highlights
- 3.1 September 2024
- 3.2 August 2024
- 3.3 July 2024
- 3.4 June 2024
- 3.5 May 2024
- 3.6 April 2024
- 3.7 March 2024
- 3.8 February 2024
- 3.9 January 2024
- 3.10 December 2023
- 3.11 November 2023
- 3.12 October 2023
- 3.13 September 2023
- 3.14 August 2023
- 3.15 July 2023
- 3.16 June 2023
- 3.17 May 2023
- 3.18 April 2023
- 3.19 March 2023
- 3.20 February 2023
- 3.21 January 2023
- 3.22 December 2022
- 3.23 November 2022
- 3.24 October 2022
- 3.25 September 2022
- 3.26 August 2022
- 3.27 July 2022
- 3.28 June 2022
- 3.29 May 2022
- 3.30 April 2022
- 3.31 March 2022
- 3.32 February 2022
- 3.33 January 2022
- 3.34 December 2021
- 3.35 November 2021
- 3.36 October 2021
- 3.37 September 2021
- 3.38 August 2021
- 3.39 July 2021
- 3.40 June 2021
- 3.41 May 2021
- 3.42 April 2021
- 3.43 March 2021
- 3.44 February 2021
- 3.45 January 2021
- 3.46 December 2020
- 3.47 November 2020
- 3.48 October 2020
- 3.49 September 2020
- 3.50 July 2020
- 3.51 August 2020
- 3.52 July 2020
- 3.53 June 2020
- 3.54 May 2020
- 3.55 April 2020
- 3.56 March 2020
- 3.57 February 2020
- 3.58 January 2020
- 3.59 December 2019
- 3.60 November 2019
- 3.61 October 2019
- 3.62 September 2019
- 3.63 August 2019
- 3.64 July 2019
- 3.65 June 2019
- 3.66 May 2019
- 3.67 April 2019
- 3.68 March 2019
- 3.69 February 2019
- 3.70 January 2019
- 3.71 December 2018
- 3.72 November 2018
- 3.73 October 2018
- 3.74 September 2018
- 3.75 August 2018
- 3.76 July 2018
- 3.77 June 2018
- 3.78 May 2018
- 3.79 April 2018
- 3.80 March 2018
- 3.81 February 2018
- 3.82 January 2018
- 3.83 December 2017
- 3.84 November 2017
- 3.85 October 2017
- 3.86 September 2017
- 3.87 August 2017
- 3.88 July 2017
- 3.89 June 2017
- 3.90 May 2017
- 3.91 March 2017
- 3.92 February 2017
- 3.93 January 2017
- 3.94 December 2016
- 3.95 November 2016
- 3.96 October 2016
- 3.97 September 2016
- 3.98 August 2016
- 3.99 July 2016
- 3.100 June 2016
- 3.101 May 2016
- 3.102 April 2016
- 3.103 March 2016
- 3.104 February 2016
- 3.105 January 2016
- 3.106 December 2015
- 3.107 November 2015
- 3.108 December 2015
- 3.109 October 2015
- 3.110 September 2015
- 3.111 August 2015
- 3.112 September 2015
- 3.113 July 2015
- 3.114 June 2015
- 3.115 May 2015
- 3.116 April 2015
Background
A team of data analysts routinely quality check each month’s CHIRPS data before its release. This page documents major points of these Reality Checks. The Rchecks Highlights section contains information that CHIRPS users may find helpful, for example, notes about major rainfall events shown by the data and validation for some.
Rcheck is a hands-on approach that helps enable a quality product for hazards monitoring and other scientific activities. In Reality Checks we examine the data visually via the Early Warning Explorer and separately using calculated statistics. Ancillary information, such as FEWS NET datasets, news reports, and government meteorological reports, are frequently used in the process. Rchecks has been successful in: 1) Validating anomalous wet and dry events around that world as shown by CHIRPS, 2) catching inaccurate station reports that would have otherwise negatively influenced the dataset, such as creating false droughts, 3) checking that the semi-automated flow CHIRPS data creation is working correctly, 4) identifying weaknesses and strengths of the algorithm and data inputs, which helps in planning improvements in future versions.
Historic vs Operational rchecks
There are two basic types of rchecks: historic and operational.
- Historical: Historic looks across the whole timeseries of CHIRPS (1981-present)
- Operational: Operational is designed to spot check our products are they are produced.
- Does this station value fall within expected range?
- Do the anomaly fields have a reasonable distribution? (not all negative)
View individual stations time series
- The center pixel of the station's 11x11 pixel representation is assigned the anchor station's sequence number in the CSCD1 database. Clicking on this pixel in the EWX will list the seqnum in the lower left corner of the map pane. Note that this may not be the station that was actually used if there was missing data and a nearby station filled in the value. The source seqnum of the station can be obtained with the follow SQL command:
- select * from station where seqnum=xxx
- then the source seqnum can be used to get the name of the source like this:
- select * from source where seqnum=xxx
- then precipitation table can be selected from the following list of precip tables:
- daily_precip_conagua
- daily_precip_fgsod
- daily_precip_fits
- daily_precip_ghcn
- daily_precip_ideam
- daily_precip_sasscal
- then the following command will return the station time series:
- select * from daily_precip_sasscal where station_seqnum=xxx order by date desc
- Note that the filled value is the precipitation value that is used in CHIRPS. This is the sum of the daily "value" column with any missing data filled in with the mean of the values that do exist in the table.
Helpful Links
The following are resources that are helpful for conducting monthly CHIRPS Reality Checks. These include links to CHC resources (e.g. data viewers & details from Rchecks) and other products that are used for comparisons.
CHC resources
Global products
- Global PERSIANN data viewer Suggestion: Compare CHIRPS to Monthly PERSIANN, PERSIANN-CCS, and PERSIANN-CDR totals
- Global Accuweather rainfall stations Suggestion: Search for a nearby city and the click the month button, then select the month and then the settings button (last on right) to see daily precip totals
- Global NOAA Climate Products: Choose zone of the world for special products (Central Asia, South Asia, Africa, Central America & Caribbean)
- Global FEWS Data Portal
- WMO Links to other National Met Services:
- Climate-Data.org Website with climatology info. Googling a city name + climatology might be helpful also
Africa products
- Africa FEWS Archived Hazards/Threats
- East Africa IGAD website
- Kenya Kenya Met Department. Here is a link to dekadal monitoring reports https://meteo.go.ke/forecast/agrometeorological-bulletins.
- Ethiopia NMA Maproom
- Senegal ANACIM: Seasonal rainfall accumulation Seasonal rainfall anomaly
Central and South America products
- Central America and Caribbean CMORPH precipitation and more
- South America CMORPH precipitation and more
- Central America FEWS Archived Hazards/Threats
- Brazil INMET: Click the Mapas de Precipitacao tab and then the Plus button at the bottom of the map and an end date and time period can be selected (30 dias).
- Argentine Servicio Meteorologico Nacional: Click on Precipitacion Observada or Precipitación Estimada links.
Asia products
- South Asia RFE2.0 precipitation and more
- Pakistan National Drought Monitoring Centre: Maps of monthly rainfall, anomalies, and SPI to compare to.
- India CRIS from India Met Dept: Variety of products. Rainfall graphs helpful b/c many maps show cumulative rains over month+ periods.
Rchecks Highlights
September 2024
Central Europe In mid-September, Storm Boris swept through central Europe and dumped well over a month’s worth of rain within several days. Authorities reported that they recorded the heaviest rainfall in 100 years on September 15th. At least 17 people were killed during the floods in Austria, Poland, the Czech Republic and Hungary. More information about Storm Boris is available here.
Hungary Despite reports of record-high rainfall throughout the region, monthly rainfall totals at Hungary stations were slightly below-average throughout the entire country. These are all GTS stations. The resulting map of precipitation anomalies shows Hungary as a pocket of below-normal rainfall surrounded by highly above-average rains. With station values overlaid, one can clearly see a difference between stations within Hungary's border and stations outside the border. We elected to exclude Hungary rainfall stations from CHIRPS final for this month.
Morocco, Algeria, Tunisia, and Libya CHIRPS shows above-average rainfall in these areas due to satellite and station inputs. A NASA article names the cause as an extratropical cyclone that brought substantial rain during Sep 7th and 8th. Satellite imagery shows that the rain filled up desert lakes in the northwestern Sahara that are usually dry.
Rchecks plots Stats fall with normal ranges with the exception of the Great Lakes region. There are a large number of stations reporting high negative z-scores throughout this area.
CHIRPS Final versus CHIRPS Prelim This map shows the difference between Prelim data and Final data, for September 2024.
August 2024
Mali, Niger, Chad Stations captured extreme August rainfall in Mali, Niger, Chad, and elsewhere in the Sahel. High above-normal seasonal rainfall has flooded rivers and communities, leading to many fatalities and severe damages to infrastructure. OCHA describes the August 2024 flooding in West and Central Africa as follows: "In the last two weeks of August alone, 1,590,000 people were affected in the region. The heavy rains recorded in this two-week period affected 12 countries, 7 in terms of displacement of population and 11 for houses destroyed or damaged. From 15 to 30 August, 465 people were reportedly killed and 1,747 others injured. Between 15 and 30 August, an additional 354,000 hectares of agricultural land were affected, making a total area of 380,000 hectares unsuitable for agricultural and livestock production" -September 6th situation overview. According to various sources, over 50 people have been killed and close to a million people affected in Mali. In Niger, at least 94 people have been killed, and more than 137,000 have been displaced due to flooding. The flooding damaged homes and classrooms and resulted in the death of more than 15,000 livestock. In Chad, where impacts have been most severe, at least 341 people have died and 1.5 million have been affected.
Somalia FAO SWALIM station reports are a very important source of accurate CHIRPS rainfall estimation in Somalia. This source has provided reports into CHIRPS for the past 8 years. SWALIM was not able to provide reports for August 2024 CHIRPS data.
Cuba High rainfall amounts are estimated by CHIRPS due mainly to the blending of stations. A station in western Cuba (580 mm) had particularly large influence, and while CHIRP (satellite estimates) were above average, estimated amounts were lower (~250-300mm). The high August 2024 rainfall is consistent with impacts from Tropical Depression 4, which crossed over the area on August 3rd.
Brazil A recurring problem with station reports, identified by Rchecker Seth, is in need of attention. There are numerous stations being identified manually in Rchecks that appear to be too low. Based on evaluation of nearby stations that align with satellite estimates. The issue has been addressed in the past by flagging and permanent omission of certain stations from CHIRPS blending process. At minimum, this will need to happen again. However, introducing an automated filter- crafted especially for this source- is a potential solution that will be discussed. This would be a valuable addition for final CHIRPS v3 historical and ongoing data production.
Rchecks plots All stats are within a normal range.
CHIRPS Final versus CHIRPS Prelim This map shows the difference between Prelim data and Final data, for August 2024.
July 2024
South Africa Southwestern Africa (near Cape Town) had very heavy storms, damage, flooding during July 2024. More on the impacts, which displaced 4,500 people, can be read here. CHIRPS is showing this anomalous high rainfall, due to the blending of 20+ stations in this area. The station reports greatly increased CHIRPS compared to CHIRP (satellite-only estimates).
Panama Only 2 stations reported, which is far less than high station count that we've had during 2023 to 2024.
Brazil Rchecker Seth continues to find numerous stations in Brazil are reporting too-low rainfall. For July 2024, he identified 35 stations. These were omitted from CHIRPS Final.
Rchecks plots There is a new hit CHIRPS maximum, standard deviation and anomaly max in Southern Africa. However, these were verified by news reports from Cape Town. There is also a new high for global CHIRPS - CHIRP but by a very small margin. All else looks bueno.
CHIRPS Final versus CHIRPS Prelim This map shows the difference between Prelim data and Final data, for July 2024.
June 2024
Saudi Arabia Two stations reported moderate rainfall in the desert. These were retained in CHIRPS due to news reports of rainfall in Mina in June 2024.
Panama Numerous stations report over 600 mm of rain and some are 1000+ mm. These are included and substantially increase CHIRPS values, compared to CHIRP. No news reports of flooding were discovered.
Brazil Rchecker Seth continues to find numerous stations in Brazil are reporting too-low rainfall. For June 2024, he identified ~60 stations. These were omitted from CHIRPS Final.
Rchecks plots The South American region contained a new CHIRPS maximum high value of over 2000mm. Previous highs are all under 1500mm. A new anomaly high was also calculated there. Otherwise, all stats fall withing previous boundaries.
May 2024
Switzerland and Italy Automated checks removed a series of large station values from southern Switzerland and northern Italy. However, during reality checks these stations were added back in to CHIRPS, as they correctly identified reported heavy rainfall events that led to flooding throughout the area.
Brazil and Uruguay In southern Brazil and Uruguay, the stations included in CHIRPS captured heavy rains that led to severe flooding. According to [a report from MSF news, "The extreme rainfall and flooding that hit the southern Brazilian state of Rio Grande do Sul isolated and forced the evacuation of whole cities. Roads have been destroyed, bridges knocked out and the main airport, in the capital city of Porto Alegre, is indefinitely closed. More than 460 state municipalities, out of a total of 497, have been hit." CHIRP estimates, in the 200 mm range for the month, were much lower than the values reported at stations, which reached as high as 800 mm. This highlights the importance of in situ observations for accurate depictions of extreme rainfall in gridded satellite rainfall data products.
India and Bangladesh In late May Cyclone Remel hit the coasts of India and Bangladesh and dumped approximately 89 mm of rain, according to news reports. CHIRP and CHIRPS both estimated above average rainfall for May 2024. The stations included in CHIRPS widened the area of estimated anomalous rainfall.
Rchecks plots All statistics ranged within normal bounds except the Latin American region, Z-score mean, which is a recorded a low of -0.9. This is corroborated in a report by the Relief Web International about delayed onset of seasonal rains.
CHIRPS Final versus CHIRPS Prelim A map [1] shows the difference between Prelim data and Final data, for May 2024.
April 2024
Afghanistan and Pakistan Stations blended into CHIRPS captured extreme rainfall values in mid-May that led to [severe flooding, destruction, and loss of life https://floodlist.com/asia/afghanistan-floods-may-2024] in Afghanistan and Pakistan. Of the satellite-only products, IMERG late v6 outperformed CHIRP in capturing the extreme rainfall.
United States CHIRP underestimated rainfall in the Midwest, from Missouri to Pennsylvania. Station values blended into CHIRPS brought up the values 2 to 3 times higher. IMERG late v6 captured the amounts relatively better than CHIRP.
Rchecks plots All stats look good. High CHIRPS values and anomalies meet previous highs but still within reasonable ranges
CHIRPS Final versus CHIRPS Prelim A map [2] shows the difference between Prelim data and Final data, for April 2024.
March 2024
Swaziland Multiple stations in southern Mozambique reported very high rainfall values, associated with impacts from Tropical Storm Filipo. According to OCHA, "...heavy rains in Maputo city and province affected 93,240 people. A few days earlier, Tropical Storm Filipo had already impacted 57,178 people in Sofala, Inhambane, Gaza and Maputo provinces." (March 28, 2024 OCHA). CHIRP estimates were much lower; the blended stations markedly increased CHIRPS final values. Several of these stations had a large effect on CHIRPS v2 in the region, particularly Swaziland, because they are included in the 2nd step of a two-step blending procedure. That effect is reduced in v3.2 beta version, which uses an improved single blending procedure.
Australia CHIRPS shows the impacts of Tropical Cyclone Megan that hammered the northern territories in mid-March. CHIRP predicted ~400mm, CHIRPS ~700mm.
Rchecks plots All statistics look within normal ranges with the exception of South America where CHIRPS max reached an unusual new high but not out of a reasonable range.
CHIRPS Final versus CHIRPS Prelim A map (soon will be here) shows the difference between Prelim data and Final data, for March 2024.
February 2024
Southern Africa drought CHIRPS Final shows extremely dry conditions in a large area spanning major maize production areas in southern Zambia and Zimbabwe, and in southeastern Angola, southern Malawi, and eastern Botswana. A severe dry spell occurred during late January and February, and the minimal to no rains and above-average hot temperatures led to widespread crop failures. Zambia declared a national disaster due to the loss of approximately 1 million hectares of maize crops- about half of their planted areas. The timing of the dry spell coincided with yield-sensitive development stages. In some areas, below-average rainfall in November to early December, 2023, had also forced some farmers in the region to plant a month later than usual. The CHIRPS preliminary data for February 2024 provided early indication that rainfall during this period was extremely low. Very poor rains were confirmed by station reports and FEWS NET/USDA FAS interviews and field visits. In Zimbabwe, ~30 stations reported very low rainfall, many of which ranged from near zero to less than 40 mm for the month. This is just a fraction of typical rainfall in February (~ 150 mm at many of these). Upon the inclusion of these (plus stations from SASSCAL and other sources) into CHIRPS Final, worst on record and close-to worst rankings are indicated for many locations across central Southern Africa. CHIRPS Final shows less than 30% of average February rainfall in southern Zambia, Zimbabwe, Namibia's Caprivi Strip, Botswana, western Mozambique, and southeastern Angola.
Italy Heavy, above average rainfall was recorded throughout northern Italy. A strong storm brought heavy rainfall and flooding to the cities of Milan, Veneto, Emilia-Romagna, and Vicenza. Some areas recorded 188mm in 24 hours. According to reports, the storm was reminiscent of Storm Vaia in 2018 and the 'Great Flood of 2010.' See this link for more about this event.
South Africa After incorporating station data in the area, the CHIRPS Final product shows that February 2024 rainfall was below average across most of South Africa, Lesotho, and eSwatini. Satellite-based estimates (CHIRP and IMERG-Late) overestimated rains in eSwatini and northeastern South Africa (Mpumalanga, northern Free State, Gauteng, Limpopo, North West). Based on reports from South Africa (from stations, interviews, and field visits from FEWS NET/ USDA FAS), the dry conditions in February 2024 negatively impacted rainfed maize. Moisture and heat stress had disrupted cob formation and grain filling in some areas, introducing concerns about impacts on seasonal yields and maize quality in affected areas.
Brazil Rchecks/Seth omitted a large number of stations that made it into the pre-release CHIRPS Final but had rainfall values that appeared to be unrealistic. Of these, 62 stations had values that were identified as being too low and 5 were too high, based on the timing, location, and disagreement from neighboring station reports.
Rchecks plots All statistics look within normal ranges.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for February 2024.
January 2024
Zimbabwe Impressive station coverage in Zimbabwe for January 2024. You can see maps of monthly CHIRPS with station locations overlaid here: Jan 2024, Dec 2023, and for Jan 2023. Beginning in December 2023, the Meteorological Services Department of Zimbabwe began providing 35+ station reports to CHIRPS, and in Jan 2024 there was also a notable increase in the number of GTS stations passing quality control and being blended into CHIRPS (10). In past years, oftentimes these GTS stations have not reported enough days in the month to pass. The recent increase in number of stations in Zimbabwe is exciting for CHIRPS producers and users. The v2 processing involves a two-step blending process, with newer sources being blended in the 2nd step. This means that some of these stations (co-located met agency & GTS) are included in both steps in Jan 2024 CHIRPS v2. The duplicate station and 2nd blending processes will not used in CHIRPS v3.
Argentina A couple of stations reported very high rainfall totals, likely associated with the flooding in Cordoba province. These stations had only a minor effect on CHIRPS Final v2.
Sri Lanka Stations data blended into CHIRPS Final v2 captured the heavy rain that led to flooding. These reports substantially increased CHIRPS rainfall estimates, compared to the satellite-based CHIRP.
Australia Stations data blended into CHIRPS Final v2 captured the heavy rain that led to flooding near Darwin. These reports substantially increased CHIRPS rainfall estimates, compared to the satellite-based CHIRP.
Rchecks plots All stats look good with the exception of the Sahel. Based on the pre-Final CHIRPS, the CHIRPS - CHIRP is much higher than any month previously. The values are very near zero, however, so it isn't of any consequence. Also, this was likely associated with a report at a station that ended up being omitted in CHIRPS Final due to an unreasonably high value for this dry time of year (and no satellite products indicated such an abnormal event).
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for January 2024 (this map will be available ~ Feb 18th).
December 2023
Zimbabwe 37 new stations have been included in CHIRPS in Zimbabwe, in December 2023 CHIRPS Final data. This is exciting. CHIRPS has needed improved station coverage in Zimbabwe for years. These stations should help better capture observed rainfall and topographic patterns, and will be especially important for monitoring impacts of extreme storm events like tropical cyclones. CHIRP tends to underestimate values in such cases, and in recent years there were few stations located in Zimbabwe being blended into CHIRPS. Several years ago CHIRPS began blending in valuable station databases with coverage in Mozambique and other areas of Southern Africa, and this Zimbabwe data contribution is another progressive move in support of high quality, publicly available gridded data that can support agroclimatic monitoring and many other applications.
The following describes some of the Rchecks on these data for December 2023 CHIRPS Final. These new 37 stations reported high rain amounts > 250 for some locations. These were higher than CHIRP amounts. Satellite datasets generally diverged with respect to anomalies, with RFE2 and CHIRP showing generally below average rain for Dec 2023. TAMSAT shows a similar pattern to what these (and other stations) in CHIRPS Final indicated: A wetter-than-average swath stretching across northeastern South Africa, part of Mozambique, and across Zimbabwe from southeast to northwest. Another check on the high values focused on 'are these rain amounts within range of past reports, and in similar geographic pattern?' An adhoc comparison using Zimbabwe station reports in CHIRPS from December in the 1980s, which had with similar good spatial coverage (as shown by the EWX Rchecks layer), determined that yes, such amounts were reasonable. Similarly, this was indicated by standardized anomalies at the stations, which were high but not outside the bounds of what we see in this type of comparison; i.e. compared to CHIRPS history, the wettest of the stations in this set had z scores ~ 2.5. Confirmation that these station reports seemed reasonable also came from examination of the "Anchors" Rchecks layer. This shows what CHIRPS would look like if only the Anchor stations were blended (i.e. not including this set of stations or the set from MZ and some of SASSCAL). The answer was that, even without blending these Zimbabwe station reports, a similar wet spatial pattern is present. In other words, these stations are giving reports that are congruent with other station-blended data. Finally, active rainfall has been expected and reported in the area during December-early January. This news article notes this for northern Zimbabwe.
Tanzania Stations capture extreme rainfall amounts in western and northern Tanzania from a severe storm in early December. Heavy rain in the area triggered flooding and landslides to gush down steep slopes of Mount Hanang, and into areas around the towns of Katesh and Gendabi. See Floodlist for more information.
Australia In northern Queensland, there are prominent rainfall amounts in CHIRP, but the blended stations in CHIRPS Final notably increased estimates. In mid December, Tropical Cyclone Jasper brought heavy rainfall and flooding. According to the BBC, the "extreme weather driven by [the cyclone] dumped a year's worth of rain on some areas."
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for December 2023.
CHIRPS v3 In Honduras, Dec 2023 data, there is an unnatural linear boundary in rainfall in v2. In contrast, it looks great in v3 here, presumably due to a difference in the newer chpclim.
Rchecks plots: All stats look within normal ranges.
November 2023
Somalia Extreme rainfall in Somalia in November 2023 led to catastrophic flooding. See this AP video for a glimpse of the results: 1.7 million people impacted, standing water in streets, and difficult access to clean water. CHIRPS shows extremely high, record-breaking amounts for November 2023, due to the blending of FAO SWALIM stations that reported extreme high values. Several reported 400+ mm for November 2023. One in Gedo reported 775mm. Strong positive Indian Ocean Dipole and El Nino conditions were responsible for producing extreme wet conditions. When comparing the 2023 rainfall to other historic rain seasons, it is important to keep in mind is that there is a high level of uncertainty around extreme rains in the past. This is due to the absence of reporting stations in the same locations and across Somalia. The historic 1997 extreme season, which is the most comparable to 2023, is an example. According to CHIRP v2 and v3 estimates in Nov 1997 vs. 2023, satellite estimates suggests that southern Gedo and an area to the south of there received higher amounts in Nov 1997 than in Nov 2023. Based on what CHIRPS Rchecks for v2/v3 show, there were no reporting stations in Somalia CHIRPS data in 1997. Without in situ reports to blend with the satellite estimates, the 1997 values could be underestimates of actual amounts. The Nov 2023 data will be ranked as wettest in CHIRPS v2 Nov. history, but beneath that is an unfortunate discrepancy in when there were stations reporting (2023) versus when there weren't (1997). This is an example of the great challenges in tracking extreme rainfall, especially in data sparse areas.
Ethiopia The second-blending processing step in v2 has produced vastly different (much much higher!) rainfall estimates in Nov 2023 in southeastern Ethiopia, compared to what would be expected based on Ethiopia reports and satellite estimates. This can be seen from comparing the anchor station and 2nd blend rchecks layers. The anchor stations layer shows what it looks like before second-blending. This case is extreme in that it produces higher values in v2 than in v3, wherein v2 is estimating very high values (400-600 mm) and much higher rain (2x higher) than v3 here. The artifact is not surprising-- the FAO SWALIM reports in Somalia are blended in a second step, after the Ethiopia NMA stations have already been blended. The SWALIM stations are reporting extreme high rainfall values, and their influence in propagated into "nearby" areas in rainfall estimation. In the past, some artifact situations have been avoided in v2 final data by omitting one or several of the extreme stations, while making sure that the impact in local (at-station) area is minimized.
Brazil High rainfall in southern Brazil that caused flooding was not captured in CHIRP v2 but was somewhat captured in CHIRP v3 beta. Definitely captured by stations and CHIRPS v2/v3. CHIRPS v2 has a "crop circle" of higher rain due to duplicate stations; CHIRPS v3 beta is more natural looking.
CHIRPS v3 V3 beta overestimates out-of-season rain over northern Africa. A known feature. Some positive feature in v3 is that a second-blending step, and multiple use of same station, are not used in processing.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for November 2023.
Rchecks plots: All stats look within normal ranges.
October 2023
Somalia, Ethiopia, Kenya Stations in CHIRPS Final markedly increased rainfall in October in southern Somalia, northeastern Kenya, and southeastern Ethiopia, compared to Preliminary data. These helped CHIRPS data better reflect the extreme wet conditions brought about by positive Indian Ocean Dipole and El Nino conditions. Preliminary data, which is mainly based on CHIRP here, underestimated the rainfall amounts compared to other near real time monitoring products and observations. The most extreme station report for October was in Bay (Baidoa), Somalia, provided by FAO SWALIM. This station reported 601 mm for the month, and that the rains were extreme through the month. In Oct 1-10, 11-20, and 21-31, it rained 197.0 mm, 135.5mm, and 268.5 mm, respectively. Heavy rains continued into November, and have led to highly destructive flooding in northern Kenya and along the Juba River in Somalia. From Floodlist: The United Nations Office for the Coordination of Humanitarian Affairs (UN OCHA) reports that since October, floods have affected more than 706,100 people in Somalia, mostly in South West, Hirshabelle, Jubaland and Galmudug states. At least 14 people have lost their lives.
Brazil High precipitation that lead to severe flooding in Santa Catarina was much better estimated after stations were blended into CHIRPS Final, compared to CHIRP, Final is still underestimating the values reported at some very wet stations.
Dominica and Guadeloupe CHIRP and CHIRPS captured the high rainfall from Tropical Storm Phillipe that led to major flooding across these islands. This is in contrast to Mexico, where storm activity was not well captured by CHIRP (but was by the blending of stations into CHIRPS Final).
CHIRPS processing notes During this Rchecks, a beta version of CHIRPS v3 (v3.2) was also examined, for purposes of checking station quality and getting more eyes on what that data looks like. For October 2023, and many other months/year, the v3.2 data shows an erroneous precipitation feature in the Sahel/Sahara/North Africa region that is also in some other satellite products (in this month IMERG-Late, Persiann-CCS, ARC2, and RFE2), but not the CHIRPS operational v2. In this month the estimated precipitation pattern spans from east Niger to south Libya, associated with the beta CHIRP estimates, which are not as directly tied to climatology as they were in CHIRPS v2 (thereby limiting estimated rain in dry areas and seasons. Other things noted by Rcheckers include: The much higher estimated rainfall amounts in the beta CHPclim in central Guatemala, compared to the CHPclim used in CHIRPS v2. Different stations were excluded from the automated "too big too small" screening step- associated with different CHIRP values used in that step as well as different "anchor locations" (more in v3 beta) used in station blending. An undercatch "correction", which is planned to be implemented in v3 and is used in the beta, resulted in the extreme Somalia report being modified for v3 to be 643 mm (25.3") instead of the observed 601 mm (23.7"). In southern Brazil, where v2 data occasionally has circular features, v3 beta had a win over v2 by not showing that feature in this month. In Scotland, rainfall gradient in the beta CHPclim was examined, and in the process a source was discovered that could possibly be useful in the future for incorporating more stations into CHIRPS data.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for October 2023.
Rchecks plots: All stats look within normal ranges.
September 2023
Brazil Flooding and fatalities were widely reported in southern Brazil. Station reports blended into CHIRPS Final had important influence in increasing estimated rainfall values in Rio Grande do Sul state for September 2023. The satellite-based estimate, CHIRP, shows slightly enhanced rain here, and then the stations bump rainfall values up around 600 mm.
Spain Stations improved CHIRP in helping to identify widespread heavy rainfall and flooding in early September. In a 24-hour period to 03 September, the storm, referred to as “Depresión Aislada en Niveles Altos,” or DANA, by Spanish authorities, dumped 217.7 mm of rain in Alcanar and 243.4 mm of rain in Mas de Barberans, both located in Catalonia. The total seen in Mas de Barberans is the highest in 23 years. Other areas of the country also saw significant rainfall totals during the same period, according to figures provided by the State Meteorological Agency AEMET and reported by Floodlist.
Greece, Turkey, and Bulgaria Neither CHIRP nor stations appear to have captured the record breaking rainfall events reported in early September in Greece, Turkey, and Bulgaria. Reports state between 650 and 750 mm of rain fell over Greece in one day, according to Floodlist.
Cameroon Two GTS stations in Cameroon were excluded from blending due to their past inconsistency. During recent months and years, these stations have not reported for enough days of the month to make it past CHIRPS Final quality-control screening and into the blending step of CHIRPS Final. They did report enough this month, and would have had large influence on lowering CHIRPS estimates values due to having quite low reports. Due to their inconsistency, and absence from CHIRPS in the past, September 2023 rainfall patterns from multiple datasets were compared. In northeastern Cameroon, the station in question was not in line with the above-average rainfall indicated by several products (e.g. TAMSAT and IMERG-Late).
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for September 2023.
Rchecks plots: All stats look within normal ranges.
August 2023
Mali CHC received reports from field scientists in Mali that CHIRPS Prelim was under-reporting rainfall in the southwest. The season is reported to have been average, to above average. CHIRP signals agree with these reports, however CHIRPS stations show negative anomalies. These stations were removed to ensure CHIRPS anomaly fields match field reports.
Kenya Four 3D-PAWS Stations have been included into CHIRPS this month. The rainfall totals, anomalies, and z-scores, agree with CHIRP and other source stations pretty well.
Belize A new source for Belize has been added to CHIRPS this month, and has added 17 stations. These stations seem to agree with CHIRP and nearby stations pretty well.
South Korea A new source for South Korea was tested for inclusion in CHIRPS final this month, but CHC decided to hold off and not include those station reports. These were making South Korea much drier than CHIRP and IMERG were indicating. Like other new sources, the reports are blended as part of a 2nd blending step. This results in those stations having substantial influence in CHIRPS estimates. In this case, the drier values were also affecting North Korea and China. Due to this is effect the source was turned off for CHIRPS v2, and will instead be considered for inclusion in CHIRPS version 3. There will not be a 2-step blending in version 3.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for August 2023.
Rchecks plots: All stats look within normal ranges.
July 2023
Panama The number of stations in Panama that have station reports blended into monthly CHIRPS has noticeably increased over the past year, bravo! It even largely smooths out the visible abrupt differences that have occurred in the CHIRPS rainfall data between Central America model and South America.
Turkey Stations improve the CHIRPS product by capturing heavy rainfall values for the month of July 2023 in the Black Sea region of northwestern Turkey. In early July, The Disaster and Emergency Management Authority (AFAD) reported damages in the provinces of Bartın, Zonguldak, Düzce, Kastamonu, Samsun, Giresun, Bolu and Karabük. AFAD said more than 250 mm of rain fell in 24 hours to 09 July in Yığılca in Düzce. Station values in CHIRPS show slightly smaller values, but are much improved relative to initial CHIRP estimates. See floodlist for more.
CHIRPS processing In CHIRPS production there are automated quality control steps that screen out station reports that are likely to be errors, associated with too big or too small values. The goal is to reduce the impact of errors on the product. With the development of CHIRPSv3, CHC is investigating ways to improve the screening methods, including through statistical modeling using multiple data sources and through better visualization of the screening process. In July 2023 data, a handful of stations in Turkey and Russia that had been auto-screened out were re-included into CHIRPS, based reports of storms and flooding at those locations.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for July 2023.
Rchecks plots: All stats look fine.
June 2023
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for June 2023.
Rchecks plots: Southern Africa doubled it's previous CHIRPS maximum but we are removing a couple of these outliers. Otherwise, all looks normal.
May 2023
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for May 2023.
Rchecks plots: All stats look fine.
April 2023
Mexico No Conagua station reports were blended into CHIRPS for April 2023. This created a major reduction in in situ reports that are typically included in Mexico, at more than 300 locations from Conagua, to less than 50 locations from global networks. Conagua, Mexico's National Water Commission, usually also provides station reports that are used to improve the CHIRPS preliminary pentad product, but these were missing during April 2023 as well.
Brazil Heavy rains produced flooding in Bahia state, according to Floodlist. CHIRPS estimates in this area were improved from blending of station reports that showed wetter conditions than CHIRP.
Columbia CHIRP estimates were moderately high, but numerous station reports were wetter. This resulted in a substantial portion of mountainous areas having CHIRPS estimates that range from 600 mm to higher than 1000 mm for the month. Flooding impacted multiple areas in early and late April, with landslides and fatalities reported in Cudinamarca and Antioquia.
Peru Severe flooding also occurred during April 2023 in Piura, Peru. A GTS station that doesn't regularly show up in CHIRPS reported a very high amount for Piura: 361 mm. According to news reports, affected areas received 5 times more rain in a few days than would typically occur in the whole month, and that the flooding greatly impacted basic services and increased risks of vector-borne and contamination-related diseases in the northern coastal areas of the country. The wet conditions came after Cyclone Yaku brought heavy rain and flooding to northern Peru in March.
Australia Station data prominently increased the CHIRPS rainfall estimates, compared to CHIRP, for the peninsula area in east Arnhem and Nhulunbuy. A tropical storm grazed northern Australia.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for April 2023.
Rchecks plots: There were new CHIRPS maximums in South America, 2300mm as opposed to the previous high of around 1300mm. Stations in Columbia and Peru confirm there were very wet conditions in April 2023, so the statistics seem reasonable.
March 2023
California Blended stations majorly increased CHIRPS values in northern coast and Sierra Nevada mountain regions of California. CHIRPS, and even just the CHIRP, did a better job delineating these as areas of high rainfall than IMERG-Late, probably due to the orographic influence built into the climatology (in CHIRP and CHIRPS), plus the stations (in CHIRPS). In contrast, IMERG-Late shows rainfall that lacks an elevation pattern as is pretty even and around 60-70 mm across much of the state. With some wetter areas along the coast and drier areas in the west.
Mozambique Three station reports along the central coast were inspected, due to their close proximity to Cyclone Freddy's landfall and the low and below-average amounts reported at two of these. A similar situation with one of these stations occurred last year (Feb/March 2022 data/Cyclone Gombe). In that case we omitted the station's report, out of consideration that it could be an inaccurate report for a monthly total. The same decision was made for these two in the March 2023 Final blending; the third station's report, which was more realistic, was retained. An article on Freddy and its heavy rain and major flooding impacts in Quelimane, the nearby main city, can be found here.
Kenya A GSOD station report in northeast Kenya was inspected, due to a report of 12.5 mm being markedly lower than what is indicated by satellite rainfall estimates. Higher and above-average March amounts are indicated in this area, associated with storms in mid-late March, by CHIRP, TAMSAT, IMERG satellite products. There was also substantial surface green up indicated in eVIIRS NDVI maps near this location during this month. A pre-March and post-March NDVI comparison is shown here. Due to the multi-source agreement, the 12.5 mm report was omitted from the Final blending procedure, out of precaution that it could be an accurate report for a monthly rainfall total.
CHIRPS improvement Quality control and procedural station blending steps are points of planned near term focus in CHIRPS v3 development. An automated station screening step in the CHIRPS processing was marked as a quality control step that will be revisited. It checks for stations that are "too big or too small", compared to expectations based on CHIRP and climatology, and is resulting in some geographic clustering of auto-omitted stations. A step of processing that blends some newer stations as part of a second blending step, was again discussed as being problematic. This 2nd step can markedly increase the influence of extreme station reports in CHIRPS rainfall estimates, and is planned to not be used in CHIRPS v3. Some inconsistencies were recently noted for some SASSCAL stations, such as a reduction in reporting frequency in recent years and possibility of sub-monthly daily totals in lieu of full-month daily totals. The latter potential issue may be improved with new screening steps, which will be investigated.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for March 2023.
Rchecks plots: A new high for Costa Rica of 1900 mm, other than that, all stats fall within normal ranges
February 2023
Mozambique Cyclone Freddy was a major driver on high rainfall amounts reported by stations in southeastern and central-eastern Mozambique. The wettest report was near the town of Vilankulos (eastern Inhambane province) at 835 mm for the month. This is ~650 mm higher than average, based on historical CHIRPS data at that location. The blending of station reports greatly increased CHIRPS compared to CHIRP in southern Mozambique. In contrast, several stations in Manica province, in central-western Mozambique, reported much less rain than satellite data indicated. In Chimoio a station reported 182.3 mm while CHIRP estimated 278 mm. These stations have been reliable in the past, and their reports were maintained in CHIRPS Final. These stations influenced a drier CHIRPS in portions of central-western Mozambique compared to what CHIRP had indicated.
Philippines There were reports of monsoon flooding in some admin level 2 areas that CHIRPS identifies as having receiving high rainfall amounts. CHIRP estimates were decently high, but CHIRPS are higher due to the blending of stations. More information about the flooding can be read in in this Floodlist article.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for February 2023.
Rchecks plots: All stats fall within normal ranges
January 2023
Algeria In coastal areas, January CHIRPS shows welcome improvement in rainfall, compared to the very dry conditions in December. Several stations blended into CHIRPS reported above average January rainfall, in Jijel, Alger, and into Medea. While CHIRP also picked up on this; having these station reports improved (increased) CHIRPS Final estimates.
Philippines Extreme rainfall was picked up by CHIRP and CHIRPS; see Floodlist for more information.
Australia High rainfall amounts that led to flooding in northern Australia were captured by CHIRP and CHIRPS, with the blended stations in CHIRPS resulting in higher and more accurate estimates.
Afghanistan CHIRPS Final is somewhat wetter than Prelim for January 2023 data, in southwestern and southeastern Afghanistan. This is seemingly due to several stations in Pakistan that reported above-average precipitation near the border. There are no stations located in Afghanistan that have reports blended into Final, since September 2021, so the estimates are influenced by a combination of satellite-based (CHIRP) estimates and reports in surrounding countries. The increases in Jan 2023 seem believable, due to higher precipitation being indicated by CPC Unified. IMERG-Late daily data also estimates high rainfall amounts in the southwest during early January, with much higher amounts than indicated by CHIRPS.
Brazil There are roughly 20 stations reporting near the town of Bela Horizonte. The sources are fGTS and local. This is an extreme case of high density stations being blended into CHIRPS.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for January 2023.
Rchecks plots: A high value of 2400 mm was plotted in the global CHIRPS maximum pane, which stood out because it was several hundred mm higher than previous value. Marty identified that this pixel is located in the Pacific Islands region at 145.65 E, 18.85 N. There were also 2 other pixels greater than 2000 mm along the same chain of the Mariana Islands. Other than that, all other statistics fall within normal bounds
December 2022
Brazil In central coastal Brazil, in Espirito Santo state, the blending of stations into CHIRPS produced much higher rain estimates compared to CHIRP. These high rainfall amounts were associated with flooding reported in this area, which resulted from heavy rain in both November and December. Read here for more.
Congo and DRC In Kinshasa, capital of the Democratic Republic of the Congo, torrential rainfall in December reportedly brought "months of rain." Floods and landslides killed at least 169 people and caused major damage to infrastructure. ReliefWeb offers more information about this event. What is surprising is that CHIRPS has a station reporting not very far from Kinshasa, just north of the Congo border, and the amount reported there seems very low considering this high impact event. This station from GHCN-v2 monthly reported 214 mm: An amount that is considered slightly below average compared to CHIRPS average for that month. Two satellite products, TAMSAT 3.1 and CHIRP show above-average rain in the area. Given the Kinshasa flood news reports and the general agreement from the satellite products, this station's report and was recommended for omission from CHIRPS Final this month.
Armenia and Azerbaijan Rchecks during this month and previous months identified 8 stations that repeatedly reported standout high values, ranging from 200 to 600 mm, that are interspersed with a dozen stations that report less than 20 mm. The source of inconsistency is not known, though maybe it has to do with data errors e.g. missing decimals. Since these stations have been flagged multiple times already, the set was recommended for permanent removal.
Spain Severe weather and flooding was reported in Spain, in several provinces in mid December. CHIRPS Final for December is benefitting from the blending of high, above-average rainfall reports across many locations. CHIRP did a decent job resolving above-average rainfall in northern Spain, but the stations across a larger region (including Portugal and France) really bumped up the CHIRPS values.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for December 2022 (a link will be active soon).
Rchecks plots: Slightly new highs for number of pixels with rain and CHIRPS - CHIRP mean for the Sahel but by very small amounts. Otherwise, statistics are within normal ranges.
November 2022
Spain Stations blended into CHIRPS final data captures an intense rainfall event on the eastern coast of Spain. The weather station at Valencia airport recorded 66.1 liters of rain per square meter in just one hour -- the most intense rainfall on record for November, according to Spanish meteorological agency AEMET. More on this story is here.
Kenya In western Kenya there are typically around 5 GTS and GSOD station reports blended into CHIRPS final data, but for Nov 2022 the Rchecks shows this area has no station reports going into CHIRPS final. The above-average Nov 2022 CHIRPS estimates in western Kenya are coming from CHIRP and likely also are influenced by above-average rainfall reported at two stations in central Kenya. Other satellite products (e.g. RFE2, IMERG-Late) also indicate above-average rainfall near the CHIRPS above-average rainfall areas in western Kenya.
Panama There is a particularly obvious visual seam between November CHPclim tiles, which is producing an odd-looking artifact in the Panama Canal region in November 2022 data.
Honduras Multiple stations reported below-average rainfall along the Caribbean coast, which lowered CHIRPS values compared to the CHIRP and CHIRPS-Prelim estimates quite a bit in northern and eastern Honduras
'Indonesia A linear artifact was spotted in November CHPclim data in Indonesia+Papua Barat (near 134E, 4S)
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for November 2022.
Rchecks plots: All statistics are within normal ranges.
October 2022
East Africa October 2022 CHIRPS Final shows drier-than-average conditions across many equatorial and southern locations, including areas of concern in Kenya, southern Somalia, and parts of southeastern Ethiopia. Available station reports confirmed the regional dry signal, and the wetter-than-average conditions in western Ethiopia. Those conditions were previously indicated by CHIRP and CHIRPS Preliminary estimates, and other satellite-based estimates. The station reports that were blended into CHIRPS Final also identified some additional areas with higher rainfall (e.g. see entry on Somalia). Forecasted below-average rainfall during September to November/December 2022 in this region has been a concern, due to drought conditions during several consecutive key rainfall seasons and extreme impacts to agricultural and pastoral livelihoods, water resources, and food security. See the Multi-Agency Drought Alert for more information.
Somalia FAO SWALIM stations that are blended into CHIRPS Final reported that many locations recieved only low to moderate amounts during October 2022, and a few recieved localized heavy rain. Ample, localized rainfall of 140 mm to 250 mm+ for the month was reported in Sool and Togdheer near the Ethiopia Somali region border. Some satellite rainfall estimates, e.g. IMERG-Late, indicate above-average rains nearby, though not > 200mm. In this area and in eastern Somali, NDVI imagery and time series (eVIIRS) indicate vegetation greenup during late October to early November, and cooler than average land surface temperatures, both of which are consistent with higher rainfall in these areas during October. Several stations in southern Somalia (two in Bay and one in Bakool) reported moderately above-average October rainfall. However, reports from most other stations in southern Somalia indicated below-average October rainfall, confirming the CHIRP, RFE2, IMERG-Late estimates that also showed drier-than-average conditions. NDVI imagery also confirms the widespread vegetation stress across these areas into early November.
Vietnam CHIRPS data shows the heavy rainfall received in Vietnam. The country was recently hit by 5-6 tropical storms, which resulted in widespread flooding.
Brazil and Paraguay Blended station reports led to large differences in CHIRPS versus CHIRP rainfall estimates in eastern Paraguay and southern Brazil. Three station reports in Brazil were omitted; two were possible falso zeros and one had a seemingly inaccurate high rainfall amount. Those station reports were markedly different from neighboring stations and also indications from multiple satellite-based rainfall estimates (CHIRP, PERSIANN, and IMERG-Late).
Columbia The very dense station network significantly raised CHIRPS values compared to CHIRP. Many stations reported much higher than average rainfall values. The wet signal was also seen in IMERG-Late and PERSIANN-CCS data.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for October 2022.
Rchecks plots All statistics are within normal ranges.
September 2022
United States In late September, Hurricane Ian made landfall in southwestern Florida and brought heavy rain and severe flooding. It was one of the strongest storms to ever hit the United States. Station reports blended into CHIRPS ranged from 15 to ~28 inches for the month, in affected areas. CHIRP v2 seems to have underestimated the precipitation, compared to IMERG and Persiann. By comparison, the beta version of CHIRP v3 was better able to pick up the increased precipitation-- a good sign for higher accuracy of extreme rainfall events in the next version of CHIRPS.
Thailand Thailand was hit by Tropical Cyclone Noru at the end of September. CHIRP captures the higher-than-average rainfall pattern but CHIRPS shows higher rainfall amounts, with differences in some of the wettest areas that are ~ 150mm higher in CHIRPS. There aren't any stations reporting to CHIRPS in Cambodia, and it was stations in Thailand that led to the increase in Cambodia.
South Korea South Korea was hit with Typhoon Hinnamnor in early September, causing flooding and evacuations. It was the second major rain event in a few weeks time. More information is available [here https://www.cbsnews.com/news/typhoon-hinnamnor-south-korea-deaths-missing-flooding-in-south-and-north-korea/]. CHIRPS data shows above-average rainfall across the Korean Peninsula and in southeastern China and Russia during the first dekad of September.
Europe Deadly floods battered countries along the Adriatic Sea in mid and late September, including Italy, Slovenia, Croatia, Montenegro and Bosnia-Herzegovina. Stations blended into CHIRPS data reported very high monthly totals in western Slovenia, with several around 500 mm (20 inches).
Puerto Rico Hurricane Fiona led to very high rainfall. CHIRP didn't capture the high values well, with isolated pixels near 500 mm. In contrasts, CHIRPS shows a widespread area with over 600 mm for the month, and one pixel of 936 mm!
Western Sahara A station reported a value here ~30 mm. Despite being a relatively low value, this amount of rain is not typical here. This seems to be an accurate station report, as multiple satellite products show higher than average rain. A station in coastal Mauritania also reported above average rainfall. The area was affected by Tropical Storm Hermine, an unusual storm that formed northeast of Cabo Verde in late September 2022.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for September 2022.
Rchecks plots Statistics fall within previous ranges except for in West Africa. The CHIRPS maximum value is much higher than any previous value for September. This was traced to several pixels along and just off the coast of Mauritania that were very high. This appears to be related to very high CHPclim (climatology) values at those locations, which appear in both September and August monthly CHPclim. The extreme values in CHIRPS final September 2022 were created by a combination of the high climatology pixels and exaggeration of those when a wetter-than-average station report was in their vicinity was blended into the data. Rcheckers also examined the next (beta) version of CHPclim, and found that the same issue was occuring in the same locations, but value were even higher than in the current CHPclim. This issue was communicated to Pete Peterson, data curator.
August 2022
Uganda August 2023 had a higher than usual number of stations reporting in Uganda. All 8 of these are GTS stations. Several reported much higher than average rainfall, with the highest amount in the Eastern Region (~300 mm), where destructive, heavy rain also occurred in late July. Data indicate that this highly above-average monthly total was mainly reflecting rainfall during the last dekad in August. In Uganda, June and July rainfall was substantially below average, and wetter and more mixed conditions occurred since then. CHIRP data tends to underestimate heavy, localized rain events, which was the case here- the wet station report increased CHIRPS-estimated amounts by more than 50% in some locations.
Yemen The magnitude of very high rainfall values in Yemen in August 2022 are regarded with only moderate confidence. This is because there are no Yemen station observations being blended in. Rather, the high values are a result of a combination of several wetter-than-average stations in southern Saudi Arabia and possibly Ethiopia, and above-average CHIRP values. This type of wet exaggeration has been apparent in CHIRPS through this summer in Yemen, and is associated with persistent wet conditions that have occurred. A wet tendency is strongly inferred by agreement between multiple satellite-based rainfall products (e.g. IMERG-Late, RFE2, CHIRP) and the stations in the general area. When it comes to differences between CHIRP (or CHIRPS Prelim) and CHIRPS Final, we occasionally see the much lower variance of CHIRP underestimating extreme rainfall, and that stations blended into Final can really make a wet difference. This seems to be one of those cases, though unfortunately we don't have local stations to provide indication of actual rainfall amounts. This case was an extreme one, as evidenced by CHIRPS having several pixels off-shore that were higher than any other August pixel from 1981-2021 in the East Africa region monitored by the Rchecks Plots.
Mali In August 2022 there was a major underreporting of GHCN-v2, globally dropping from ~1700 to ~1250 stations. Mali is one country where this had a major impact on typical station composition- while most months this year had GHCN-v2 and GSOD in Mali, this month the stations are all GTS. The values reported at these stood out as being suspiciously low, compared to what CHIRP and IMERG-Late indicate, especially in southern Mali. The impact would be to dramatically lower CHIRPS values across southern Mali. We also checked GTS amounts against a secondary station dataset, the MCDW, and found GTS to be around 100 mm lower than those in some areas in question. Given that the CHIRP seemed to have a reasonable-looking anomaly pattern (mixed, with some ongoing dryness but not more intense compared to previous months), and that GTS is the lowest-ranked station source in terms of quality, we opted to omit almost all the GTS reports in Mali this month. CHIRPS relies mainly on the CHIRP estimates there. We kept one GTS, in the northwestern zone of southern Mali, to "counteract" influence of an anomalously wet station in western Senegal.
Pakistan Exceptional and highly destructive flooding has occurred in Pakistan this summer. The 2 southern states of Sindh, Balochistan were most affected, according to August news reports. August CHIRP data and z-scores don't pick up on the severity of this. Stations help CHIRPS quite a bit, and resulted in CHIRPS z-scores in the +2-3 range. Some estimates may be underestimated, based on a station reporting 500 mm and CHIRPS FINAL ultimately estimating 200-300 mm near there.
Somalia Several stations in southern Somalia reported moderate and above-average rainfall during August, mainly ranging from 30 to 50 mm in total, and these are reflected in the August CHIRPS estimates. The location of this localized rain, in Bay, Shabelle-Hoose, and Shabelle-Drexe, matches well with the pattern indicated in RFE2's August rainfall anomaly estimates. Good to see that level of agreement between these data products.
Panama There is a particularly obvious visual seam between August CHPclim tiles, which is producing an odd-looking artifact in the Panama Canal region in August 2022 data.
Brazil Four stations in southeastern Brazil along the southern boundary of Sao Paulo state and the northern boundary of Parana state were omitted and suspected of having false zeros. Their station values of zero contrasted the surrounding CHIRPS' pixel values that ranged between ~30 to 90 mm. Other stations within 5-10 km reported around 60 mm. IMERG-Late and PERSIANN data also indicated ample precipitation, around 30 to 100mm in this region.
Iran CHIRP is reporting near zero rainfall across southwestern Iran. However, some GSOD and GTS gauge stations are reporting rainfall between 32 and 74.5 mm. Other data, e.g. IMERG-Late and PERSIANN-CCS, confirm there was precipitation in this area, with values ranging from 50 mm to localized amounts higher than 150 mm.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for August 2022.
Rchecks plots All statistics fall within previous ranges except the "Long Horn of Africa", CHIRPS maximum value. CHIRPS Final data for August 2022 contains several pixels that are much higher than any in previous August data. These are located just off the coast of western Yemen. The high value pixels are ~ 1050 mm and are seemingly created from a combination of abnormally wet CHIRP values and abnormally wet station reports in southern Saudi Arabia.
July 2022
Yemen CHIRPS shows much higher July rainfall totals than CHIRP in western Yemen. The accuracy of July 2022 CHIRPS high rainfall amounts in the area near Marib and Sana'a is in question, as these are not verified by stations in that area. There are no stations in Yemen that are blended into CHIRPS. The high values in this area appear to be from a combination of two things: Above-average rainfall in CHIRP and reports from stations in nearby countries.
Afghanistan It has been almost one year since any stations have reported in Afghanistan to be included in CHIRPS. The last report was a GSOD station on August 2021.
Australia In New South Wales, the dense station network shows high rainfall amounts for July, which increased CHIRPS compared to CHIRP. Some locations could potentially have received higher amounts than shown by CHIRPS. Australia has been hammered by rain lately, producing repeative and damaging floods.
New Zealand CHIRP performed decently well in estimating high rainfall amounts along the west coast of the South Island, but anomalous station reports all around the area further increased CHIRPS values. Much of the area that was most affected by heavy rains is uninhabited, but there was plenty of flooding in surrounding areas. More on the South Island floods is here.
United Arab Emirates Extreme high rainfall occurred during July 27th-29th, and had major impacts in the city of Kalba. A station blended into CHIRPS reported 220mm for the month of July at this location as well as several others with lower amounts; an article about the event noted that rains were the heaviest in 27 years during the event. While CHIRPS contained these reports, the data values do not reflect such high amounts. This is due to the estimation algorithm being tied to climatological averages, which are low in this location. That suppression of localized wet extremes in dry locations/seasons is a downside of that methodology.
China On Hainan island, blending of one station's report for July rainfall boosted CHIRPS values, compared to CHIRP. A typhoon brought heavy rain to this area; some locations could potentially have received higher amounts than shown by CHIRPS. More on the typhoon is here.
Colombia CHIRP seems to have problems estimating high orographic rainfall in the mountains of Colombia (particularly coastal); stations help CHIRPS a lot. Probably not a lot of agricultural areas there, but it's an interesting feature.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for July 2022.
Rchecks plots All statistics fall within previous ranges except the "Long Horn of Africa", CHIRPS - CHIRP mean. It is about 2 mm higher than any previous July and looks to be due to the Ethiopian highlands increases.
June 2022
Côte d'Ivoire Heavy, abnormally high rainfall in June 2022 was reported by a station in Abidjan. This is in part due to an extreme rain event that reportedly brought 160 mm of rain in 12 hours, according to Floodlist. Flooding from this event, and another one during the previous week, led to at least 6 fatalities. The GTS station blended into CHIRPS reported 728 mm for June. The station resulted in higher CHIRPS estimates compared to CHIRP in this area, though CHIRP did a decent job resolving a high amount at the same location (~600mm and ~ 150mm higher than average for the month).
USA Heavy rainfall combined with the melting of late season snow pack to produce record-high river levels that flooded portions of southern Montana, including in Yellowstone National Park. The flooding washed out roads and bridges, and occurred in some river and creek areas that seldom or reportedly never have experienced flooding. Stations blended into CHIRPS in this area and in northwestern Wyoming have above-average monthly totals, and satellite-based estimates from CHIRP and IMERG-Late show this being primarily to above-average rain in mid-June. The blending of these stations' reports into CHIRPS final resulted in wetter monthly totals over a larger area, compared to CHIRP estimates.
Guatemala Numerous stations in Guatemala report heavy rainfall, which led to fatalities, flooding, landslides, and damaged infrastructure. The high density of INSIVUMEH stations that are blended into CHIRPS final data increased CHIRPS estimates compared to CHIRP, across western, southern, and southeastern areas.
Costa Rica Station data increased CHIRPS estimates compared to CHIRP. News reports note tropical waves have led to high rainfall/flooding in the north part of the country. More information is available here.
Nicaragua Station data has been missing here for the last few months.
Persian Gulf To the northwest of Dubai in the Persian Gulf, on the small island of Siri, GTS and GSOD reported station values of 65 mm and 64 mm, respectively. CHIRP, IMERG, and PERSIANN show the same area and its surroundings to have zero precipitation. The closest measurable precipitation, on the southern shore of Iran, is about 0.6 to 2.5 mm. These stations were omitted from blending in CHIRPS final due to lack of support of rain from satellite products; Rcheckers also did not find any online reports to support highly localized rain.
North Korea North Korea is showing up as much wetter in CHIRPS than the CHIRP for June 2022 due to the influence of blended station data. Rain gauge data from a station in Pyongyang, for example, recorded 591 mm. CHIRP estimates partially resolve this event, with above-average rainfall in the same area; however, CHIRP totals range from 150 mm to 195 mm.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for June 2022.
Rchecks plots All stats fall within normal ranges, except for the Southern Africa region, where new a CHIRPS mean and maximum and CHIRPS-CHIRP all had new highs for June totals. Looking back at previous years' CHIRPS final data for June, the current highs correspond to unusally widespread rain in June 2022.
May 2022
Southern Africa CHIRP and stations fail to capture severe rainfall and flooding in late May in Kwazulu-Natal. Some areas reportedly received over 200mm in 24 hours on May 22. Stations blended into May 2022 CHIRPS in KwaZulu-Natal that are visible in the Rchecks interface all had less than 100 mm for the month.
Puerto Rico Stations reported lower rainfall totals than were estimated by CHIRP. There is a relatively dense station network here, to this lowered CHIRPS values. In general, stations appear to be having a bigger role than normal this month in CHIRPS in Southern and Central America.
Columbia Reports from the dense station network, including some stations in the Amazon region, had the effect of increasing CHIRPS rainfall values above the already high CHIRP estimates.
Brazil In southern Brazil, many stations report a band of higher rainfall amounts than are estimated by CHIRP, and resulted in higher CHIRPS values.
United States Stations increased CHIRPS estimates, compared to CHIRP, across most areas. Especially in the central US and upper midwest.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for May 2022.
Rchecks plots All statistics are within previous ranges with the exception of Southern Africa, where the regional mean difference in CHIRPS and CHIRP was higher than any previous values for May. This is due to the effect of many stations in South Africa and Mozambique increasing CHIRPS estimates along the coast. The May 2022 mean CHIRPS - mean CHIRP value is about 1mm higher than the previous high value.
April 2022
Madagascar In southeast Madagascar, a station that is included in CHIRPS reported a very high 429 mm rainfall for April. High values are not shown in CHIRP, TAMSAT, ro RFES2 estimates, but they are in IMERG-Late. The reported wet conditions are likely related to a tropical storm that made landfall in the region in late April. More on Tropical Storm Jasmine is here.
Australia CHIRP estimates were decent in northern Queensland, but station data boosted CHIRPS Final values quite a bit. Heavy rains lead to extensive flooding in this area in late April.
Columbia After a hiatus, Columbia stations are back in CHIRPS Final. Rchecker Seth noted: "Good to see the stations back. CHIRP doesn't seem to perform optimally with orographic rainfall, and the stations always make a difference (increasing estimates)"
Northern US and southern Canada CHIRPS data shows the highly above-average precipitation in April 2022 in western Washington and Oregon, USA, western British Columbia, Canada, and the region from North Dakota, USA to southern Ontario, Canada. In many locations in these areas, April 2022 precipitation amounts were close-to or above previous record highs, according to this article about April 2022 precipitation and temperature extremes.
Western US The hydrologic drought in most of California and across the southwest was worsened by below-average April precipitation. In northern California, Washington, and Oregon, precipitation conditions were mixed and many areas had above-average amounts. Most western US areas are now in extreme or severe stages of drought, as of May 10th. See US Drought Monitor map here for more information.
Panama and Costa Rica The stations included in CHIRPS resulted in large changes along the Atlantic side of Panama and Costa Rica.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for April 2022. Overall, CHIRPS Final had higher rainfall amounts than Prelim, in most of the regions where data were different.
Rchecks plots There is a new high for CHIRPS-CHIRP in Latin America. This seems to be the result of a large number of very high measurements along the Colombian coast as well as Panama. Since they are in good agreement, this looks legitimate.
March 2022
Mozambique On March 11th, Cyclone Gombe made landfall in coastal Nampula Province as a Category 3 Tropical Cyclone. March CHIRPS Final data shows above-average rainfall in this region, in a large part due to this storm and above-average rain that occurred during the following week. Local sourced station and GTS reported 536.1 mm and 535.4 mm for the month, respectively. The cyclone brought large amounts of rain and flooding to central-northern Mozambique. In the city of Beira, to the south, the city's mayor reported that they had received more than 400 mm of rain in two days, associated with Cyclone Gombe. More about the destructive Cyclone Gombe can be read here.
Western U.S. The hydrologic drought worsened during March 2022. CHIRPS data shows monthly precipitation deficits over most areas of California, Oregon, and Washington (and farther east) in January, February, and March. Precipitation totals for that 3-month period, across coastal and southern Sierra Nevada mountains, are ~300 to 400+ mm (11-15+ inches) lower than typical amounts for that period. According to the U.S. Drought Monitor, "Water storage in the two largest reservoirs in the west – Lake Powell along the central Arizona/Utah border, and Lake Mead farther downstream along the Colorado River – has dropped to unprecedented levels. In early April, the combined storage was only 44 percent of the average since 1964." More on that at the US Drought Monitor.
Southern California As predicted by the weather models, Southern California received a late season rain storm that soaked the Southland. It did not have much of an impact on the drought but delayed the start of fire season. The March CHIRPS reflects this rainfall event very well. More on this event is here.
Australia Severe flooding occurred in New South Wales and southern Queensland along Australia's East Coast, associated with record-breaking rainfall. Inclusion of more station reports led to CHIRPS showing much higher rainfall amounts there compared to CHIRP. CHIRP. More than 21 people died in the flooding; more on this extreme rainfall event can be read here.
Portugal and Spain In Portugal and northwestern Spain, CHIRP (without stations) depicted well-above average precipitation for the month of March that was significantly downgraded by local weather stations. The CHIRPS Final product is still above average, but the signal is considerably weaker than was seen in CHIRP.
Kazakhstan An unusual-looking precipitation pattern is visible in the CHIRPS in the Caspian Sea. The source of this feature was traced back to the CHIRPS climatology, which has data values over the Caspian Sea that form a shape similar to the Sea extent. The next version of CHIRPS climatology will mask out data values over the Caspian Sea (see e.g.; in EWX, the CHIMPS Clim 925 data layer).
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for March 2022. Many more station reports are blended during the CHIRPS Final processing. Where Prelim and Final estimates were different by more than 10 mm, in March 2022 data, most of these were instances of Final being wetter as opposed to being drier. Some areas with large "wet" differences are in Mozambique, southern Tanzania, western Zambia, western Republic of the Congo Namibia, coastal China, coastal southeast Australia, and portions of South America. Some of these changes were examined during Rchecks, and were found to correspond with stations reporting high rainfall impacts that seemed possible, such as in coastal central Mozambique (high localized rain amounts from Cyclone Gombe), in Republic of the Congo (IMERG-Late data also indicated localized wet conditions), and flooding rains in coastal Australia.
Rchecks plots All statistics are within previous values except in South America where a new CHIRPS mean and CHIRPS standard deviations set new highs but by small amounts.
February 2022
Australia During late February 2022, eastern Australia (southeast Queensland and northeast New South Wales) experienced major flooding due to extremely high rainfall. During February 22nd and 28th, Brisbane had its wettest 3 days on record, and other notable areas received over 1100 mm (That is more than 43 inches!). Read more from weatherzone.com.au here. CHIRPS data included numerous gauge reports in this region, and the reports being blended into the product results in good depiction of the observed spatial pattern. The satellite-based CHIRP estimates showed above-average rainfall, but greatly underestimated monthly totals and totals for late February. Because of this, CHIRPS estimated amounts are lower than many of the gauge reports; however, the data still show the historical extremity of rainfall. CHIRPS totals for the last 8 days of February are more than 3 standard deviations from the mean in the very wet areas.
Columbia Heavy rain and flooding in the department of Nariño, Colombia led to flash floods, destruction, and at least one fatality (see Floodlist report). CHIRPS data shows rainfall amounts as being substantially above average during this time, and very high amounts for February totals. The wet signal is coming both from CHIRP and the IDEAM gauge reports; the gauges are responsible for CHIRPS having very high values here.
Eastern Mediterranean In western Turkey, southern Bulgaria, and eastern Greece, blending of multiple station reports resulted in CHIRPS correctly reflecting above-average rainfall. CHIRP estimates were drier-than-average in these areas.
Western United States February 2022 CHIRPS depicts the severe ongoing dry conditions across much of the Western US. February is typically one of California's wettest months, but most areas received either no precipitation or a fraction of typical amounts, according to CHIRPS (and supported by numerous blended gauge reports). As shown by CHIRPS, December 2021 was wet but deficits during October, January, and February have resulted in much lower than average water year precipitation totals through February. According to the U.S. Drought Monitor, snow water equivalent values are below-normal in many Western basins, and parts of California's San Joaquin and Sacramento Valleys and Central Coast have experienced record dryness since January 2022. In those areas, some reservoirs are at record low levels and stream flows and soil moisture is ranking below the 2nd percentile (March 15th, 2022 summary).
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data, for February 2022. Many more station reports are blended during the CHIRPS Final processing. Where Prelim and Final estimates were different by more than 10 mm, in February 2022 data, most of these were instances of Final being wetter as opposed to being drier. Some areas with large "wet" differences are in western Tanzania, northern Zambia, northeastern Namibia/southwestern Angola, northern Brazil, and eastern Australia.
January 2022
Central America In eastern areas of Honduras, Nicaragua, and Costa Rica, and in northern Panama, CHIRPS Final is showing an area with large negative anomalies during January. The values show drier conditions than Prelim data had indicated. The pattern appears associated with multiple stations reporting below-average rainfall in central Honduras, two co-located stations in eastern Honduras, and multiple stations to stations to the south and east. The co-located eastern Honduras stations were examined using two layers in the EWX that show the influence of stations incorporated in the first “anchor blend” and 2nd blending step. Stations used in the 2nd blending step can have more influence. A good sign for validity of data is that these two reports generally agree that rainfall was very low compared to climatology, around 53 mm for GSOD and 35 mm for the locally-sourced report. CHIRPS values near this location are similar to these reported values. Overall, multiple stations and the satellite-based CHIRP provide support for drier-than-average conditions having occurred in Caribbean coast region of Central America in eastern Honduras and to the south. It is possible that low station density could obscure localized differences from this dry pattern.
CHIRPS Final versus CHIRPS Prelim A map here shows the difference between Prelim data and Final data for Africa, for January 2022. In southern Africa, stations provided by SASSCAL and by Mozambique are blended into CHIRPS Final (along with reports from global networks). These quality-controlled resources can greatly improve precipitation estimates beyond what is achievable with satellite-based estimation and the pentadal-blended GTS stations. In January data, Mozambique and SASSCAL reports resulted in increased CHIRPS Final rainfall estimates in some areas affected by Tropical Cyclone Ana. Difference map provided by the FEWS NET NASA team.
Western USA January CHIRPS Final shows severe dry conditions in California's Sierra Nevada Mountain range, across central and northern California, and in western Oregon and Washington. CHIRPS data indicate that January precipitation totals are 4 to 5 inches (~100-150 mm) lower than average in many areas, while some localized deficits are around 8 inches for just the month of January. The data also show expansive drier-than-average conditions across the Western US for January, corresponding to the ongoing moderate-to-severe drought as described by the US Drought Monitor assessment for early February
Ongoing dry conditions in portions of Southern Africa As shown by CHIRPS Final for January, in southwestern Angola, northwestern Namibia, southwestern Madagascar, and southern Mozambique.
Montana and Colorado, USA Stations were helpful in correcting for satellite-based (CHIRP) overestimation of precipitation in Montana, while both data types showed agreement about above-average January precipitation in the Denver area of Colorado. According to the Weather.gov January summary for the Denver area, upper level disturbances, Pacific moisture, and orographic lift led to several snow events in the Rocky Mountain region, and the first month of above-average precipitation and below-average temperatures since May 2021.
Venezuela Rchecker Seth noted the inclusion of several additional station reports in Venezuela and that these agree with CHIRP estimates.
Australia In January CHIRPS Final, stations led to higher rainfall estimates in north and eastern Australia compared to CHIRP. An Rchecker noted that they usually observe similar estimates from CHIRP and station reports here.
Rchecks plots CHIRPS mean is at a new high for Africa, but by a very small amount. Otherwise, all statistics are with historical ranges.
December 2021
Kenya CHIRPS Final data is notably wetter than preliminary estimates from CHIRPS Prelim, for December 2021 monthly totals in southeastern Kenya, northeastern Tanzania, and far southwestern Somalia. The higher December values resulted from the blending of multiple wetter-than-average station reports (some on the periphery of this area) with weaker but still wet anomalies estimated by the satellite component, CHIRP. Reports of swollen rivers and, sadly, numerous fatalities in Kitui County highlight the very high amounts of rainfall received recently in some areas. CHIRPS data indicates that the wettest period was in late December. Other satellite-based products like TAMSAT, RFE2, and IMERG-Late also estimate above-average December 2021 rainfall in this region, however, at lower levels of extremity than CHIRPS Final. Given the lack of station reports where CHIRPS estimates are very high, it is difficult to ascertain the accuracy of estimated values. Differences between rainfall products and the uneven station network suggest that CHIRPS may be overestimating rain totals in some of these areas.
Final vs. Prelim data As a reminder, CHIRPS Final data incorporates station reports from more sources than Prelim, and additional quality control procedures are applied for Final. For Africa data, Prelim data is based on CHIRP and the stations from GTS only. For December 2021 Final, no GTS reports were included due to the source having missing reports for 6 days of the month. Differences in Final and Prelim occur regularly, and are usually not systematic. An image showing the difference between CHIRPS Final and CHIRPS Preliminary, for October, November, and December 2021 totals in Africa, can be viewed here.
Mongolia and China More than 10 GHCN-v2 monthly stations and several GSOD stations reported precipitation in northwestern and eastern Mongolia and in northeastern China. Reports ranged from no precipitation to over 100 mm in China. December CHIRPS precipitation estimates are generally low across this region, due to low values in CHIRPS climatology as well as the influence of the mixed station reports.
Columbia No station reports from IDEAM for Columbia data.
Australia CHIRPS estimates shows high amounts of rainfall brought by a monsoonal low into the coastal Northern Territory, near Darwin, in late December. CHIRPS captured this due to the blending of station reports; CHIRP did not resolve this wet event.
Panama Coastal differences between station reports and CHIRPS Final estimates in Panama appear related to irregular spatial coverage of stations and its impact on the estimation algorithm. In CHIRP, the Atlantic Coast shows high rainfall, and the few stations there also show high rain. However, the Pacific side has more stations, and they are low, which drags down CHIRPS rainfall estimates on the Atlantic side.
Rchecks plots All regional stats fall within normal ranges this month.
November 2021
India Southern India received very heavy rains during November, reportedly associated with five low pressure systems that developed in the North Indian Ocean Region and a later-than-normal exit of the southwest monsoon. In some areas, it was the wettest November since 1901. See this Indian Express article for more information. CHIRPS data shows November rainfall as being more than 2 standard deviations from the mean across much of southern India. The very wet conditions are reported by numerous stations as well as the satellite-based CHIRP estimates, IMERG-Late, and Persiann-CCS data. The very wet conditions are reported by numerous stations as well as the satellite-based CHIRP estimates, IMERG-Late, and Persiann-CCS data.
Canada Highly above average rainfall was received in areas of British Columbia, with some stations reporting monthly totals that were more than 2 times higher than typical amounts. According to Environment and Climate Change Canada (ECCC), the very wet conditions came after an extremely hot and dry summer, and that the occurrence of such extremes was consistent with climate change projections for Canada. Flooding in British Columbia, caused by the heavy rainfall events in November led to at least $450 million in damage, making it the "most costly severe weather event in the province's history,m according to the Insurance Bureau of Canada. CHIRPS data captured the high November rainfall totals in B.C., Canada as well as in western Washington, USA.
Spain While rainfall totals were marginally above average for the month, the majority of rains came in short, extreme events, which caused flooding throughout Basque country in mid- to late-November.
Italy CHIRP and stations capture extreme rainfall in Sardinia. On November 15, heavy rain of over 100 mm in 4 hours caused flooding in the south of the island, including the capital, Cagliari, and the communes of Villa San Pietro and Sant’Anna Arresi. According to Floodlist, heavy rain had previously affected parts of the island of Sicily around 10 November, in particular in Agrigento and Trapani Provinces. Extreme CHIRPS values (~500) on the ball of the foot of Italy (Calabria, Italy) is an artifact of the elevation DEM that goes into CHIRPS. This is expected to be remedied in CHIRPS3.0.
Panama CHPclim having noticeable impacts on data artifact in Panama. This should be remedied in CHIRPS v3.
Nicaragua Rchecks identified a non-realistic-looking anomaly pattern in Nicaragua pre-release CHIRPS. A station with a high rainfall report in southwestern Nicaragua was identified as a probable source of the pattern (high z-score, low climatology, station is blended in the 2nd blending step). Experimentation with and without this station, in a test version of CHIRPS, confirmed that this was the case. It was omitted and the non-realistic pattern does not occur in CHIRPS Final. The Final data show a more narrow and coastally-located above-average rainfall pattern. In southeastern Nicaragua, those estimates may by influenced by wet reports at stations in southern coastal Honduras and northeastern Costa Rica. Some satellite data depict above-average rainfall in that area in late-November, and uncertainty is high due to low station density in that area.
Rchecks plots In the Africa region, new lows in CHIRPS mean, CHIRPS standard deviation and z-score mean. Most CHIRPS grid cells in East, Central, and Southern Africa have estimated below-average November rainfall. Globally, there were new highs in CHIRPS standard deviation and CHIRPS-CHIRP mean but only by a small amount. Haiti stats show new lows in CHIRPS mean, maximum, standard deviation and z-score by small amounts. This follows a dry trend that has been ongoing for several months.
October 2021
East Africa October CHIRPS final data includes a substantial set of station reports that are blended into the CHIRP satellite IR-based rainfall estimates in eastern areas, with approximately 50 stations in Somalia (from FAO SWALIM) and 50+ stations in Ethiopia (from Ethiopia National Meteorological Agency). During Rchecks of this data, most were retained in processing. One station in southern Somalia was recommended to be excluded due to unreliable reporting and a suspected false zero. The October final data confirms below-average rainfall conditions shown in other less-station inclusive data sets, including in CHIRPS preliminary data. A figure that can be viewed here shows the station reports overlaid on the CHIRPS final estimates, for rainfall totals (left column), anomalies (middle column), and z-scores (right column). The top row shows these for October 2021. The bottom row shows these for October 2020, which was also a dry month and part of a poor performance Short Rains/Deyr SOND rainfall season. As can be seen in the maps, both stations and CHIRPS estimate show drier conditions in October 2021 in many affected areas. A major concern for this 2021 season, is that drier-than-average conditions have persisted throughout the season thus far, and that forecasts indicate are likely to continue through November.
Sicily, Italy CHIRP/IR data and stations captured heavy rainfall that led to flooding throughout Sicily in late October. Sicily Regions meteorological agency Servizio Informativo Agrometeorologico Siciliano reported 312.2 mm of rain fell in 24 hours to 25 October at a weather station at Linguaglossa.
Liguria province, Italy CHIRP/IR data failed to capture extreme flooding in northern Italy in early October. Reports indicate 181mm of rainfall fell in 1 hour and >900 mm in 12 hours on October 4th/5th. During Rchecks is was identified that a station that normally reports in this area was not included. It was discovered that the data screening step eliminated the station value for being outside of of the acceptable distribution (z-score too high). This was corrected, and the station was included in CHIRPS final, and improved estimates in this region.
Columbia Says Rchecker Seth: "Yay, IDEAM Colombia station data are back!" This is great news for quality CHIRPS data in Columbia.
Oman and Pakistan Oman and Pakistan contain multiple stations from three different sources that demonstrate very high rainfall amounts that the CHIRP/IR estimates did not resolve. An intense rainfall event was confirmed in this area during the first week of October 2021. Cyclone Shaheen formed in the southeastern Arabian Sea and maintained its intensity as it made landfall. The last time a cyclone made landfall in northern Oman was in 1890, according to this article.
Rchecks plots All statistics fall within previous ranges except for South America which had a new low for CHIRPS max. But very small difference.
September 2021
Spain CHIRPS, informed by both the CHIRP satellite estimates and station reports, captured record rainfall across Spain. Heavy rainfall in two separate storms, in early and late September, caused flash floods and destruction in central and eastern Spain/Catalonia.
Thailand CHIRPS data, informed by both the CHIRP satellite estimates and station reports, captured very high September 2021 rainfall amounts in locations that were affected by Tropical Storm Dianmu and by heavy rain earlier in the month. According to Floodlist, 229,220 households were impacted by flooding across northern and central Thailand.
India CHIRPS shows September 2021 was wetter than average in many areas across central and northern India. Many of these were impacted by heavy rains from Cyclone Gulab in late September, including near where it made landfall, between the east coast states of Odisha and Andhra Pradesh, as well as in areas to the west after it transitioned to a tropical depression. Numerous stations that were blended into CHIRPS reported above-average and high amounts for the month, which helped to increase the more muted wet signal shown by CHIRP in some areas. According to CHIRPS, consistent, above-average rainfall occurred in some western and northern states (e.g. Gujarat, Punjab) through September.
France CHIRPS, informed by station data, captured an extreme rainfall event in mid-September, which led to widespread flooding and dozens of rescues from flooding in the towns of Uchaud, Bernis, Calvisson and Boissieres.
Honduras The addition of local station data, which began in January 2021, really paid off this month. They made quite a difference in modifying CHIRPS from the satellite-based CHIRP estimates. Rainfall amounts in CHIRP in some areas of western Honduras were 300-400 mm, where the station data and resulting CHIRPS were in the low 200s.
Panama There were no local station reports in Panama blended into CHIRPS this month. Also, the chpclim v2 climatology is producing an artifact of high precipitation, and its influence on CHIRPS is particularly bad this month.
Rchecks plots For the Hispaniola region, new lows where calculated for the CHIRPS mean, CHIRPS max and z score mean statistics. Low station reports contributed to these new lows which are just a small amount lower that the previous low values. All other statistics fall within previous value ranges.
August 2021
Turkey, Ukraine, Russia Station reports that were blended into CHIRPS captured devastating amounts of precipitation from Medistorm Falchion. This storm formed over the Black Sea and caused severe floods and landslides in several provinces of Turkey, Ukraine, and Russia in mid-August.
Spain Station reports that were blended into CHIRPS captured abnormally high rainfall in southeastern Spain that led to flash floods in several areas in late September. There were reports of 45 mm of rainfall in a one hour.
India In Rajasthan, CHIRPS show high rainfall amounts that are corroborated by reported flooding in the area. CHIRP showed higher-than-average rainfall in this area, but stations increased the values quite a bit in CHIRPS.
Jamaica Station reports that were blended into CHIRPS, in southeastern Jamaica, show much higher rainfall than CHIRP. The reports may be associated with the heavy rain and flooding caused by Tropical Storm Grace
Costa Rica A station report from the Nicoya Peninsula increased the CHIRPS estimates in northwestern Costa Rica. The CHIRPS estimates seems plausible, due to reported flooding in western Costa Rica and due to stations further north on the Pacific Ocean coast of Central America also reporting high rainfall.
Canada CHIRPS data, based on CHIRP and the blended stations, as well as IMERG-Late data show substantially below-average rainfall for August 2021 in southeastern Canada (southern and eastern Ontario and in much of Quebec) and into the United States' Northeast (Maine). According to a Montreal CTV report, many areas received 25 to 50 percent of typical rainfall. Late August heat waves brought record-breaking high temperatures, such as in downtown Montreal where temperatures hit 35 °C on Aug. 21 (2° C higher than the previous record set in 1916). In Montreal, August 2021 mean temperature was the hottest on record.
United States Across many areas in the central and western United States, CHIRPS rainfall totals for June-July-August 2021 show mild to substantial rainfall deficits. The largest areas with substantially below-average 3-month totals are in Minnesota and Kansas, and in other Midwestern states. While above-average August rains in some northern areas eased deficits, low August rainfall in eastern Colorado, Kansas, added to the ongoing deficits from June and July. In the southern and eastern United States, and in some southwestern monsoon-affected areas, CHIRPS shows average or wetter-than-average conditions. High rainfall amounts in Alabama and Mississippi are in part due to Hurricane Ida.
Columbia Unfortunately, this is another month without station reports from IDEAM for Columbia.
Rchecks plots Other than a new high (just barely) for CHIRPS standard deviation in the Sahel, all stats look good and are within the normal ranges.
July 2021
South Africa Several stations reported above-average precipitation in the western Cape region, which is likely associated with the severe weather reported in the area. See reports here and here. The station reports, combined with the CHIRPS blending process, are producing overall above-average CHIRPS estimates across this region. The satellite-only CHIRP does not indicate a wetter-than-average July. Stations show a mixed precipitation pattern, and IMERG-Late shows a more localized mixed pattern, compared to the CHIRPS estimates.
New Zealand Heavy rainfall on west coast of the South Island in CHIRP is backed up by news reports, e.g. here. CHIRPS lowers the rainfall amounts because it is averaging in stations on the other side of the island.
Romania Stations captured exceptionally high rainfall in central Romania mid-July, which led to widespread flooding in Lerești, Argeș County and in Busteni in Prahova County.
Columbia July 2021 was another month without the good station coverage that CHIRPS had, until recently, in Columbia. This is a topographically complex country, and reports for July were limited to a low elevation valley.
Southwestern US A map series that compares CHIRPS, CHIRP, and IMERG-Late precipitation estimates, and station reports for July 2021, can be viewed here. The lower right map shows station reports as boxes with black symbols, with the box color indicating reported value, and the underlying CHIRPS as the pixelated background. One can see the broad similarities between CHIRPS spatial patterns and station-observed amounts, which is coming from both the satellite-only component (CHIRP) and the blended stations. Compared to the stations that reported, CHIRP (upper right map) estimates underestimated station reports in many areas, as can be seen from the comparatively higher amounts in CHIRPS (post station blending) than in CHIRP. IMERG-Late (lower left map) overestimated the amount and spatial extent of high precipitation in southeastern Arizona and southwestern New Mexico and in other locations in the Four Corners region during July 2021. In the southern and eastern California desert, IMERG-Late shows extensive low rainfall amounts, in contrast to the dry conditions reported at most stations.
Panama The climatology data appears to be making a similar artifact in CHIRPS as was noted for the June 2021 data. We anticipate this will be improved in the next version of CHIRPS.
Rchecks plots All statistics fall within previous ranges, with the exception of a new CHIRPS maximum for the Global region. The turns out to be on Asuncion Island near 145E, 19N, part of the North Marianas Island chain. There was something similar last month with a value of over 2200 on an island chain off of eastern Africa.
June 2021
Columbia CHIRPS typically has many stations from Columbia, but in the past several months (March to June 2021), this data source has not been reporting into CHIRPS. Instead, June 2021 CHIRPS ingested more sparse GHCN v2 stations.
United States Historic high rainfall amounts occurred in southeastern Arkansas and Mississippi in June 2021, which is shown by very high anomalies in CHIRPS. Near Dumas, Arkansas, one of the hardest hit areas by a June 8 to 10 storm reported 22 inches of rain for the month. According to reports, some areas received more rain in two days than is typically seen in months. Flooding and damage to homes farmland occurred throughout the region.
Panama Artifact showing high rainfall, linked to the CHPclim v2. A new version of CHPclim will be included in CHIRPS v3.
Southeastern Africa Artifacts in eastern Mozambique and eastern Madagascar due to CHPClim, which should be corrected by CHIRPS v3
Tanzania-Mozambique CHIRPS shows above-average June rainfall in southern coastal Tanzania, northern coastal Mozambique, and the Comoros islands. This is coming from reports of higher-than-average rainfall from three stations in the area. Estimates may be amplified due to one of them being double-blended (a GSOD station in southern Tanzania reporting ~114 mm).
May 2021
Ethiopia Very wet conditions from late April to early to mid May resulted in flooding damages that displaced 70,000 people in parts of the Afar, Somali, and SNNP regions of Ethiopia. This very wet period was preceeded by a very dry February to middle of April, and followed by dry conditions after middle May in many areas. NMA stations provided to CHIRPS report atyically high May rainfall amounts in Dire Dawa City (155 mm), a location of 9 fatalities, and for other stations in these regions and in Amhara and northern Oromia regions. CHIRPS Final May totals are informed by the ~50 NMA stations and the CHIRP satellite-bsed estimates, which show a similar spatial pattern for anomalies as the monthly station reports. There are only 2 CHIRPS-reporting stations in Afar. This low density makes it challenging to observe localized rain there.
Somalia Flash flooding near Jowhar and Mogadishu (southern-central Somalia) caused fatalities and damages to homes and crops in early May. Two of the three nearby SWALIM stations report May rainfall totals that were above average; reported amounts were 126 mm and 182 mm. At Mogadishu, CHIRPS received two reports from two stations: one from GSOD for 42.5 mm and one from SWALIM for 0 mm. The latter was deemed a false zero and removed from Final blending. CHIRPS monthly totals will show above average rainfall for the month in the Jowhar area, however, the rainfall amounts estimated in CHIRPS will likely be lower than the wet SWALIM reports.
Louisiana May rainfall totals in southeastern Louisiana are around 2 standard deviations above average. In the Lake Charles and Baton Rouge area a May 17th rain event was reported as the third wettest in city history and hundreds of building were flooded.
Panama CHPclim has a rectangular-shaped artifact in May climatology in the center-east part of the isthmus. This makes CHIRPS values look unrealistic there.
Rchecks plots All statistics for this month's CHIRPS final data are within normal ranges.
April 2021
Kenya April is a critical month for the March to May season in the eastern East Africa. In Kenya, April CHIRPS shows below average rainfall across most of the country. A few areas had above average April rainfall: In western Kenya, in localized areas of the southeast, and in the extreme northeast.
United States CHIRPS shows large negative anomalies along the western US Sierra Nevada and Cascade mountain ranges. April rainfall was below average across the Western US, in the central Midwest, and in the central-northern Eastern US. Above average rainfall is along the Gulf Coast, with historically prominent anomalies (high z-scores) in Louisiana. According to the National Weather Service, the first half of April was the second wettest on record for New Orleans (reported by Nola.com, article here). The current US Drought Monitor map for the Western US ([https://droughtmonitor.unl.edu/CurrentMap/StateDroughtMonitor.aspx?West here) shows an unsettling situation for that region as it enters the annual peak fire season: Most areas are in drought, ranging from severe to exceptional levels. Let's hope someone has finally started raking the forests.
Columbia Minimal stations reporting again this month. The ones that were there agreed well with CHIRP but it is still unusual to not have 100+ stations.
Costa Rica and Panama Stations reporting to CHIRPS increase rainfall estimates on the Atlantic coast of Costa Rica and Panama. This is in agreement with CMORPH data.
Guatemala A number of stations in the mountain range near the Pacific coast have (much) higher values than CHIRP; it doesn't seem to handle orographic effects well here.
Papua There are some odd values in West Papua and Trangan. These appear related due to the current CHPclim.
Australia In northern Queensland, stations are a bit higher than CHIRP, raising rainfall from Cape York down to a little south of Cairns.
Taiwan A station on Pengjia Islet, an island to the north of Taiwan, is reporting a low value of 4.1 mm, compared to CHIRP values of between 90-145 mm in this region. Similarly, two stations in Taiwan are also reporting a value which appears to be too low relative to the CHIRP values, 9.4 mm and 20.7 mm compared to 87-150 mm respectively. While the CHIRP anomaly for north and central Taiwan is low, at between -45 and 3.5, the stations are significantly lower with anomaly readings of -128 to - 145. These three stations are having a significant effect on the CHIRPS values for the northern half of Taiwan, bringing the CHIRPS values down quite a bit. Because they differ so significantly from the CHIRP as well as the climatological average, they have been removed during the r-checks process.
Rchecks plots Two features: A new low for Southern Africa CHIRPS - CHIRP (April mean values), and the global CHIRPS z-score was very low (tying the 1987 minimum value).
March 2021
Columbia IDEAM stations for Columbia were not included in March 2021 CHIRPS Final, so data quality may be low there. If IDEAM reports are received they might be included in another run of March 2021 CHIRPS Final.
China March marks the sixth continuous month of anomalous dryness in Taiwan as well as parts of southeastern China. CHIRPS is doing well at capturing both the intensity and duration of this drought. Upon looking at March’s CHIRPS R-checks, the rain gauge stations and infrared satellite products are in agreement and show another anomalously dry month. In fact, according to CNBC’s Pacific Asia News, Taiwan’s president tells residents to conserve water as the island faces the worst drought in “56 years”. A link to that information is here.
Morocco Extreme high rainfall amounts reported for March (156 mm and 238 mm) in and near the city of Tetouan in northern Morocco appear to be corroborated by a Floodlist report: " Heavy rain caused dramatic flash flooding in the city of Tétouan in northern Morocco on 01 March 2021. Roads and infrastructure were damaged and fast flowing flood waters and debris swept through streets dragging along vehicles. Local government reported 100 mm of rain in 9 hours to the afternoon of 01 March which caused rivers and drainage channels to overflow." Australia The eastern coast of Australia was in the news in March for rain/flooding. CHIRP rainfall estimates were high, but the blended stations appear to improve CHIRPS by increasing amounts.
USA Stations in the southeastern United States shifted the bulk of the precipitation north compared to CHIRP. Marty speculates that the effect may be from high clouds drifting south with the cold front(s) have already rained out, but the IR temps are still low enough to make the CHIRP processing estimate rainfall there.
Egypt There are several stations that reported very high and likely inaccurate values around 70 mm to 101 mm in northeastern Egypt. These were omitted from CHIRPS because they were extremely different from climatology (near zero) and CHIRP and other rainfall products did not indicate widespread highly anomalous rainfall.
Central America CHIRP estimates on the Atlantic side of Panama/Costa Rica quite low and the stations blended in seem to improve this.
Kazakhstan In south-central Kazakhstan, a GTS station with a monthly value of 701.8 mm was eliminated from the March CHIRPS final through the reality checks process. Compared to the anomalously high value of this station, the CHIRP pixel values for the same area range from 13-16 mm. Furthermore, this station recorded an anomaly value of approximately plus 686 mm compared to the CHIRP anomaly of between -2 and 0 mm for the exact same area.
Rchecks plots No report available
Contributors: Marty Landsfeld, Laura Harrison, Austin Sonnier, Seth Peterson, Will Turner, Pete Peterson
February 2021
Africa Earlier drier than average conditions in December to January continued in February in south-central Angola, northwestern Namibia, northeastern Mozambique, east coast of Madagascar, parts of southern South Africa, and parts of central Oromia region of Ethiopia. Wetter-than-average conditions in December to January were followed by above-average February rainfall in Botswana, southern Zimbabwe, southern Mozambique, and Liberia.
Russia Record snowfall (73cm) was reported in mid-February in southern Russia, near Sochi and the Black Sea, which appears to be captured in the CHIRPS products. See here for more on this event.
Tajikistan A station near the cities of Chkalovsk and Khujand in northern Tajikistan was omitted from February’s CHIRPS through the R-checks process. Evidence for the station’s removal was found upon comparing the station reported value of 319.9 mm to CHIRP, the satellite-based estimate, and the CHIRPS climatology near the station. CHIRP recorded a value between 18 mm and 24 mm for the same area. Given that the station report was also far higher than climatology (~20mm), the report was deemed potentially inaccurate and omitted.
Pakistan Across northern Pakistan, multiple stations reported February precipitation totals that were lower than CHIRP estimates. For example, a station near the town of Dir in northwest Pakistan recorded a February monthly total of 47.7 mm, indicating below average conditions, while CHIRP values nearby are around 130 mm, indicating near average conditions. Given that multiple stations had this feature, all those reports were blended into CHIRPS. This CHIRP and CHIRPS Rchecks discrepancy will be noted and, if found to be recurring, will be subjected to further scrutiny.
Honduras The new stations in Honduras continue to show helpful data. Rchecks note: For some reason some switched from fGSOD in January to fGTS in February.
California Below-average precipitation in February 2021, according to CHIRPS and with support from many stations. Z-scores for February range from around -0.8 to -1.4. While parts of central California received above average January precipitation, the prevailing conditions from October to February have been drier-than-average across California.
Rchecks plots All stats for all regions fell within the previous minimum and maximums.
Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Laura Harrison, Austin Sonnier, Pete Peterson
January 2021
Honduras There are new stations in Honduras reporting to CHIRPS, from COPECO. January 2021 CHIRPS data blended in 42 of these stations. Rchecker Seth reports that their values look good.
Kenya There is one station report included in January 2021 CHIRPS in Kenya, a GSOD in western Kenya. This is highly out of the ordinary. CHIRPS has always had at least 10 stations, GSOD and GTS sources, blended into monthly data in Kenya. According to Pete, the low count is not due to a processing issue at CHC, as all the GSOD and GTS station reports come to the CHIRPS process via a single download and these exist in many other countries for January 2021. One possibility is that more of Kenya's stations had not yet been reported to that source by the time of download. The implication of low station count is that January 2021 CHIRPS data in Kenya is mainly based on CHIRP and some influence from stations in Ethiopia, Somalia, Tanzania, and potentially Rwanda. Other nearby countries do not have station reports in CHIRPS this month.
Southern Africa Since October 2020, Southern Africa's monsoon season has exhibited lower-than-average monthly rainfall in Angola, northeastern Mozambique, and Madagascar and higher-than-average rainfall in central region areas. January 2020 CHIRPS data shows one of the more extreme months thus far into this season in this regard, with extensive above average rainfall from Namibia to central-southern Mozambique and including southern Zambia, Malawi, and central-northern South Africa. This expansive wet signal is coming from CHIRP, the satellite-only part of CHIRPS, and also from many station reports. However, across this wide region there are also station reports that show lesser amounts, and below-average or average rainfall. These seem to be swamped out by the combination of a wet CHIRP and numerous wet stations. So while there seems to be evidence for wetter-than-average conditions in January in much of continental Southern Africa, there is probably a more spatially mixed pattern than CHIRPS data indicates.
Burundi Conflicting reports from CHIRPS Prelim, CHIRPS final, and news media. According to reports, Burundi suffered from extreme rainfall in early and late January, which appears to be captured by CHIRPS Prelim. However, CHIRPS final shows below average rainfall for the month of January. It is unclear what station values led to this discrepancy between CHIRPS Prelim and Final. See here for that media report.
Tanzania CHIRPS stations capture extreme rainfall and flooding that occurred in the southeast (Mtwara) region of Tanzania in mid-January. See here for the report on the floods.
Central America Atlantic coast of Costa Rica and Panama shows quite high rain amounts in CHIRP, and the stations bring these satellite-based estimates lower. Looks like the high values in neighboring Nicaragua should come down, too, but no stations there, unfortunately.
South America The blended stations are increasing rainfall values compared to CHIRP, resulting in better agreement between CHIRPS and CMORPH estimates, in the Brazil/Paraguay area and the Amazon.
Rchecks plots A new low for CHIRPS - CHIRP Mean for Haiti. The value is only 12 mm lower then previous values though. New highs for CHIRPS mean, Z score mean and CHIRPS - CHIRP mean in southern Africa. But all are minor and it appears that stations significantly increased estimates in the region. See the Southern Africa entry above for more commentary.
Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Laura Harrison, Austin Sonnier, Pete Peterson
December 2020
Mozambique and Zimbabwe Stations (and CHIRPS) accurately captured heavy rainfall from Tropical Storm Chalane, which made its second landfall in southern Mozambique, in Beira, after passing over northern Madagascar in late December. The storm brought high winds and ~200 mm of rainfall to south central Mozambique and Zimbabwe, resulting in some flash flooding. However, damages were reported to be minimal, relative to expectations. You can read more about Tropical Storm Chalane at ReliefWeb and at Reuters.
Mozambique and Madagascar Stations and satellite-based estimates (CHIRP) are in agreement regarding the December 2020 deficits in northern Mozambique and southern central Madagascar. Approximately 5 stations in each of these regions report large deficits for December. At a seasonal time scale, deficits have persisted and have accumulated to led to the October 1st 2020 to January 15th 2021 period as having the lowest rainfall total on CHIRPS record in some of these areas. The CHC Early Estimate historical rank map shows this, here. More CHC Early Estimates are available at the UCSB Climate Hazards Center monitoring and forecasting site.
Angola CHIRP is showing that December 2020 was drier than average across much of western Angola, and that an area in central-western Angola had 100+ mm deficits. Several SASSCAL stations in southern Angola reported that December was drier than average. Due to very few stations in CHIRPS in Angola, much of the dry signal is coming from CHIRP.
Saudi Arabia Unique storm cell in northern Saudi Arabia. CHIRPS recorded above average December 2020 rainfall in the northeast region of Saudi Arabia. This appears to be associated with an observed extreme storm system that created one of the largest tornadoes on record for this region, along with heavy rainfall and hail. Video of the tornado is available from The Watchers news at this link. Other local news organizations also reported on the event. Stations in the region, as well as in Kuwait and southern Iraq, reported rain gauge measurements in the 55.0-70.0 mm range to CHIRPS. These reports corroborated the rainfall event and, importantly for CHIRPS data, increased estimates in northern Saudi Arabia, raising the ~ 11 mm satellite-based CHIRP anomalies to ~ 26 mm anomalies in CHIRPS.
Tajikistan A station in southern Tajikistan, which recorded a rain gauge monthly value of 2.0 mm, was eliminated from the December’s CHIRPS through the R-checks process. Evidence for the station’s removal was found upon comparing the gauge value to both the CHIRP value and its two nearest neighbors. The CHIRP values in the area immediately surrounding the station in question, southern Tajikistan, eastern Afghanistan, and northern Pakistan, range from 30 mm to 90 mm. Furthermore, the two nearest neighbors recorded a rain gauge value of 28 mm and 53.4 mm.
United States Olympic Peninsula-- Several stations reported much higher values than CHIRP, and were responsible for raising CHIRPS estimates here by 100 mm to 200 mm compared to CHIRP.
Rchecks plots All the Rchecks plots look good.
Contributors: Marty Landsfeld, Austin Sonnier, Will Turner, Seth Peterson, Laura Harrison, Pete Peterson
November 2020
Somalia- Cyclone Gati Cyclone Gati, the strongest storm to hit Somalia in at least 50 years, brought heavy rains to Ras Hafun (the eastern point of the Horn of Africa). SWALIM stations reported 156mm, 151mm, and 71mm to normally dry areas here. CHIRPS final for November failed to reproduce these amounts in values and anomalies. Z scores, however, do show that CHIRPS amounts were historically extreme. CHIRPS users would thus want to work with percent of averages, or z scores, if they need to show the severity of the monthly rainfall in these Gati-affected areas. The CHIRPS version 2 estimates are closely tied to variations from climatology, and this is an excellent example of how that technique can go wrong. Efforts are being made in the production of a new version of CHIRPS, version 3, to limit this kind of problem.
Eastern Africa November brought below average rainfall to much of the eastern Horn of Africa, according to CHIRPS and other rainfall products. Some noteable differences between CHIRPS prelim and final are that November rainfall anomalies are more negative in CHIRPS final than in CHIRPS prelim in central-eastern Kenya, southwestern Somalia, and in some of southwestern Ethiopia. Unlike prelim, CHIRPS final shows fewer areas in southern Somalia with pockets of average to above average rainfall-- rather, below average is shown across most areas. This signal is reflecting reports from 15 stations there, of which only two show average to above average rainfall. None of these reports jump out as being bad values. There is an area where reported localized rainfall is not being represented in CHIRPS: A very wet station in dry northeastern Kenya reported 157 mm (~ 100 mm above average) but CHIRPS shows below average across this area with no clear sign of localized rainfall. By comparison, CHIRPS prelim does show more localized rainfall patterns in these areas.
Mozambique We are omitting reports of what appear to be false zeros from two stations in the Tete administration of northwest Mozambique. These two stations are located just east of the Cahora Bassa Lake. Other stations, CHIRP, and CHIRPS Prelim are demonstrating November rainfall nearby, as do other rainfall datasets. For example, the CHIRP value at these station locations is approximately 42 mm and the CHIRPS Prelim value for the location is approximately 45 mm. The reported 0 mm amounts at these stations had translated into ~ -54 mm anomalies, while CHIRPS Prelim anomalies were smaller, approximately -10 mm.
Europe November 2020 was drier than average across much of Europe, and large deficits were seen in eastern Southern Europe. Deficits in northern Italy and Mediterranean coast areas of Montenegro and Greece were some of the largest. Amounts in those areas that were 100mm to 150mm below average. The CHIRPS signal is coming from numerous stations across the region and CHIRP.
Cuba A slightly wet station (284835) on the dry side of Cuba jacks up values on the wet side to 600mm of rain, far above the values that CMORPH shows (it agrees with CHIRP).
Indonesia In Indonesia (Irian Jaya)/Papua New Guinea, there is an interesting and questionable pattern in CHIRPS. It shows much wetter than average in the south and below average in the north. The CHIRPS pattern appears related to the anomalies coming from one station in each area. However, the pattern looks questionable due to there being a spatially less distinct anomaly pattern in prelim, and the surpisingly higher than average amounts estimated in CHIRPS' very wet area compared to the southern station.
Rchecks plots
Contributors: Marty Landsfeld, Austin Sonnier, Seth Peterson, Laura Harrison, Pete Peterson
October 2020
Southern Africa data Update, 11/20: CHIRPS October 2020 data has been corrected in response to this issue. It was discovered that there were two factors responsible for the problems: (a) Errors in Mozambique station reports from a preprocessing step (quick correction of the errors enabled the reports to be blended in the corrected CHIRPS Final) and (b) that the reports had been included in a 2nd blending step that overrode many reports in South Africa. The wet Mozambique reports had been thought to be possible, due to news reports of extensive flooding, but the corrected monthly totals look much more reasonable. These show October 2020 totals in Mozambique ranged from localized above average (this may still correspond to flooding reports) to minor deficits in central and other areas. In addition to corrected CHIRPS data, another positive outcome is that the Rchecks process came in handy and a new data layer showing 2nd blended stations will be tested to help diagnose similar issue in the future. Previous: CHIRPS October 2020 data is wetter than is indicated by numerous stations reports in part of eastern South Africa. Users of CHIRPS preliminary data will notice that CHIRPS final is much wetter than preliminary data. See here for a snapshot of October 2020 anomaly from these datasets: from left to right, CHIRPS preliminary, CHIRPS final with station anomalies indicated in the overlaid boxes, and CHIRPS final. The 'wetting' in CHIRPS final in Mozambique is in line with stations reports in Mozambique that were included in final data (and not in preliminary data). These stations are in line with reports of flooding in the provinces of Niassa, Nampula, Zambézia and Manica and in Maputo city. Wetting in eastern Zimbabwe is probably coming from the wet Mozambique observations too. Something also shown by the data comparison snapshot, is that in east central South Africa most of the stations report below average rainfall, like preliminary and other datasets, but CHIRPS final shows above average. This issue could be related to one or more things, and is currently unresolved. One factor could be that local or regional wet station(s) are having a disproportional, primary influence in the blending procedure in this area. Preliminary data from the South African Weather Service also show a much drier October than does CHIRPS final in east central South Africa, shown here. CHIRPS users should thus be cautious about the wet conditions shown by the CHIRPS final data in that area.
Ethiopia Southeastern Ethiopia CHIRPS data appears to underestimate rainfall for the September 1 to November 10th, 2020 period, compared to blended data that includes CHIRPS and a larger number of Ethiopia NMA station reports. Some of the data difference could be related to a station gap in the southeast in the October CHIRPS Final data. Typically there is one NMA report blended into CHIRPS Final data, in Somali's Gode zone, but this month it reported as a no data value. A different source shows 44mm reported at that location in October 11-20th, 2020. There is low station density in this part of Ethiopia in CHIRPS Final, and the low estimates were possibly influenced by stations farther away, such as below average reports in Somalia. This may help explain why CHIRPS Final is drier than CHIRPS Prelim in this region in October 2020 data.
Italy and eastern Europe Stations captured extreme rainfall values in Italy and eastern Europe at the end of October. Severe weather swept across Europe at the end of October. Strong winds, roughs seas, heavy rain, and thunderstorms caused deadly flooding, damage and power outages in Italy, Croatia, Slovenia, Bosnia, France and Switzerland.
Vietnam October was an active typhoon month for parts of southeast Asia. Typhoon Molave, also known as Typhoon Quinta in the Philippines, made landfall over the Philippines, Vietnam, Laos, Cambodia, and Thailand. A large swath of Vietnam's central coast saw flooding as October monthly totals reached well over 1,500 mm with many areas reaching over 1,800 mm. A station between the cities of Da Nang and Hoi An, for instance, recorded a value of 1863.3 mm. These totals are anomalously high for October in Vietnam. The CHIRPS anomaly for the central Vietnam coast was well over 1000 mm. See here and here for more information about the typhoons.
United States and Mexico A dry October for the western and central United States, Texas, and in northern and central Mexico. CHIRPS data shows October 2020 rainfall as being 0.5 to 1.5 standard deviations below average in many areas.
Mexico Tropical Storm Gamma brought heavy rain and damage to the Yucatan Peninsula on October 4th, 2020. CHIRPS is showing high amounts for October in coastal areas that were affected, with anomalies for the month ranging from 300 mm to 600 mm above average. More on Gamma here.
Panama There were only 3 stations reporting to CHIRPS final this month, usually there are ~14
Rchecks plots Southern Africa posted a new high for CHIRPS - CHIRP of 13mm. The previous high was 10mm. This is related to the wetting in CHIRPS final; please see the entry 'Southern Africa data' above for more on this.
Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Laura Harrison, Pete Peterson
September 2020
New station sources have been added to CHIRPS Two new sources of in situ rainfall observations were implemented in this month's CHIRPS, Brazil-Cemaden and Costa Rica-IMN. This exciting addition brings the number of sources to fifteen. In addition to global coverage from GHCN-daily, GTS, GSOD, and GHCN-v4, special contributions from national and regional sources are a big reason CHIRPS is able to provide quality rainfall estimates. Special contributions provide enhanced in situ coverage in Southern Africa, Mozambique, Somalia, Ethiopia, Brazil, Chile, Colombia, Panama, Guatemala, Costa Rica, and Mexico. There are plans to include Trans-African HydroMeteorological Observatory (TAHMO) TAMHO reports in the future to increase coverage in Africa.
New source Rchecks This included visual checks and comparisons of reported values to multiple datasets for September 2020. Brazil-Cemaden and Costa Rica-IMN reports passed these checks and were given the green light for including in CHIRPS. Rchecker Seth noted that in Costa Rica, "the 15 new stations seem to be of good data quality and lead to higher estimated rainfall amounts in CHIRPS in mountainous areas." TAMHO reports for Uganda and Kenya are also exciting, given their dense coverage, however it was determined that these receive a longer evaluation period. Specifically, there were numerous reports with very low (< 10mm) rainfall values in Uganda and western Kenya. Much higher rainfall amounts (50-200 mm) were to be expected, according to recent reports from the Kenya Met Department and IGAD ICPAC.
Japan and Korean Peninsula CHIRPS is showing very high rainfall values in the region affected by Typhoon Haishen/Kristine, the first super typhoon of the 2020 Pacific typhoon season. It peaked as a category 4 super typhoon, then at a weaker stage made landfall in southwest Japan and the eastern Korean Peninsula. This powerful storm left 2 dead, 4 missing, and over 100 injured in Japan. Several stations included in CHIRPS registered highly anomalous amounts for the month, including a station on Fukue Island, the southernmost of the Goto islands in Japan (+441.3 mm above average) and in the South Korea coastal city of Gangneung (+475.0 mm above average, 614 mm total). The impact in the region can be seen on CHIRPS September anomaly map here.
Pakistan Although missed by CHIRP, station data provided vital information regarding above-average precipitation in September which contributed to an already heavy, deadly monsoon season in northern and southeastern Pakistan.
United States With 10 major storms, September 2020 was the most active month on record for the Atlantic hurricane season. One of the most damaging storms in the Gulf Coast and Mexico, Tropical Storm Beta, caused over $100 million in damage and a fatality in Texas. CHIRPS for September 2020 shows monthly totals that are far above average (greater than 2 standard deviations from average) in the Florida panhandle, southeast Alabama, southwest Georgia, and central-northeast Texas. Meanwhile, CHIRPS shows extreme low September rainfall in the upper Northeastern United States, where drought conditions are ongoing. Similarly, much of the West and Great Plains regions and central-south Canada had a much drier than average September. The West is under Extreme to Exceptional Drought conditions. The latest US Drought Monitor can be viewed here.
Africa dataset differences Rchecks observed there are very large differences between CHIRPS and NOAA ARC2, and compared these to other data. CHIRPS, TAMSAT, and PERSIANN show a band of generally above average rainfall in the Sahel region and parts of northern and western East Africa, and below average and mixed condition rainfall equatorward and for a large part of Central Africa. ARC2 is wildly different, with that data showing highly above average rainfall across nearly all of these areas. Comparison of datasets can be viewed at the following links. Map of September 2020 rainfall TOTAL and ANOMALY. (Top-left, CHIRPS; Top-right, ARC2; bottom-left, TAMSAT, bottom-right, PERSIANN)
Rchecks plots New highs for CHIRPS-CHIRP mean in Africa and Sahel but not extreme: eog /home/chc-data-out/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.*.stats.2020.09.png
Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Laura Harrison, Pete Peterson
July 2020
Ethiopia Very large station values, several over or near 500mm, but they are in good agreement with PERSIANN-CCS. Brazil The dry season is very dry in Northern Argentina and southern Brazil, many stations have 0 values. CHIRP was already quite low, but station data lowers values for CHIRPs. Chili The CMORPH product is showing a lot of rain, ~300mm, in the Atacama desert whereas CHIRPs shows near 0 values. Rchecks Plots All statistics look reasonable. There was tie for the low value for CHIRPS standard deviation in Latin America but nothing extraordinary.
Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Pete Peterson
August 2020
China CHIRPS data shows impact of Typhoon Higos, which made landfall in southeast China at the coastal city of Zhuhai. More on Higos here. The signature of the typhoon on rainfall was localized, and it contrasts with the otherwise drier than average August in the greater southeast China region shown in CHIRPS. For instance, in Zhuhai, and the area closely surrounding it, a report shows 190 mm above average while just under 175 kilometers inland, reported anomalies are -51 mm to -121.9 mm.
North Korea and South Korea CHIRPS is depicting observed extreme rainfall in North Korea and South Korea. The events led to fatalities and flooding and major damage to farmland, homes, and infrastructure. More here. There are ~15 stations reporting heavy, highly above average rainfall in North Korea and northern South Korea. Some of these in northern North Korea report >1000mm! Unable to check the accuracy of those, and of course they influence CHIRPS, but the CHIRPS values seem fine (albeit very large). The outcome on CHIRPS is that stations increased CHIRP anomalies to around 2x CHIRP.
India and Pakistan Pakistan and western India experienced extremely heavy rains and catastrophic flooding. More here and here. CHIRPS Rchecks for August displays station anomalies as high as 703.7 mm in west India and 416 mm in southeast Pakistan.
United States Station values significantly increased CHIRPS estimates along the eastern seaboard while decreasing estimates in midwest and northwestern quarter of the country.
Mexico Quality check on what CHIRPS shows in southern Mexico (Pacific coast): Noticed that stations are quite high compared to CHIRP, which shows moderate precip. This produced comparatively much higher values in CHIRPS, which better matches CMORPH estimates.
South Sudan Interesting that ARC2 shows a strong wetter than average August while CHIRPS, CHIRP, and PERSIANN show below average rainfall in much of eastern and central South Sudan. TAMSAT shows a mixed and mainly wet signal there. More analysis could be done to gauge if CHIRPS is wrong or right, but either way there are no stations to discuss removing there.
Rchecks plots All statistics are within normal ranges. The Africa Long Horn set a new high for mean z-score but marginally at less than 0.5.
Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Laura Harrison, Pete Peterson
July 2020
Ethiopia Very large station values, several over or near 500mm, but they are in good agreement with PERSIANN-CCS. Brazil The dry season is very dry in Northern Argentina and southern Brazil, many stations have 0 values. CHIRP was already quite low, but station data lowers values for CHIRPs. Chili The CMORPH product is showing a lot of rain, ~300mm, in the Atacama desert whereas CHIRPs shows near 0 values. Rchecks Plots All statistics look reasonable. There was tie for the low value for CHIRPS standard deviation in Latin America but nothing extraordinary.
Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Pete Peterson
June 2020
Madagascar Here is an identified issue with the existing climatology that CHIRP(S) is built around, known as CHPclim, which is causing artifacts in CHIRP, Prelim, and CHIRPS. The new CHPclim is approaching final stages of production, and appears to perform considerably better in this area. Correspondingly, these artifacts will likely be corrected for in CHIRPS 3.0 (release date pending).
Japan Heavy flooding in southern Japan in the news. CHIRP estimated fairly high rainfall but with the addition of stations, the CHIRPs prediction got boosted.
India Station data shows more rainfall than CHIRP. CHIRPS is more accurate but some lower elevation stations having lower rainfall are mitigating the predictions of higher rainfall at higher elevations.
North America Station values reversed a CHIRP estimated dry anomaly in the Pacific NW to become a wet anomaly from the Cascades westward.
Rchecks plots All statistics look reasonable. There was tie for the CHIRPS Max value and Anomaly Max for Southern Africa which were examined and determined to be from an artifact in CHPClim.
Contributors: Marty Landsfeld, Seth Peterson, Will Turner, Austin Sonnier, Pete Peterson
May 2020
Kenya Stations report continued above average rainfall and flooding in the north and central regions of Kenya in early to mid-May. A total of 161,000 households (over 800,000 people) have now been affected across the country. http://floodlist.com/africa/kenya-floods-north-central-regions-may-2020
Caribbean For some reason, in this month, the station part of the CHIRPS algorithm seems to be breaking down for islands. In Cuba, Hispaniola, Hainan Island (also inland central vietnam) there are big differences between CHIRP and rchecks due to stations that are quite a ways away from the area that changes. There are no stations where the changes occur.
Vietnam An area of moderately high precip in CHIRP (and RFE2) gets boosted to over 600-700mm, for no apparent reason.
China Moderate precip in interior of Hainan island in CHIRPS drops 100mm in rchecks because of stations in lowlands on the island.
Rchecks plots A new low CHIRPS - CHIRP for Africa but only slightly. Very low values in most variables reflects the extreme dryness in Haiti
Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson
April 2020
South America In western Amazonia, confluence of Brazil, Oeru, Columbia, is a very large change in Rchecks (lower precip) over a large area that is based on stations quite a distance away, seems less ideal. In SW Amazonia the opposite happens, there is a very large increase in precipitation that is based on sparse stations.
Iran Heavy rainfall in mid-April created flash floods and swollen rivers in several Iranian provinces, including Kerman and Sistan and Balouchestan in the southern parts of the country.
Rchecks plots A new high for CHIRPS Max in the Long Horn of Africa. Nearly double the previous high for the region. This translated into new high CHIRPS max in Africa and globally, but not drastically.
Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson
March 2020
Eastern Africa Above average rainfall and flash floods in early-to-mid-March resulted in tens of deaths and left thuousands displaced across the D.R. Congo, Rwanda, Burundi, Tanzania, and Kenya http://floodlist.com/africa/drcongo-floods-maniema-march-2020 http://floodlist.com/africa/burundi-heavy-rain-floods-march-2020 http://floodlist.com/africa/rwanda-floods-march-2020 http://floodlist.com/africa/kenya-floods-busia-siaya-march-2020
Madagascar Despite a lack of stations, CHIRPS accurately captures significant rainfall over northeastern Madagascar, which reported flooding in mid-March from Tropical Cyclone Herold. http://floodlist.com/africa/madagascar-tropical-cyclone-herold-march-2020
Rchecks plots New low in CHIRPS mean for Latin and Central America by a large amount, > 5 mm. Also, New low in CHIRPS Z-scrore mean for Latin and Central America by a small amount. Z-scores confirm this with much of the regioin well below normal. This extends well into South America and the southern US. Also, PERSIANN and CMORPH confirm the abnormal dryness. See: http://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.lat_amer.stats.2020.03.png
Contributors: Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson
February 2020
Ethiopia Ethiopia CHIRPS data has improved station density, thanks to support from the Ethiopia NMA. There were approximately 100 stations in February 2020 CHIRPS data. This is around two times more stations than in recent data. These stations corroborated and enhanced a weak dry signal also shown by CHIRP in February 2020 rainfall in central Ethiopia.
Australia CHIRPS data shows the much needed rain that eastern Australia finally got in February. The bush fires ended last month after 200+ days of burning, see article here.
Southeast Asia CHIRPS shows a stronger (but still low magnitude) below average signal compared to CHIRP in Thailand and Laos. This is due to reports from numerous stations in both countries
India CHIRPS shows above average rainfall in central east, whereas CHIRPS shows a much weaker signal. This is due to reports from ~6 stations in that area.
Ecuador Higher than normal station values in the rainshadow of mountain ranges caused the values at the mountain ridges to double from 300 to 600 mm. Not ideal. However in Columbia there were a couple of stations near the ridge that were in the 400-500 range so perhaps it's ok.
North America Southern CA had virtually no rain in February 2020 yet CHIRPS is showing estimates in the mountains of over an inch. Big Bear CA station measured zero rainfall, CHIRPS estimated 37.7mm.
CHIRPS processing In recent weeks the team investigated impacts of the two-step station blending process, which is currently a processing step designed to incorporate more recently acquired stations. This showed examples where having the 2nd step resulted in reports farther away than closer stations being blended in the second step and having a substantial influence on CHIRPS estimates. Based on the results of the investigation, Rchecks team is strongly recommending that future CHIRPS processing uses a single pass blending step.
CHIRPS processing Southern Africa CHIRPS data received additional attention in this rcheck. The final version of CHIRPS appears much improved from the first version seen during rchecks. In the first version, the data appeared excessively low in Zambia and Zimbabwe area despite some areas having actually received ample February rainfall. Three SASCAL stations with unrealistic low values were identified- these were the same problem stations identified during rchecks of other recent data. This time these stations were removed from February 2020 data and also permanently removed from future data. The second version of data (after these were removed) showed much more realistic CHIRPS estimates in that area. An odd circular excess wet feature remained, affecting Mozambique and southern Zimbabwe, and it was shown to be due to lack of local stations and influence of stations in South Africa. This was improved by omitting those stations. The result was still realistic estimates in South Africa (where there was high station density even without these) and realistic estimates in the Mozambique and southern Zimbabwe areas. Comparisons to CHIRP and ARC2 data, and previous knowledge from regional rainfall monitoring, were helpful in identifying the problems in pre-final CHIRPS and in confirming that the final, public-released February 2020 CHIRPS looks fine.
Rchecks plots All plots look good and new values fall within historical ranges. There was a new low for CHIRPS Maximum over Africa but just barely.
Contributors: Laura Harrison, Marty Landsfeld, Will Turner, Seth Peterson, Pete Peterson
January 2020
South America In general, pretty good agreement between CHIRP and CMORPH datasets.
Costa Rica Pretty sure this happened last month, too, low values on the leeward side of the country cause areas in Rchecks to have much lower values than CHIRP on the windward side (NE part of CR).
Nicaragua Odd very low rain features in rainfall SE of country near coast. Appears to be in climatology because repeats in other months.
North America Stations greatly increased the CHIRPS estimate in the Pacific NW by a factor of 8 from CHIRP. CHIRPS looks good around Santa Barbara.
Armenia and Azerbaijan We have become aware of a station reporting / CHIRPS measurement issue in Armenia and Azerbaijan. We believe that some stations are reporting solely rainfall measurements, while others are reporting snowfall. As rainfall is roughly one tenth of the snowfall amount, this leads to relatively low CHIRPS precipitation values. CHIRPS values in this area should be interpreted carefully, as the rainfall representation is likely inflated, and the snowfall representation is significantly deflated. In the attempt to make the most accurate precipitation dataset possible, this issue is on our radar and will be addressed soon. Thank you for understanding.
Australia and Indonesia Stations generally show same pattern in anomaly as CHIRPS, which is good to see for that satellite-based product. In Indonesia stations bumped up localized rainfall amounts in several areas.
Afghanistan, India, Pakistan Stations made big difference increasing CHIRP values. The wetter than average signal is coming from 20+ stations in the region, so it seems believable.
Thailand Very nice station density in this country. 25+ stations all showing mild drier than average signal. CHIRP was near average. CHIRPS seems to meet halfway, showing very mild deficits.
Rchecks plots Plot comparisons look normal. There is a new CHIRPS Max high for the Africa Long Horn but (~550mm) but just barely higher than the previous high
Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Austin Sonnier, Will Turner, Sari Blakeley, Pete Peterson
December 2019
Australia and Indonesia CHIRPS shows below average December rainfall in most of Australia and Indonesia. Largest deficits are in the 100-200mm range. According to Australia's Bureau of Meteorology, December 2019 had the lowest rainfall on record for the country as a whole and "rainfall was in the lowest 10% of historical observations for much of the eastern mainland and north of the Northern Territory. (link)" We did not examine CHIRPS historical ranks but these are areas with large anomalies and negative z-scores. A big reason for agreement with BoM would be that CHIRPS blends in hundreds of stations across the country.
Brunei, Malaysia (island areas), and Indonesia (near Malaysia border) Consistent with reports of flooding from high intensity rain during December, CHIRPS shows above average December totals (100mm-200mm anomalies). The rain event led to flooding and evacuation of several hundred people. (link to report). In this area several stations reported very high values (~600mm), which increased CHIRPS compared to CHIRP. The flood report and consistency between stations supports the wet CHIRPS signal there.
Zimbabwe Large deficits in CHIRPS across the country. In northern and western Zimbabwe, we note that the CHIRPS anomaly map indicates a larger dry signal in those areas than does CHIRP. This corresponds to CHIRPS values being lower than CHIRP values (by around 20 mm). We remind users that there are no stations in Zimbabwe being blended into CHIRPS, and as usual this results in uncertainty in the data there. Values are based on stations outside the country being blended into CHIRP. In this case for December 2019 data, Zimbabwe is surrounded by ~20 stations that show below average rainfall. These are in Namibia's Caprivi Strip, Botswana, Zambia, Mozambique, and NE South Africa. Between this and the below average CHIRP signal, the dryness in Zimbabwe indicated by CHIRPS appears reasonable.
Portugal, Spain, and France Once again (~3 months in a row), we see that CHIRP and Prelim underestimated rainfall in parts of Portugal, Spain and France (CHIRPS Final is considerably wetter than both CHIRP and Prelim). We have now seen several months of anomaly disagreement between CHIRP and Final in parts of these 3 countries. For monitoring, users should be aware of this discrepancy between CHIRP/Prelim and CHIRPS Final.
Costa Rica and Panama CHIRPS shows mixed anomalies while CHIRP shows largely above average, prompting some investigation as to the cause and which is correct. Compared both products to CMORPH. CMORPH values on land also show mixed anomalies, and while spatial patterns are not the same as CHIRPS, this aspect makes CMORPH in general was more similar to CHIRPS than CHIRP. CMORPH did show above average rainfall offshore. No problems stations in CHIRPS were identified. In terms of station agreement with CHIRPS values, there are discrepancies along the Caribbean coast. Here, some stations report higher rainfall than CHIRPS. One possibility is that the CHIRPS interpolation is being influenced by stations on the Pacific side, or at least on the other side of the mountains, that have below average rainfall.
Honduras and Nicaragua (1) In eastern Honduras and northeastern Nicaragua CHIRPS shows below average rainfall in December, ranging from deficits of 50mm to 140mm. This is in line with a dry signal also shown by CHIRP, but is more intense. Stations are also playing a role here, but these are not well distributed. One near the coast that shower a report that is much lower than CHIRP, by ~50%, and it may have a role in producing the largest difference between the products. This station reports frequently and was not deemed problematic in this check. (2) In northern Honduras, a similar comment to the one for Costa Rica and Panama. On the north coast of Honduras and the islands CHIRP shows high rain ~300mm. 2 of the stations in this area also show reasonably high rain, so this doesn't seem unreasonable. Also CMORPH shows a blob just offshore of this region. When the other more inland stations are averaged in the values on the north coast of Honduras drop down to ~200mm, probably a bit low.
North America Station values increased the rainfall estimates in the Pacific NW reducing the dry anomalies experienced there this winter. The news also reports dryness in this region, see report here.
CHIRPS processing (1) False zero screening was examined in east Brazil, as CHIRPS diagnostics plots show what looks like a large cluster of stations being excluded for this reason. We compared CHIRPS and this screening map to Brazil INMET's map of December 2019 rainfall. The INMET map showed rain where many of these potential false zero reports had been removed. CHIRPS estimates look similar to INMET estimates in the examined area. False zero screening therefore appeared to be working fine here. (2) Possible problem resulting from 2nd blending step. A 2nd blending is done to incorporate stations added to the database after 2015. In Rchecks it was observed that a station involved in 2nd blending was possibly having more influence on CHIRPS values than closer stations. See 'Zambia (NE) entry' on the watchlist for more information. The impacts of the 2nd blending step should be further examined.
Rchecks plots There was a new high value for CHIRPS in South America of around 1600 mm. Other than that all other stats look fine. http://data.chc.ucsb.edu/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.*.stats.2019.12.png
November 2019
East Africa Highly above average rainfall occurred in East Africa during November 2019, according to CHIRPS Final. Some of the more historically extreme amounts are in Kenya, southern Somalia, southern Ethiopia, Uganda, and northern and coastal Tanzania. Estimates show some areas with 100-300 mm above the long term average for November. In many of these areas CHIRPS Final estimates are higher than CHIRPS Prelim, due to blending of station reports into Final. Despite the increased wetting in Final in some areas, the regional wetter than average signal is consistent with what Prelim had indicated earlier. Extreme wet conditions during October to December 2019 are related to a strong positive Indian Ocean Dipole (IOD) mode and warm ocean temperatures. More explanation about the IOD can be be found in this article by The Weather Channel.
Panama and Honduras Stations being blended created more realistic rainfall estimates, compared to the satellite-based CHIRPS estimates. Assessment based on comparison to CMORPH data and review of CHIRPS (too high) versus several blended station reports.
Portugal, Spain, and France Significant discrepancy observed between CHIRP and CHIRP+Stations (CHIRPS), as stations across northern Portugal and Spain and western France report heavy precipitation for the month of November. According to news reports, much of this precipitation came in the form of snow and thunderstorms.
North America Station measurements reduced the CHIRP estimates along much of the west coast and Sierra Nevada mountains.
CHIRPS processing The GHCN-v2 monthly product was recently replaced by a new version, v4. GHCN-v4 monthly contains thousands more station reports than v2, so it is an exciting in situ source to blend into CHIRPS. Efforts were made to do so for the November 2019 CHIRPS final data, but during Rchecks, a problem with the v4 values was identified. In some regions like East Africa GHCN-v4 monthly values were unrealistically high. The problem may have been caused by a processing error, or something else, and the decided solution was to wait on using this new source until more time could be spent quality checking the data. This new source can be included in the new version of CHIRPS due in 2020.
Rchecks plots Regional statistics did not have any outlier values.
October 2019
East Africa East Africa was very wet in October 2019. According to FEWS NET, flooding has displaced more than 700,000 people in Somalia, Ethiopia, and Kenya since early October See here for the report. CHIRPS October data shows very high amounts in southern Ethiopia, southern Somalia (Bakool, Gedo, and and Bay regions), in Kenya (eastern, central, and western areas), Uganda, and parts of Tanzania (L. Victoria and northeast). Many of these areas show > 200 mm amounts, and localized areas show amounts > 300 mm. In and near Somalia, some of highest amounts are in upstream drainage areas of Juba and Shabelle Rivers, along which major damages related to flooding in populated and agricultural zones have been reported. In this area in particular there are ten station reports from SWALIM that are blended into CHIRPS, and comparison of these reports and CHIRPS estimates shows general agreement between the two. Most CHIRPS estimates are within ~25mm of the reported values near the same location, though CHIRPS estimates are higher than reports in northwest Bay by ~100mm. Both reports and CHIRPS show agreement as to October amounts being higher than average- 1 to 2 standard deviations above average in this part of Somalia. Across much of East Africa, October 2019 CHIRPS values are substantially wetter than average, and many of these are historically prominent at 2 to 3+ standard deviations above average.
Southern Africa CHIRPS shows a moderately drier than average October across a large area of Southern Africa, with larger, more substantial deficits in South Africa and Lesotho. October deficits are between 10 to 20 mm below average in Zimbabwe, Botswana, and parts of southern Mozambique, Zambia, and northeastern Namibia. In eastern South Africa and Lesotho October totals were ~50 mm below average. Of all the countries South Africa has highest station density (from GSOD, GTS, and GHCN monthly), and CHIRPS estimates are close to their reported values. Elsewhere, blended reports from SASSCAL and other sources also show agreement with CHIRPS estimates. It is early in Southern Africa's main period of annual rainfall (October to April) and cropping season, and the deficits outside South Africa and Lesotho were relatively small, but these were a notable departure from past Octobers, with amounts being 1 to 1.5 standard deviation below average and in parts of South Africa, up to 2.5 standard deviations below average.
France Stations blended in CHIRPS captured heavy rainfall in southern France and northern Spain. The town of Béziers, France saw 198mm (nearly 8in) of rain - or about two months' average rainfall - in just six hours on the morning of 10/23. See the BBC article here. Across Spain, Germany, and Switzerland, stations reported an anomalously wet month of October, which was otherwise missed by CHIRP.
Japan CHIRPS October data shows the rainfall impacts of Typhoon Hagibis in Japan. Typhoon Hagibis which made landfall near the Izu Peninsula on October 12, 2019. Once making landfall, Hagibis moved NNE transecting the coast just east of Fukushima. It deposited a significant amount of precipitation along the eastern flank of central Honshu, the largest and most populated island in the Japanese archipelago. According to Accuweather’s documentation of precipitation in Fukushima, on October 13th alone, 19.18 in or approximately 487 mm of rain fell. During Rchecks it was observed that two stations reported markedly lower values than neighbor stations. These reports of approximately 145 mm were at the cities of Fukushima and Yamagata. Compared to their surroundings, which ranged from 295-435 mm, and the well documented torrential downpours resulting from Typhoon Hagibis, these station reports may be underestimates. Overall however, CHIRPS data registered the high amounts coming from a high density network of 60+ stations. CHIRP, the satellite-based part of CHIRPS, also showed above average rainfall but the stations substantially increased estimates and were responsible for more accurate spatial details in CHIRPS compared to CHIRP.
United States CHIRPS data shows plenty of low z-score values in the west, verifying a very dry month as noted by the California Weather Blog.
Central America/Caribbean Cool windward/leeward rainfall effects noted in station data reports in the eastern Caribbean
Southeast Asia October amounts were below average from Myanmar to Taiwan, according to CHIRPS. This signal comes from agreement between CHIRP and stations in Thaliand, southern Vietnam, and Taiwan. Stations tended to increase the size of deficits, compared to CHIRP. Stations and CHIRP in northern Vietnam agreed as to above average amounts there.
India CHIRPS shows most of southern India as wetter than average in October, which exception of in northern Tamil Nadu and some nearby areas. The signal is coming from both CHIRP and stations, though the stations increased CHIRPS amounts compared to CHIRP in most of the wet areas. Their blending also increased estimates in southern CHIRP-deficit areas.
Australia We note a circular feature in CHIRPS in eastern Australia- this is centered on a station report that is substantially wetter than surrounding reports. CHIRP shows marginally above average amounts in area, so the station itself is possibly fine. There is no similar feature visible in the October CHPclim, so it is not coming simply from the CHIRPS climatology, but it is being produced by some aspect of the CHIRPS algorithm. This type of thing can be seen in other months of CHIRPS data in Australia. Ideally this will be corrected in next version of CHIRPS.
Chile/CHIRPS algorithm There appear to be high rainfall totals in the southern Chilean Andes, according to CHIRP, but there are no station reports are in that area. Blending of stations in the central valley, which showed low to moderate amounts, seem to have reduced the high elevation values. Seems like this could be an issue in other parts of the world, though perhaps they are better instrumented. Future formal CHIRPS assessments that may help improve blending strategies would include an examination of CHIRPS accuracy in high elevation/high topography regions. Perhaps elevation trends in the Cascades or Sierra Nevada could be useful to inform the veracity of high elevation estimates in South America. CHIRPS blends a high density station network in Guatemala and may be incorporating numerous new stations in Chile, so topography-related assessments would be useful.
Rchecks Plots New highs for region-average CHIRPS Mean and Z-score mean for the Sahel domain, and for the entire Africa domain, but these are not very far from previous highs.
Contributors: Laura Harrison, Will Turner, Seth Peterson, Austin Sonnier, Marty Landsfeld, Pete Peterson
September 2019
Laos A station in southern Laos captured the heavy rainfall from Tropical Storm Podul and Tropical Depression Kajiki, which hit one after another in the first two weeks of September 2019. More than 580,000 people were impacted and at least 28 died in the resulting floods. See the ReliefWeb article here. CHIRPS data shows high values in this region due to influence from this station and from other stations reporting high amounts located nearby in Thailand. These stations being blended in produced a substantial improvement compared to the satellite-based CHIRP, which did not estimate high amounts or above average September rainfall in the affected area.
India CHIRPS shows high rainfall amounts. These are based on the high amounts reported by stations. Heavy, extreme rainfall has led to flooding and over 100 deaths in India. The 2019 monsoon season has seen the heaviest rainfall in 25 years. See the Washington Post article here.
United States Impact of the Hurricane Imelda that struck Houston, Texas on September 17th and caused record-setting flooding is shown in CHIRPS, though we find that the satellite infrared-based estimate (CHIRP) greatly underestimated rainfall totals. Two stations around the Houston area reported around 15” and 18” rainfall and the CHIRPS blending algorithm did a fine job recreating estimates seen in an Accuweather article (link to article here). However, high values above 10” were underestimated in CHIRPS.
Republic of Congo CHIRPS data shows below average September rainfall. This signal is attributed to several GHCN-v2 monthly stations. We examined these and found they report intermittently, which makes their reports suspect, but given they agreed in direction (below average) they were retained.
Rchecks Plots Besides a new high in Africa region anomaly (slightly higher than previous maximum), all other stats are in the normal range.
Contributors: Laura Harrison, Will Turner, Seth Peterson, Sari Blakeley, Austin Sonnier, Marty Landsfeld, Pete Peterson
August 2019
CHIRP vs. Prelim vs. CHIRPS Final in Africa Notable difference between Prelim and Final in northern Ethiopia. Final still shows below average rainfall but CHIRPS Prelim and CHIRP were substantially drier. This was indicated by the CHC Ethiopia Special Reports on dekadal rainfall (Diego Pedreros and Diriba Korecha) that do an early blending of Ethiopia NMA stations with Prelim. These can be accessed from https://chc.ucsb.edu/monitoring. Good to know that that monitoring information is reliable. It is worth noting that Final is also wetter than Prelim in southwestern Ethiopia with big influence from a couple of wet (above average) stations. Same thing in Sudan. These signals have cross-product agreement- ARC2 also shows above average rains in similar locations. Across much of the Sahel, we notice that CHIRP did not capture some of the localized heavy rains that stations in Final and Prelim show (Prelim has GTS stations). One of the areas that CHIRP did perform well is in northwestern Cote d’Ivoire. CHIRP estimates agree with stations there.
Niger CHIRPS shows higher than average August rain in eastern areas of Niger including east of Maradi and in Zinder and to just past the Chad border. Heavy August rains likely contributed to soil saturation and high river levels that, after further heavy rains in September, contributed to recent flooding events and fatalities. According to a Floodlist report from September, “Meanwhile the number of flood related fatalities in Niger has increased from the 42 reported a few days ago. In a statement of 10 September, government authorities said that that the ongoing floods have now resulted in 57 deaths and affected 132,528 people. Over 12,000 homes have been destroyed and widespread damage caused to crops and livestock. Flooding has affected some areas of Niger since June to July, but has worsened over the last week, with many of those affected in Maradi, Zinder and Agadez, as well as Dosso and the capital Niamey.” Link to article here.
Nigeria CHIRP captured heavy rainfall for the month of August, which was confirmed (and increased in severity) by the stations in CHIRPS. Northeast Nigeria suffered from flash floods throughout August. According to ReliefWeb, "Above-normal volumes of rain and the associated flooding are increasing vulnerabilities and risks in camps for internally displaced persons. An estimated 21,056 households have been affected by torrential rains and flash floods across Borno, Adamawa, and Yobe (BAY) states." Link to article here.
India CHIRPS stations captured the extreme rainfall events that occurred in southwest India (these were not identified by CHIRP). According to AccuWeather, “Nearly 227,000 people are seeking shelter from the flooding in Karnataka, where 61 people have been killed. Chief Minister B.S. Yeddyurappa told Reuters that the flooding was the worst the state had endured in 45 years.” Link to that report here. Also in line with CHIRPS estimates of highly above average rainfall along the southwestern coast and in central-northwestern India (Madhya Pradesh and Rajasthan) is a report noting that August 2019 rainfall was especially extreme in India (see report here.
CHIRP vs. Prelim vs. Final in Central America Stations in Final enhanced the dry signal seen in CHIRPS in northern Guatemala and some other Central America locations. However, CHIRPS Final looks very similar to CHIRPS Prelim. This is a good thing to see, as monitoring often makes use of Prelim until Final is available (typically the 3rd week of each month). In northern Guatemala the CHIRPS Final values agree well with the numerous station reports that are blended in. Same agreement in southern Mexico. In western Guatemala, as usual there are a ton of stations, and localized variations such as above average rain reports in mountains and mixed anomalies at lower elevations, have trouble coming through. Hard to tell if there is overall under or over estimation there (by Final, compared to stations). It has been proposed to quantify this, as it could help to know if CHIRPS has any clear systematic bias in this and other high station density areas.
Cuba CHIRPS values are clearly influenced in Cuba by a single station with a high rainfall amount. An internet search did not produce explanation for the high amount, but CMORPH data is also higher in this part of Cuba so this station was deemed ok to retain in the CHIRPS data.
Brazil It was noted during Rchecks that, similar to what has previously been seen, the values on the coast south of Salvador are substantially increased from CHIRP to CHIRPS-- they go from 100-200 mm in CHIRP to 300-400 mm in Rchecks despite none of the nearby stations being particularly anomalous.
Rchecks Plots New lows for CHIRPS mean, max, standard dev and z-scores for Haiti. New high for CHIRPS max overall (“Global”) of near 2600 mm but this is not substantially different from previous maximums. A figure showing stats for August 2019 for entire near-global CHIRPS extent can been be seen [/home/ftp_out/products/CHIRPS-2.0/diagnostics/rchecks/monthly_compares/chirps.global.stats.2019.08.png here].
Contributors: Laura Harrison, Will Turner, Seth Peterson, Sari Blakeley, Austin Sonnier, Marty Landsfeld, Pete Peterson
July 2019
Central America July CHIRPS shows below average rainfall across most of Central America. Much of Guatemala, Belize, and El Salvador had deficits of 100-200 mm and totals only reaching between 50-200 mm. 100-200 mm deficits were also in Caribbean side areas of Costa Rica, Honduras and Nicaragua. These areas tend to be wetter and accordingly still received totals of 300-400 mm (and in SW Nicaragua, 450-650 mm). Large deficits were also seen in Panama, and were most pronounced (compared to climatology) in the Azuero peninsula.
Bangladesh Stations reported highly above average rainfall throughout the country. CHIRP also shows above average rainfall but the signal is more amplified in CHIRPS due to the stations. Heavy rainfall was confirmed by a news report that stated the following: "At least 60 000 homes were washed away or damaged in 13 districts across Bangladesh after a heavy monsoon rains hit Bangladesh and neighboring countries over the past week. At least 26 people have been killed and 3 million marooned. Over the past couple of days, rivers overflowed in 122 upazilas, flooding thousands of villages. According to a special flood bulletin issued by the Bangladesh Water Development Board (BWDB) on Thursday, July 18, 2019, rivers Jamuna and Teesta are at levels not seen in 40 years of water level records." -The Watchers (link to article here)
Southeast Asia and Thailand Approximately 30 stations and CHIRP show below average rainfall in Thailand. Stations amplified the CHIRP dry signal. Most of the country is showing deficits-- largest standardized anomalies are -2.5 in some western and other areas. According to a news report by Hawaii Public Radio, Thailand's government says the country is heading for its worst drought in a decade or longer and it is affecting key crop growing regions and water supplies. More on this story and drought in southeast Asia can be accessed here.
South Korea/Japan CHIRP and stations captured heavy rainfall from tropical rainstorm Danas, which drenched the Philippines, Taiwan, South Korea and Japan in mid-July, according to an Accuweather report. Report here
Kenya A GTS station in NW Kenya was omitted from CHIRPS July 2019 Final. This station reported 95 mm which was suspicious given that this area in dry NW Kenya typically receives around 15 mm in July. The report was cross checked against maps in ICPAC dekadal reports for July 2019. These ICPAC reports blend GHA station reports with CHIRP and can be accessed here. According to ICPAC maps, this area did not receive highly anomalous rainfall and the monthly total in that area were around 35mm at maximum.
Mexico Inland of Los Mochis (mainland Mexico, across from La Paz) there is a notable blob (-100 to 150mm) in the anomaly map in the mountains that seems to stem largely from lower elevation stations being below average. Higher elevation stations are only slightly below average.
Italy In Bologna, Italy a station is reading much higher than the neighboring stations and climatology (approximately 9 inches compared to 2 inches). It has a z score of approximately + 4. The station's report was cross referenced with data from Accuweather.com, which reported a monthly total of 1.88 inches with a previously forecast total of 1.5 inches. It seemed that if a highly populated area actually received such anomalous rainfall there would be a report about it, and none was found online. Thus it was recommended that this station report not be included in July CHIRPS.
India There are large differences between CHIRP and CHIRPS in northern areas of India. CHIRPS shows below average but stations show a mixed pattern, with some far northern and northeastern stations reporting highly above average rainfall. Station reports are tending to break up CHIRP negative anomaly areas so that areas with pronounced negative anomalies in CHIRPS are left in eastern India near Bay of Bengal (Orissa) and in a smaller area in northwestern India (Gujarat)
Sudan Unfortunately there were no station reports in CHIRPS data for July in Sudan. This is not atypical, but last month (in June 2019 data) there were ~14 GHCN v2 station reports included.
CHIRPS note 1 In far southern Argentina along the coast, the CHIRPS climatology (CHPclim) has some artifacts that show up in CHIRPS. Here is very high precip in all months (~300-400 mm when surrounding area is ~25mm).
CHIRPS note 2 In Brazil, in this month's CHIRPS, a lower than normal occurrence of duplicated stations was noticed. Also in Brazil, where July climatology is low, there were many more stations than usual (and most with near-zero values), which was interesting. At first a relationship to the false zero screening in CHIRPS processing was hypothesized. We examined Pete Peterson's maps that show false zero screening and also compared July 2019 station and CHIRPS values to the Brazil INMET July 2019 precipitation map (INMET link here). It appeared that the false zero screening was working fine this month. The phenomenon of there being groups of many stations screened in some months and not others, which was clearly shown in the false zero screening maps, was not explained by this examination and would be worth looking into.
Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Austin Sonnier, Will Turner, Sari Blakeley, Pete Peterson
June 2019
Global rainfall and temperature It is interesting to compare global June 2019 CHIRPS anomalies to the global June 2019 air temperatures from Climate Science, Awareness and Solutions' monthly Global Temperature Update. A number of global areas saw both higher than normal temperature and lower than normal rainfall in June 2019. These are southern Brazil (~ 100 mm deficits and temperatures 3+ deg Celsius higher than normal), Central America and some of Caribbean (50-150 mm deficits and temperature 1-2 deg C higher than normal), much of western Europe, West Africa, India and southeast Asia, and in western Australia and northwestern United States. The June 2019 global average was a record high, at +0.93 degC above the 1951-1980 average, and 0.1 degC above the previous record (in 2016). See the June 2019 Global Temperature Update and the CHC EWX to compare.
Sudan High amounts of rainfall and flooding in western Sudan is shown in CHIRPS and is detailed in United Nations Office for the Coordination of Humanitarian Affairs (OCHA) reports: "Flooding in North Darfur has damaged 18 homes in Kebkabiya and 550 homes were destroyed or damaged in Sarafaya village (outside El Fasher). A mission to Tawilla following reports of flooding that occurred on 4 June found 6,198 people in need of assistance. In Leiba, South Darfur, an inter-agency mission identified 325 people affected by flooding caused by torrential rains on 8 June." (Sudan Flash Flood Update No. 8, 20 June 2019 )
Western Europe CHIRPS show below average rainfall in much of western Europe.This signal is coming coming both stations and CHIRP. In Austria the stations showed higher severity of deficits than CHIRP.
Panama All CHIRPS variations (CHIRPS, CHIRP, CHPclim show a North-South swath of high rainfall values. Does not look like a physical rainfall feature. Is also in the preliminary v2 of CHPclim. Would be good to find out what is going on there.
North America Stations often appear to increase estimates in the eastern US. Indication of potential systematic underestimation of rainfall there by CHIRP.
Rchecks Plots New lows for CHIRPS mean, max, std dev and z-scores for Latin America but nothing extreme. New highs for CHIRPS mean and std dev for Africa Long Horn but nothing extreme. New high for CHIRPS Anomaly maximum by ~50% in Sahel. Identified this as being in western Sudan, where there were reports of flooding in June. See entry above.
Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Pete Peterson
May 2019
Ethiopia The higher than average precipitation in the southwest is mainly coming from CHIRP (satellite-based estimate) information. Based on comparison to station reports, the CHIRPS final estimates are likely too wet there.
Somalia Rchecker Marty says, "Nice to see no false zeros in the station reports here!" Marty is referring to one of the things we look for during the pre-release CHIRPS Final Reality Checks. Occasionally we notice cases when a station reports a zero value that is highly at odds with neighboring reports and CHIRP. In such cases we give the report extra scrutiny, and if deemed likely to be a "false zero," e.g. an inaccurate report, we recommend not including that report in the CHIRPS blending procedure. One of the station reports in southern Somalia was omitted for this reason last month.
Cote D'Ivoire No stations reporting for the second consecutive month
Guatemala Great to see a very high station density (> 50 reports) in Guatemala. Reports generally agree with respect to locations of above and below average in CHIRP, with one exception: along the Pacific coast CHIRPS has an above average signal while CHIRP shows below average. Several stations point in both directions, but it appears that the wet signal there is mainly dominated by a clump of wet stations that are overriding the below average signal in other areas.
Haiti and the Caribbean Haiti now has 3 stations reporting to CHIRPS. CHIRP is very different from CHIRPS. The CHIRPS signal in Haiti (below avg in CHIRPS, mixed in CHIRP) is due to these 3 station reports (2 are below avg, 1 is above avg) but also stations in Dominican Republic (all are below average). Hard to know if CHIRP is wrong or if the difference is due to lack of stations in the discrepancy area. Jamaica and eastern Puerto Rico stations indicate below average rain, while western Puerto Rico and central-east Cuba indicate above average rain.
Italy/Croatia Station reports greatly increased CHIRPS estimates (compared to CHIRP).
Russia In southeastern Russia several stations report highly above average rainfall. CHIRP does as well but stations are more extreme. Given agreement, this feature in CHIRPS may be associated with a potentially interesting event. Did not get a chance to explore it further. If anyone reading this has information, please share it with us!
Myanmar The large magnitude of negative anomalies in CHIRPS seems due to below average reports in the neighboring country (southwestern region of China). CHIRP shows below average in this part of Myanmar but to a lesser magnitude. Overall, a below average signal in the region is supported by numerous stations and by CHIRP (across Myanmar, to north and east across southern China, and to west in Bangladesh and eastern India)
Philippines Impressive agreement between CHIRP and stations with respect to location of above and below average signal on northern islands.
Rchecks Plots New maximum value for Africa of 2504 mm and anomaly of 2000 mm in Tanzania (islands)
Contributors: Laura Harrison, Marty Landsfeld, Seth Peterson, Pete Peterson
April 2019
South Africa CHIRPS captures the torrential rainfall that led to flooding and fatalities in Eastern Cape and KwaZulu-Natal provinces of coastal South Africa. A station in this area reported 464 mm (18 inches!) in April 2019. The flooding was documented in the April 25th FEWS NET Africa Hazards report.
Caribbean CHIRPS shows that the eastern Caribbean has been experiencing below average rainfall and that, in contrast, April was very wet in some eastern areas like the Cayman Islands. According to a Caribbean Drought and Precipitation Monitoring Network Bulletin, "CIMH said that there is concern for most of the Caribbean that the short term drought situation can impact agriculture, as well as the flow in small rivers and streams except in the vicinity of Cuba, the Bahamas, Jamaica and Cayman islands." Link to report here.
Central America CHIRPS has begun receiving and ingesting a large number of stations in Guatemala, which is markedly improving the estimates. See here for an example of how CHIRPS Prelim for April compares to the pre-release Final, with stations overlaid and the resulting product. In this figure the middle panel shows where stations are located (by pronounced boxes and symbols) and how their reports compare to historical average rainfall. Nice to see sub national variations in the result, due wholly to these stations. In combination with other station data contributions, such as in Panama (see February wiki entry) and Mexico, station density is certainly looking better in this region.
Europe CHIRP largely underestimated rainfall for the month of April. Stations contributed a great deal to capturing multiple storms across Europe and improved CHIRPS.
Portugal/Spain Stations capture widespread wet April across northwestern Portugal/Spain and southern Spain, which was missed by CHIRP.
Switzerland Stations capture extremely wet April across southern Switzerland, which was missed by CHIRP.
USA Station measurements revealed large area of negative anomalies and z-scores. This reversed the CHIRP estimates in Colorado.
CHIRPS issue 1 Odd data feature identified during Rchecks that shows poor CHIRPS rainfall estimation can occur where two geostationary satellite paths meet. This is in northeastern India. In this case a station located on the eastern swath had higher than average rainfall and seems to have produced a very enhanced above average rainfall signal in data on the western swath. CHIRP was mildly above average in that area of the western swath. The problem is that CHIRPS had an unrealistic rainfall above vs below average pattern on either side of the swath line. Certainly something funny going on with the data production, and we requested that the above average station be omitted from final CHIRPS as a patch to this problem.
CHIRPS issue 2 We found an interesting example of a station + algorithm issue that affects CHIRPS, CHPclim, and CHPclimv2. In this case there is a long term station that seems to have been included in CHPclim that corresponds to an unrealistic circular feature in the CHIRPS. The station is at the bottom of a valley in Himalayan mountains north of Nepal. It gets rainfall during the Indian monsoon, but is drier than surrounding area. The current CHPclim algorithm reacts to this situation by producing a dry pimple-shaped feature. This appears in CHIRPS. See the white dot in each panel of the figure here. This is a case of CHPclim struggling in extreme topography-- ideally the climatology would have more geographically realistic spatial variations (than a dot!). We will keep an eye out too see if this is a major problem in other areas. It is reminiscent of the 'circle' problems in Brazil CHIRPS data, which was noted in earlier Rchecks wiki entries.
Rchecks Plots New high z-score mean for entire global domain. Large anomaly maximum in Latin America. New low for South American minimum anomaly. Other than these, stats are in normal ranges. For those noted, no pressing need to investigate further before data release.
Contributors: Laura Harrison, Will Turner, Marty Landsfeld, Seth Peterson, Sari Blakeley, Pete Peterson
March 2019
Mozambique, Malawi, NE Zambia, SW Tanzania We normally have reports from two gauges along central Mozambique coast. Neither of these reported for March 2019. Could they have been damaged by Tropical Cyclone Idai? CHIRPS shows above average rainfall from central Mozambique to the north... into Malawi and near NE Zambia-SW Tanzania. Based on comparisons to TAMSAT, PERSIANN, and ARC2, the above average signal is mainly agreed upon by products. The most different product is ARC2, which shows above average rainfall as being less expansive and mainly in Mozambique. Two stations in NE Zambia and SW Tanzania indicate that CHIRPS estimates are too high in that area. The large extent above average signal is mainly coming from CHIRP.
Kenya We inspected two stations using dekadal reports from the Kenya Met Department website: One in Kitale (western Kenya) and one in Wajir (northeastern Kenya). Kitale report from GSOD did not match the KMD reports and was recommended for removal from CHIRPS. Wajir station from GSOD did match and was retained. The Wajir report plus influence from other stations in region prevented a moderate wet signal from appearing in CHIRPS in the NE Kenya to E Somalia area. This wet feature was coming from the CHIRP satellite information. Several other satellite products (TAMSATv3, PERSIANN, and ARC2) also showed a similar wet feature. We have more confidence in the station reports than the satellite information so it was good to see the blending process produced this correction.
Angola In central-west Angola there is a wet feature that produces an above average signal surrounded by an extensive below average signal. This is in direct opposition to nearby SASSCAL stations. CHIRP is the source of this signal. Interestingly, this feature is also seen in TAMSATv3 and PERISIANN CCS. It is much less pronounced in ARC2. Probably has something to do with common satellite information used in CHIRP, TAMSAT, and PERSIANN. Interesting that a similar thing is seen from the satellite products in NE Kenya (see "Kenya" note above).
South Africa We inspected two GTS stations in NE South Africa because they had same value (7.2mm) and low zscores. We compared these reports to reports from AccuWeather website. March Accuweather reports for Rustenburg total to 7.4 mm (<10% of average). So the 7.2mm there looks correct. Accuweather reports for Ermelo total to 17 mm) (<20% of average). Not identical value, but only off by 10mm. % of average is in agreement with the low zscore. Retained both GTS reports in CHIRPS.
Central America and Hispaniola Widespread below average March rainfall (zscores ~ -1) from Mid-Mexico down to northern Columbia. Rainfall has been below average for Central America region since last summer. Likely related to the borderline to moderate level El Nino conditions since then.
Problem with CHPclim in Indonesia CHPclim is the climatology used in CHIRPS. It has large influence on estimated rainfall values. In northern Indonesia (northern Paua Barat province) CHPclim has either near zero or patchy values for December-March. This produces poor quality CHIRPS values. March 2019 is a good example of this. A station is reporting 319 mm but CHIRPS values are around 15 mm.
Australia NE coast of Australia suffers from a high number of multiple counted stations. Will be interesting to see if CHIRPS data changes much in v2.1 which will not include this practice.
Rchecks Plots Latin America average tied lows for CHIRPS mean and z-score means. March 2019 region average is similar to the driest years on record: March 1988 and 1991. 2019 was drier than March 1992 and 2000. Southern Africa came close to the previous low z-score mean. March 2019 region average is similar to March 2013 and a small set of other previously very dry Marchs. Other than that, pretty normal stats.
Contributors: Laura Harrison, Seth Peterson, Marty Landsfeld, Sari Blakeley, Will Turner, Pete Peterson
February 2019
Panama CHIRPS Panama estimates will now include reports from around 23 stations, which is a major improvement from the 3 station reports that previous data relied upon. Since it was the first time including this source, we took a careful look. It looks like good data, and confirmed that northern South America and the Pacific-side of southern Central America were dry this month.
Southern Africa dryness continues Similar to previous months of the 2018-2019 season, February rainfall was below average for a large area of Southern Africa. February deficits are most expansive in western and central areas including southern Angola, Namibia, Botswana, southern Zambia, western Zimbabwe, and central-western South Africa. Parts of northern Mozambique and western Madagascar also were below average in February. In western and central areas named above and also western parts of South Africa's major maize growing area, December to February totals are 0.5 to 2.5 standard deviations below the local 1981-2018 means.
Ethiopia Inclusion of stations resulted in lower CHIRPS values than CHIRP in central and northern Ethiopia. February CHIRPS shows moderately below average rainfall in southern and central areas and moderately above average rainfall in the southwest. When February deficits, early-mid March deficits, and current forecasts for below average rainfall through end of March, plus a pessimistic forecast for April rainfall from some NMME models are considered, there is concern about a poor start and possibly of overall below average rainfall during Ethiopia's Belg season. This is the main season in southern central Ethiopia and pastoralists in that region are highly dependent on February to May rainfall performance.
Mozambique CHIRPS values may be overestimating rainfall in southern coastal Mozambique in Inhambane. Two GSOD stations reported 115mm and 103mm, but CHIRPS values are nearly 3x higher. The issue is probably due to a combination of CHIRP estimates being wetter than average there, influence of a very wet station report in southern Mozambique in Gaza that also deviates far from average, and the way this information is used to produce CHIRPS estimates.
Afghanistan CHIRPS captures extreme rainfall event that led to flooding in Herat in northwestern Afghanistan. A station reported 314mm with a z-score > 3. Given its extreme nature we examined this report carefully and compared to PERSIANN (did not agree with CHIRPS) and RFE2 (agreed with CHIRPS). The report, and CHIRPS values being above average there, are indeed correct: A news report documented extremely heavy rain, the most in over a decade. It caused flooding on Feb 12-13th that resulted in several deaths, traffic accidents, and collapsed houses. Link to article here. Flash floods have been reported in Herat province on March 18th as well...
Papua New Guinea CHIRPS captures flooding in Papua New Guinea, East New Britian province. CHIRPS totals are 300-400mm above average and 800-900mm in total. The accuracy appears solely due to CHIRP, as there are no stations in this area. Link to article is here.
Australia CHIRPS missed a major rain event in Townsville, Australia. While CHIRPS has a large number of Australia stations and these are relatively dense in this region, there is no Townsville station. Many of the neighboring stations and also CHIRP show rainfall deficits. This extreme and localized rain event led to mass farm animal causalities. Link to the report is here.
Madagascar Large (100mm+) deficits in February in northwestern, northeastern, and southeastern areas. Most of the country shows below average rainfall. Exception is central and northern tip. The signal is coming from CHIRP and station reports, with the latter being responsible for the large deficit areas.
India and Nepal PERSIANN and CHIRPs are in agreement about above average rainfall in far northern India, Jammu Kasmir, and Nepal.
Dominica (Caribbean) CHIRP had a high amount of rain across half of the island, but there was nothing in the news, and 2 stations with low totals for February largely corrected things.
U.S. Station significantly increased estimates in California and Oregon and the southern Appalacian regions.
Contributors: Laura Harrison, Seth Peterson, Marty Landsfeld, Sari Blakeley, Will Turner, Pete Peterson
January 2019
Mozambique CHIRPS values are overestimating rainfall in central western Mozambique compared to a GSOD report in central Manica province. The station reports 265 mm but nearby CHIRPS values range from 400-600 mm. CHIRPS anomalies in central MZ are very large, from > 250mm in west to > 400mm above average along the coast. There are several stations in the country that show high amounts and above average rainfall, including in Tete province and along the coast, and CHIRP also shows above average The presence of higher than average rainfall in some areas is thus not disputed, but the concern is it may be overestimated in some due to overdue influence of these stations.
Turkey/Balkan Peninsula Deadly storm slams into the Balkan Peninsula and Turkey at the end of January. Progressed northeastward into Romania and Ukraine. Captured by CHIRP and stations. A link to the news article is here.
Spain Stations capture above average rainfall in northern Spain not captured by CHIRP. Outcome is substantially higher accuracy in final product than the satellite-only product (CHIRP).
Australia Stations did a good job at correcting CHIRP to CHIRPS in Southern Australia. CHIRP showed above average rainfall, where stations showed well below, and final product accounts for that.
Costa Rica Several of us had concern is that 2 stations with reports of 0mm are helping create major large negative anomalies on the Gulf side of the country (compared to CHIRP). The z-score in affected area of Gulf are not extreme, but are large. This is not a case of duplicate station, as is sometimes seen- seqnums indicate these 0mm reports are from two different GSOD stations near to each other. With goal of reducing influence on the Gulf side we requested one of these stations not be included this month.
Caribbean Noted during the checks was that in some islands with a climatologically dry side/wet side, an above average report on the drier side resulted in the wet side being estimated as having a very large anomaly. Consistent with how the algorithm operates (% of normal is interpolated) but it produced an unrealistic outcome here.
Z-scores reminder A reminder to be careful when interpreting z-scores (standardized anomalies) in CHIRPS data in low rainfall regions/periods. These fields are made available to users via the ftp site. In reality checks, z-scores are one field we look to when comparing station values to CHIRPS estimates. Example here is in Myanmar-- There is generally very little rain there at this time of year. Several stations reported 0mm, while CHIRP showed around 4 mm. Yet, by looking at z-scores in the region, if you weren’t careful to look at raw data, the stations overlaid on CHIRPS would look bizarre – exceptionally dry z-score value stations in the midst of an exceptionally wet z-score value CHIRPS field.
Reality Checks overview 21 stations were identified for removal from the final CHIRPS. 9 of these were in Brazil, due in part to the over influence attributed to them by the current CHIRPS processes step that allows for a single station to be counted multiple times. Not all these cases are grounds for station removal, only when they have a noticed and substantial impact on regional anomaly patterns. This problem is due to be fixed in version 2.1.
Contributors: Laura Harrison, Will Turner, Emily Williams, Marty Landsfeld, Seth Peterson, Sari Blakeley, Pete Peterson
December 2018
Missing GCHN-v2 stations US government shutdown may have impacted access to GHCN-v2 stations, which are considered high quality and an important source in CHIRPS. CHIRPS usually incorporates ~1,000 GCHN-v2 reports globally. Station count (all sources) used for December 2018 CHIRPS data is currently ~12,000. When GHCN-v2 become available, December 2018 CHIRPS data will be reprocessed.
Eastern Horn of Africa NOAA ARC2 and CHIRPS data have a different interpretation of December rainfall anomalies in eastern Kenya and southern Somalia. Differences can be seen in the figure here. CHIRPS, which includes ~16 SWALIM stations in southern Somalia, shows southeastern Somalia as above average. ARC2, which has no stations in Somalia, shows a mix of below average and above average here and in eastern Kenya. In eastern Kenya CHIRPS above average. This is primarily coming from CHIRP signal and stations in central Kenya and southern Somalia. The positive anomalies in the eastern Horn in CHIRPS are consistent with the above average rainfall estimated across equatorial East Africa in CHIRPS.
Switzerland and Austria Stations in CHIRPS capture storm that hit Switzerland and Austria during the holidays. A link to that article is here.
Argentina Rchecks has higher precipitation than CHIRP in northern Argentina. A website on commodity crops confirms December was wet. Link to article here.
Southern Africa CHIRPS shows December 2018 rainfall as below average for much of Southern Africa. This is consistent with ongoing monitoring and reports in the region. December rainfall was near or above average in some smaller areas of eastern Botswana and northeastern South Africa. Evaluation of difference between CHIRPS Prelim and Final for Dec 2018: As indicated by comparison of anomaly maps: 1) Final is substantially drier in SW Zambia. 4 stations in this zone; 1 was removed for suspected false zero. 2) Final less dry than Prelim in south-central Angola. 3) Zimbabwe Final and Prelim estimates are similar, except that far western Zimbabwe is drier. 4) Areas in NE South Africa with above average in Prelim are still above average but closer to average now. The comparison can be seen here [Figure link coming soon].
Central America and Hispanola Widespread dryness for the month on both the islands and most of C. Amer. Based on time series plots for the region, December 2018 CHIRPS mean and average z-score was a new low, compared to 1981-2018 data. Evaluation of difference between CHIRPS Prelim and Final for Dec 2018: No big changes in regional anomaly pattern. Both show below average in western region of Central America. CHIRPS is slightly drier than Prelim in Guatemala and slightly different dry anomaly pattern in Nicaragua. In far southeastern Mexico CHIRPS has a more expansive above average area.
West Africa Evaluation of difference between CHIRPS Prelim and Final for Dec 2018. Prelim showed below average near coast; Final shows less dryness and a more mixed pattern across this region.
United States Stations used in CHIRPS significantly increased estimates in the southeastern US. In the western US, a comparison of CHIRPS and Persiann estimates identified there are dramatic differences between these data sets for December 2018 rainfall.
Contributors: Laura Harrison, Marty Landsfeld, Will Turner, Seth Peterson, Sari Blakeley, Pete Peterson
November 2018
Southern Africa The inclusion of station reports into CHIRPS resulted in a (more) negative assessment of November 2018 rainfall across much of southern Africa (compared to CHIRP and CHIRPS Preliminary). See comparison here. CHIRP and CHIRPS Preliminary for November 2018 were already showing deficits across these areas. Numerous stations (~100) from multiple sources (SASSCAL, GTS, GHCN-v2 monthly) indicate substantial deficits in November 2018 for Botswana, South Africa, Lesotho, Namibia, Zambia, Angola, and in southern Madagascar, southern Mozambique, and southern Tanzania. As usual Zimbabwe does not have stations reporting to CHIRPS. A result is that CHIRPS in Zimbabwe is influenced by neighboring country stations and thus CHIRPS deficits are larger than what is shown in CHIRP and CHIRPS Prelim. It is notable that the difference between the southern Africa CHIRPS and CHIRP means is larger (more negative) than for any previous November in CHIRPS record. This also speaks to the value of the SASSCAL contributions to CHIRPS.
Missing GSOD stations For a ~5 day period in late November, thousands of GSOD station reports were not available in the main GSOD data repository. This resulted in only a fraction of the usual reports being considered for inclusion into CHIRPS. The reason being is that with this many missing days, the criteria for >27 days of reports to make a monthly total was not met at thousands of locations. In CHIRPS processing, if other sources e.g. GTS were available, those were used to fill in for missing GSOD monthly totals. This filling-in occurred in many regions. Stations counts in Portugal, France, and Spain were notably lower than normal because of the missing GSOD reports. Portugal normally has ~14 GSOD reports; this month Portugal had 0 GSOD reports and only 1 station report guiding CHIRPS.
Ethiopia The value of Ethiopia NMA's sharing of 50+ stations was clearly shown in November 2018 CHIRPS. CHIRP and CHIRPS Prelim, in central and northern Ethiopia, showed a mixed signal of above and below normal rainfall. Inclusion of numerous NMA stations into CHIRPS changed this signal to show a more widespread pattern of above average rainfall, and with larger positive anomalies.
Central America The stations that were included in CHIRPS show a similar story as did CHIRPS Prelim—- a below average November. See comparison here. It would be ideal to have more stations reporting to CHIRPS in this region, but there are ~30 stations in total for the region from south of Mexico to Caribbean to Panama. For monitoring and early warning it is helpful that these stations in CHIRPS were in general agreement with the low latency CHIRPS Prelim.
Somalia Three station reports were given extra scrutiny due to having reported low values (compared to CHIRPS background estimates). The 2018 Deyr rains have been given careful attention in the FEWS NET community, given deficits being previously reported and estimated. A fruitful Reality Check was to compare daily reports at these stations to daily rainfall time series from NOAA's ARC2 rainfall data. ARC2 does not have stations in Somalia-- we used it as indication of timing and magnitude of potential storms near these scrutinized stations. The comparison yielded support for two of these reports (25mm in Baardheere and 0mm in Mogadishu). The third (0mm) was considered potential false zero and removed from CHIRPS. There are typically ~9 SWALIM stations contributing to CHIRPS estimates in southern Somalia and 30+ SWALIM stations in northern Somalia- making a higher station count in CHIRPS than any other global product.
South America There is a general trend of higher precipitation in the south of the equator ITCZ in CHIRP but the addition of the stations raises the precipitation values a little, bringing them more in line with those from CMORPH. This feature stretches from Peru through western Brazil, northern Bolivia, Paraguay, and a portion of northern Argentina.
California Two erroneous stations identified (Bode and Redwood City). These were removed from CHIRPS. Interesting that CHIRP shows average to below average in central and northern California, and inclusion of stations corrected this to an above average signal.
Sierra Leone Anomaly sign flips in CHIRP vs. CHIRPS, probably due to influence from a wet station in Guinea
India Stations and CHIRPS Prelim both show below average for most of India (~50 stations). Zscores are -0.5 to -1.5.
Japan Below average November rainfall, based on Prelim and stations (~50 stations). Anomalies range from ~-20mm up to large deficits of -100—150mm along the west coast.
Australia Northeastern and eastern coast areas were below average according to Prelim and stations. Through central Australia the stations substantially increased estimated rainfall compared to Prelim, changing that area from average to below average to average to above average.
China In southeast China stations led to a change in anomaly sign. Prelim was showing a mix of below and above average; stations (~30) being included changed CHIRPS to above average in this region.
Indonesia/Papua New Guinea Signal in CHIRPS is different than CHIRPS Prelim, despite there being no station reports on this island. Thus it is due to influence of stations in other areas. The change is that the drier than normal southern areas appear drier in CHIRPS Final, and the wetter than normal northern areas are closer to average or below average in a few locations.
Contributors: Laura Harrison, Marty Landsfeld, Will Turner, Seth Peterson
October 2018
East Africa Given high level of concern about below normal rainfall in the eastern Horn's OND season thus far, and importance of CHIRPS products in monitoring this event, we took care to notice the data in this region. Here are some features: There is a spot in southern Somalia where ARC2 registers high rain total in a small area, but CHIRPS does not. Compared to ARC2 rainfall estimates, CHIRPS shows higher October 2018 rainfall values in the eastern Horn and has a more realistic looking spatial pattern. A previous analysis comparing October 2018 CHIRPS Prelim to SWALIM stations (which are used in CHIRPS Final) showed that reports matched values well in Bay region, where there were concerns about cropping. Closer to Kenya border we have less confidence in CHIRPS values as some areas may have had localized rainfall. In dry areas we have seen CHIRPS struggle with such cases in the past. One of the SWALIM stations in southwestern Somalia reported 0mm for October. ARC2 daily indicated rain in several days, totaling ~20mm for the month, so we took a cautionary route-- we assumed this SWALIM report was a 'false zero' and recommended it not be included in CHIRPS Final. We appreciate FAO SWALIM providing reports early this month-- these were helpful for assessing conditions in the region and providing early warning.
Spain, France, Italy Stations capture heavy storms throughout northern Spain, southern France, and Italy, which left at least 11 dead in Italy and thousands without electricity. The severity of these storms were not originally captured by CHIRP. News reports about Italy storms here and here.
India According to news reports, October 2018 was the driest October in India since 1976. CHIRPS also shows October as being drier than normal for large area of the country-- making it the 2nd month in a row with widespread deficits and 3rd month with deficits in some areas. Sugar cane yield is projected to decrease, and price to increase. This dry spell was captured by CHIRP and supported by station data.
Sri Lanka CHIRP captures devastating flooding in Sri Lanka from early October that left 9 dead and 5,000 displaced.
United States Station values really contributed to CHIRPS in the southern Applachians as well as Texas where flooding was an issue in October.
Western United States CHIRPS anomalies show the continuing drought of the west coast states
Central America and Haiti Below average October rainfall in areas that have experienced rainfall deficits for several months: parts of Guatemala, Honduras, El Salvador, and Haiti. High rain totals and above average signal along Pacific coast, Nicaragua to Costa Rica. CMORPH also shows this. Probably associated with hurricane activity.
South Korea and Japan Really interesting anomaly pattern. South Korea showing anomalous high rainfall across country while Japan shows opposite. Signals are backed by numerous stations.
Southern Africa October 2018 is a new low in terms of how much rainfall occurred in the wettest location of southern Africa (lowest CHIRPS Maximum of 1981-2018). Below average rainfall was seen across much of the region. CHIRPS mean for this region indicates October 2018 is among one of the driest Octobers of 1981-2018.
Kenya During Rchecks we looked into a potentially odd pattern in western Kenya. There were reports of highly above average rain close to reports of below average rain. Compared to the October 2018 ARC2 anomaly map. It shows same pattern.
West Africa CHIRPS shows above normal October rain in Burkina Faso, Niger, and Nigeria. The signal is coming from some numerous station reports and with some agreement from CHIRP. eMODIS NDVI shows higher than normal vegetation productivity in early November in that region. Potentially an outcome of above normal October rains.
Contributors: Laura Harrison, Will Turner, Marty Landsfeld, Sari Blakeley, Seth Peterson
September 2018
Ethiopia CHIRPS Prelim (and CHIRP) were wetter than CHIRPS Final. This is due to influence of average to below average station reports in some areas of NW and much of central Ethiopia that were included in final version of CHIRPS.
Philippines CHIRPS shows very high rainfall in northern Philippines where Typhoon Mangkhut passed through. Heavy rainfall from Mangkhut led to a mudslide that killed at least 66 people. At monthly time scale, CHIRP only picked up on moderate magnitude above normal rainfall, but reports from stations in that area produced large (wetter) values in CHIRPS. An extreme station report is 1220mm for the month; others report 300-500 mm.
Japan CHIRPS shows high amounts of rainfall associated with Typhoon Jebi. This is coming from both CHIRP and station reports.
Cayman Islands There is a co-registration issue with small islands, we can see that the shape of the island in vector format is different from the area that is modeled in CHIRP/CHIRPS. In this month this caused an issue because the station value was compared against a (low) ocean rainfall value rather than a (high) land rainfall value, which caused the already high land value (Tropical Storm Isaac) to become even higher.
Eastern Caribbean Kind of odd, regarding influence of Tropical Storm Kirk on the data: In CHIRP, Barbados has lower rainfall, but the island chain E of it is high rain. From the stations, Barbados got hammered and the island chain was neutral (though stations not positioned the best to capture Kirk effects). In CHIRPS, even with the high station value Barbados rainfall didn't get corrected very much. So this is a different small island phenomenon than for the Caymans. Seems like interpolating from 5 station values is not ideal when rainfall from tropical storms can be so localized.
Costa Rica and Nicaragua CHIRP is quite wet in central, western Costa Rica, and western Nicaragua. CHIRPS (with stations) is quite a bit drier than CHIRP. CMORPH is drier than CHIRP as well.
'Northern India In far northern India, CHIRP and stations showed anomalous high rainfall in Himachal Pradesh Mountains. Station reports (but not CHIRP) showed a wet signal also to the south, and this was carried through into CHIRPS.
India and SE Asia CHIRP and stations show below average rainfall in much of India and many arts of SE Asia. Interesting feature, which we are not sure if is accurate, is an area of above average rainfall in NE India/Bhutan area. Seems to be mainly coming from CHIRP. PERSIAN-CCS also shows below average across this region.
Contributors: Laura Harrison, Will Turner, Seth Peterson, Marty Landsfeld
August 2018
India Northern India recieved higher than average rainfall in August 2018, based on reports of amounts 350mm to 700 mm above normal at several stations in the lower elevation areas of the Himalayas. The wet signal is also shown in PERSIANN-CCS data and CHIRP.
Hawaii Wow! Two stations near Hilo reported 73 and 48 inches of rain in August. That is 4-6 FEET of rain. CHIRPS Prelim did a decent job of showing spatial pattern of enhanced rainfall on that part of the island but the added stations in CHIRPS Final really upped the magnitude. Tropical Storm Lane was responsible for much of the monthly total and produced record breaking rainfall for August. Read the story here
Haiti CHIRPS shows below average August rainfall particularly in southern areas. This signal is coming from CHIRP and possibly also also influence of a substantially below normal (z-score ~2.6) report in southwest DR. Three other stations in DR show below normal (but closer to normal). Haiti has no reporting stations. CHIRPS final similar to CHIRPS Prelim for August 2018.
Brazil Near the coastline south of Salvador, Brazil shows a large increase in rainfall from CHIRP to CHIRPS, going from ~200 to 400mm. However there aren't any visible stations causing this, the only visible stations (in EWX version of CHIRPS Rchecks) have neutral to slightly negative anomalies. Not sure what is going on here.
Liberia There is a spot of low rainfall in central Liberia that stands out as "off." This is present in August CHPclim, teh CHIRPS climatology, and likely the cause.
Sudan No stations reporting in Sudan. Last month there were 14. Previous Rchecks month/years shows the number of stations varies a lot from month to month.
More about RChecks 23 cases were carefully examined during Rchecks, and this led to 10 stations being removed from global August 2018 CHIRPS final data.
Contributors: Laura Harrison, Marty Landsfeld, Sari Blakeley, Seth Peterson
July 2018
Ethiopia Ethiopia CHIRPS data based on > 30 stations. These generally confirm the pattern of below average rainfall in southern, central and northern Ethiopia as shown in CHIRP and CHIRPS Prelim. CHIRPS and stations show above average rainfall in two localized areas: a small zone in central Oromia and at border of Amhara and Afar. The drier than normal July signal is more severe in CHIRPS than CHIRP and Prelim in some areas.
Greece CHIRPS data, due to incorporation of stations, captures series of flash floods towards the end of July, following the deadly wildfires in Athens, Greece.
West Africa coast An area along coast that usually has a station (GTS or GSOD) is not reporting. This results in the countries of Guinea, Sierra Leone, and Liberia having no station reports. End result is that CHIRPS data is mimicking the CHIRP signal and is somewhat influenced by stations outside the area, which lowers confidence in CHIRPS estimates of below average in that area. However, CHIRPS is not the only data showing this dry signal. TAMSAT and PERSIANN data also show below average here. This is a curious area because recent months have also registered as below average in CHIRPS but ARC2 data has been showing the opposite in all except May. July 2018 anomalies from multiple data sets shown here.
Mexico and Central America According to CHIRPS July 2018 rainfall was below average for a large region including central and southern Mexico and through Central America to western Costa Rica. For this region: In comparison to July 2015, the summer of drought leading up to the major 2015/16 El Nino, this July (2018) had lower rainfall in many areas and the spatial extent of the below average precipitation signal appears larger, in part due to much of Mexico being affected in 2018. Comparison of July 2018 (left) to July 2015 (right) CHIRPS here.
Mozambique Multiple stations in Mozambique and southern Malawi report higher than average rainfall in July 2018. To some extent this is supported by ARC2 data, which shows above average rainfall at spots in these areas. The spottiness of ARC2 here is likely problematic for users of that data. In comparison the signal in CHIRPS data is coming from >10 stations of different sources and shows a more geographically expected precipitation pattern. July 2018 data for CHIRPS and ARC2 can be seen here.
Uganda The drier than normal July signal in northern Uganda looks less severe in CHIRPS than CHIRPS Prelim. There are two stations in vicinity (NW Kenya and central Uganda) which both show standardized anomalies of -1.7 and -0.5, respectively). CHIRPS shows standardized anomalies of -0.5 to ~-2 in some areas. Reason for more severe signal in Prelim may be CHIRP and preliminary GTS stations.
Senegal Multiple data sets, including CHIRPS, show below average July 2018 rainfall in western Senegal. July anomalies can be seen here. This area has been highlighted in FEWS NET weekly and seasonal monitoring as an area of concern for poor cropping conditions and potential food security issues.
Switzerland Stations capture continued drought in eastern Switzerland. 'Driest summer for more than a decade'
Serbia Stations capture intense storms and flooding throughout Serbia for the month of July.
Contributors: Laura Harrison, Will Turner, Sari Blakeley, Seth Peterson
June 2018
Haiti and Dominican Republic A station in southern coast of DR was removed from CHIRPS because it seem to have adverse influence in Haiti, where a dry signal was shown by CHIRPS, other stations, and other rainfall and vegetation products. This station reports highly above average rainfall (total 221mm, anom ~130mm). Upon comparison to CMORPH it might be from some on-land influence of an offshore area of above average rainfall (related to storm Beryl?). The value itself is thus believable but the influence seems to be such that precipitation in Haiti is markedly changed from CHIRP anomaly, which shows below average across Hispanola and agrees with CMORPH June anomaly. Drought conditions have been recently reported in Haiti
Kenya CHIRPS in western Kenya show large positive anomalies. While stations to the northwest and southeast do show above average precipitation, there are no stations within the area that has very large positive anomalies. The signal is coming from CHIRP and probably also influence from the stations outside the area, plus the area's higher climatology, as described below in the Columbia and Ecuador entry.
Southern Africa Coastal areas of Southern Africa shows a weak below average precipitation pattern that comes from station reports. These are generally enhancing the signal shown by CHIRP. Interesting that CHIRP anomalies offshore are stronger below average than on land. Together the stations and CHIRP indicate a region-wide drier than average signal.
Columbia and Ecuador Contribution of stations into CHIRPS increases the magnitude of the negative anomaly shown by CHIRP in coastal Ecuador and Columbia. The influence seems to be coming from inland stations that have large negative standardized anomalies. There are no stations on the coast here, and in fact the nearest coastal station, at the northern edge of the coastal area, has a positive anomaly. This case might be a result of a feature of CHIRPS algorithm that applies closest 5 stations' percent of normals to the local pixel's climatology to estimate local precipitation. The climatology in this area is relatively high, which means that a drier than normal signal from elsewhere would be amplified.
India CHIRP shows above average and high rainfall totals along western coast of peninsula. 8 stations along this zone also report very high amounts. The station totals tend to be higher than CHIRP totals, but not in all cases. Result is CHIRPS totals of 750mm-1500mm in this zone, maybe some pixels are even higher than 1500mm.
Mariana Islands CHIRPS estimate of 3270mm here is an all time high CHIRPS value. This is the same island chain that produces extremely high z-score values (10^11). This needs to be investigated and resolved in CHIRPS 3.0.
Afghanistan RFE2 and CHIRPS data in agreement about localized higher than normal precipitation in southeast Afghanistan.
Contributors: Laura Harrison, Marty Landsfeld, Lilian Yang
May 2018
Continuation of wet conditions in some of East Africa CHIRPS May 2018 data shows positive rainfall anomalies in interior areas (from western Kenya north to South Sudan and western central Ethiopia) and eastern areas (coastal Tanzania and Kenya, southern Somalia, and northwest Somalia). This is consistent with flooding and landslide-related disasters, large numbers of displaced people, and many fatalities in some of these areas. In Kenya the number of fatalities is at least 186 people during this extremely wet March to May season.
China (south east) Severe drought continues in south east China (including Hong Kong). CHIRPS May 2018 data shows large magnitude deficits. Subtropical Hong Kong gets an average of 2,400mm of rain a year, about a tenth of which comes in May. But since January this year, less than 170mm has fallen on the city, under half the normal average for this period. Low rainfall, coupled with high heat has begun to deplete reservoirs, which farmers rely on for irrigation. Some crop failure and wilting has been reported.
Guinea and Sierra Leone Substantially below avg. rainfall (~100mm deficits) indicates multiple week delay to growing season rainfall. NDVI anomaly maps had indicated vegetation impacts. More extreme in CHIRPS than CHIRP. Careful though. Biggest signal is in areas without stations but with higher climatology (e.g. central Guinea); surrounding stations are leading to increased deficits in some areas. However, CHIRP does show deficits of ~80mm.
India (southwest coast) CHIRP and stations both capture early monsoon arrival on the southwest coast of India. CHIRP fails to identify deadly storms in northern India (Uttar Pradesh), though they are captured by several stations
Armenia High rainfall amount in CHIRPS confirmed by flooding report
Bangladesh CHIRP and stations both capture devastating floods in Bangladesh
Thailand Stations capture flooding in northern Thailand (Chiang Rai) that caused a fatality
Tasmania CHIRP and stations fail to identify extreme rain events in southeast Tasmania. Rain and thunderstorms brought exceptionally high rainfall to the southeast of Tasmania, in particular to Hobart and the nearby Wellington Range where almost all sites reported their highest May daily rainfall on record. The daily totals of 236.2 mm at kunanyi (Mount Wellington Pinnacle) and 226.4 mm at Leslie Vale are now ranked two and three in the list of highest May daily rainfalls ever recorded in Tasmania.
Ethiopia May CHIRPS shows below avg rainfall through northern and central regions. The signal comes from NMA station reports and CHIRP. The stations enhance the deficits compared to CHIRP but show similar pattern. Rchecks identified that multiple stations (from SWALIM and NMA)indicated dryness in eastern area and that instead of reflecting this, the first version of CHIRPS was showing an above average signal. Further analysis indicated that a single highly anomalous wet station reporting ~300mm from a mountain top in the area, along Somalia border, may have been positively swaying the regional signal. Comparisons were done to dekadal rain totals and anomaly maps from Ethiopia's MapRoom- these did not show such high rainfall. The station was omitted from CHIRPS final based on concern it was casting too much weight. Tropical Cyclone Sagar did pass across parts of northern Somalia, and other remaining anomalous wet stations still show its impact.
Somalia Overall CHIRPS appears to have good estimates for Somalia. Areas of below average rainfall in the eastern Horn (from stations) are showing up in CHIRPS, as are above average rainfall estimates in southern and northern areas. CHIRP is consistent in some of these areas but stations are having clear role. Note that several stations report below average rainfall in southern Somalia and CHIRPS may be overestimating in these areas due to wetter stations nearby. Tropical Cyclone Sagar in early May had some role in heavy rainfall in northern Somalia.
Mozambique There is a single station in coastal central MZ creating a below avg. signal that propagates towards interior. CHIRP does not indicate this. We compared to ARC2 to find that ARC's May 2018 anomalies and May climatology pattern is odd looking (spotty) in southern Africa. There is a large difference between CHIRPS and ARC2 May climatology in this central coast area in particular-- CHPclim shows the area receives from 25-80 mm on average. Hence why the CHIRPS anomaly propagate through this area. The station report was deemed as potentially being accurate-- ARC2 also shows a below average spot there.
Niger There is an incorrect blob of rainfall in northern Niger data, which is usual for May CHIRPS. The feature comes from a wet feature in the climatology (CHPclim) being perturbed by estimated percent of normal to produce CHIRPS estimates. Sometimes remote stations have enough influence to perturb it towards substantial rainfall values, which is what may explain this month's estimates of 25-50mm (+10-25mm anomalies). CHIRP anomalies are close to zero.
Ghana In northern Ghana a positive anomaly at a rain gauge seems responsible for an area of enhanced positive anomaly to its south. Little influence from other rain gauges for explaining this rainfall event, but rather a likely influence of it working with the higher climatology to produce a larger anomaly in that area.
Republic of Congo and DRC The rain gauges are on either side of the border between Republic of Congo and DRC, but they have about 200 mm of rainfall difference. There might be an influence of topography.
Brasil/Argentina/Uruguay There are 3 separate stations in the Iguazu falls area that all show low rainfall. The other stations in the general vicinity and CMORPH all show very high rainfall.
United States In eastern US, CHIRP did not pick up the very heavy rain amounts in the Appalachain mtns but stations corrected that in the CHIRPS product. CHIRPS overestimated rainfall in the Pacific NW but many low value station readings corrected this in the CHIRPS product.
CHIRPS algorithm issues May 2018 data in Kenya has a clear example of why it is problematic to make estimates based on a deviation from monthly climatology when the climatology is near zero. November or October 2017 data had same problem in northwestern Kenya. In May 2018 data two stations, in northern and eastern Kenya (179mm and 48mm), report substantial and highly anomalous rainfall; its is reasonable to think this may have occurred through the climatologically dry corridor in northern to eastern Kenya. CHIRPS estimates however are near zero throughout the whole area, including at the 48mm station location. This is because CHPclim is near zero. CHIRP shows average to below average in the area so there is an odd effect where the stations exhibit highly anomalous wet rainfall (zscores >3) but CHIRPS indicates average to below. Being highly anomalous, it is possible that these stations are influencing estimates elsewhere but it is difficult to detangle their influence from other wet stations across the region.
Other CHIRPS info There were no statistical outliers to report this month. In southern Tanzania, a blocky pattern in anomalies is coming from CHIRP.
Contributors: Laura Harrison, Will Turner, Sari Blakeley, Marty Landsfeld, Seth Peterson
April 2018
East Africa Consistent with reports of much higher than normal rainfall, which led to a number of disasters and impacts in east Africa, CHIRPS shows highly above average rainfall in April 2018. Extreme rains (>100 mm in 24 hrs) and flash flooding were reported on several days in cities across the country, incl. Marsabit (4/13-4/14), Garissa (4/16-4/17), and Kitui (4/23-4/24). Between 4/9-4/26 the Red Cross estimates 211,000 people were evacuated and 50 people were killed by damages Floodlist. Final April 2018 CHIRPS data is based on a relatively high number of stations in Kenya- more than normal- and CHIRPS estimates and stations are in general agreement, albeit in some areas CHIRPS is probably overestimating to some degree (see other entries below). CHIRPS data shows April rainfall was >100 mm above average in many areas of southern Ethiopia, southern Somalia, Kenya, Uganda, and Tanzania. Anomalies ~ 300mm are shown in some of the high elevation zones. The spatial pattern and size of anomalies are overall similar to those shown in ARC2 data.
Somalia SWALIM and Ethiopia NMA contributions to CHIRPS: SWALIM and Ethiopia NMS stations were highly influential for CHIRPS- reports in some areas of southern Somalia, southern Ethiopia, and eastern Kenya were ~100mm lower than CHIRP estimates. Result is that while CHIRPS shows above average precip across region, some of these areas anaomlies are weaker than otherwise would be based on satellite estimate (e.g. ~54 mm vs 180 mm)
China Stations were important for correcting CHIRP estimates in central-northern china and southeastern china. ~60 stations reported contrasting anomalies to CHIRP, with above average rainfall in central-northern china and below average rainfall in southeastern china. CHIRP showed below average across most of southern china. Could not find news reports to validate, but number of stations in agreement give support for CHIRPS accuracy.
Southeast Asia Stations were important for correcting CHIRP to above average rainfall in Thailand and northern area of Laos. ~25 stations show general agreement about this.
CHIRPS improvements During Rchecks on the first version of CHIRPS Final, it was identified that were substantially fewer stations than usual in east Africa and that CHIRP was overestimating rainfall in some areas. The combination of these factors gave concern that it might be reducing accuracy of CHIRPS data this month. Rcheckers and Pete Peterson, data curator, worked together to identify why so few stations were getting through (explained below). After these efforts, which resulted in a more stations being included and other positive outcomes, the final CHIRPS final is regarded with confidence. Including of a higher number of stations helped correct CHIRP overestimation in some areas e.g. coastal Kenya now shows ~150mm as opposed to ~300mm, which is more in line with stations, and Kilimanjaro shows values closer to ICPAC-blended data from bulletins. Positive outcomes of these efforts are better station coverage in east Africa in April 2018, identification of a screening step that needs to be evaluated more closely, and some of the added stations were in support of CHIRPS estimates, which is always great see. The reason for the initial lack of stations was identified- it was a data quality screening step (false-zero screening) that reduced 26 available GTS stations to 2. GSOD were reduced also such that Kenya only had 4 stations in CHIRPS. The hypothesis is that two factors in processing reduced number of days with reports to below the required threshold for them to be used for monthly totals. One factor was that there were no GTS reports on the GTS ftp site for one day (4/29), which counted against the monthly tally for the stations. Two, there may have been days where reports of 0mm were incorrectly identified as false, potentially b/c of extremely high CHIRP values. To get the stations back in Pete omitted the false zero screening step in east Africa countries. Screening steps are one of the processing features that will be revisited in the planned CHIRPS v3.0. In the meantime, an extra check may be introduced to processing prevent this type of problem.
Contributors: Laura Harrison, Will Turner, Marty Landsfeld
March 2018
East Africa: CHIRPS, CHIRP, and station reports show a convergent story-- anomalous wet conditions occurred in March across the region, with largest anomalies (>100 mm) in Uganda, Kenya, Burundi, Rwanda, and Tanzania. This led to major flooding problems in Uganda, Burundi, and Kenya.
Mediterranean: Stations included in CHIRPS reported the anomalous high rainfall that led to major flooding in northern Algeria, Gibraltar, Portugal and Spain from Storm Emma and Storm Felix, which was not previously represented in CHIRP.
Balkans: Stations also showed the high rainfall associated with Storm Emma that caused flooding in the Balkans. Contributors: Marty Landsfeld, Will Turner, Laura Harrison
Madagascar: CHIRPS, thanks to CHIRP and a couple stations) shows the heavy above average rainfall in northern Madagascar associated with Tropical Cyclone Eliakim that caused flooding and damages.
South America data Return of CHIRP data in southern Chile/Argentina. Satellite input had stopped contributing several years ago.
Contributors: Laura Harrison, Marty Landsfeld, Will Turner
February 2018
Southern Africa: Reversal of rainfall signal between January and February 2018 for a large region. This was noted during weekly FEWS NET Hazards monitoring, and CHIRPS data confirms. After an extremely dry January across large parts of southern Africa south of 10 S, extreme wet conditions were seen in February in Zambia, Zimbabwe, central-south Mozambique, northeast Botswana, and northern South Africa. As noted below, there were no stations reporting to CHIRPS in Zambia and Zimbabwe (fewer than normal were in Moz too). This wet signal is coming from several wet stations and CHIRP. Is also corroborated by other products (PERSIANNE-CCS, ARC2).
Tanzania: According to CHIRPS, a drier than normal February prevailed across Tanzania, with large negative anomalies (< -100 mm) in southern Morogoro province (also in northern Mozambique). This is consistent with CHIRP, ARC2, and PERSIANNE. After noticing that there was a station in southern coastal TZ that was being duplicated in CHIRPS, Rcheckers recommended removal of this station to prevent the duplication from artificially enhancing the dry signal (the duplication is a known problem in current processing method and is schedule to be fixed in next version). This station was not removed during processing of CHIRPS-final, so unfortunately it may be having a negative impact on the CHIRPS data by artificially enhancing dryness in the locale of Mtwara (TZ) and northeast Cabo Delgado (MZ).
Kenya: Station in east central Kenya removed. This station, at 52mm, was wetter than would be expected, given that a station next to it had ~5mm. To assess, we looked to IGAD/ICPAC dekadal bulletins for February. For their data they improve CHIRP data by blending it with many stations provided by some GHA countries. IGAD dekadal bulletins reported all three dekads had < 5mm each in that area. Thus the GHCN-v2 station was deemed inaccurate and removed. Note that this station does not consistently report and when it does it usually shows substantially higher rainfall than its GTS neighbor. The IGAD/ICPAC website was added to the 'Helpful Links' list so that all Rcheckers can quickly access the website for future checks.
Zimbabwe: No stations reporting again. Like in January 2018, no station reports went into CHIRPS. GTS stations did share reports for some stations but only for ~18 days. This was not enough to meet the requirement to go into CHIRPS (27 days) to make a monthly total.
Zambia: No SASSCAL stations reporting. This was concerning, as we typically receive ~10 stations and incorporate these into CHIRPS. According to the SASSCAL website (http://www.sasscalobservationnet.org/), these stations have not reported to them in around a month.
Artifacts in CHIRPS: Arcs and blockiness are visible in data, anom, z-scores in south-central to south-eastern areas of Africa. This was seen during Rchecks; Rcheckers notified CHIRPS data curator. Same artifacts came though in final version of product too.
Example of Rchecks: Here is an example of the type of process that occurs during CHIRPS Reality Checks. Compared to CHIRP, several stations created rainfall in southern Burkina Faso and Ghana. CHIRPS shows it as wetter than average for Feb 2018. One of the stations (GSOD, 277149) is especially high at 93 mm. This station we have not seen in CHIRPS in past year... so is suspicious. However, ARC2 also shows a signal of above normal rainfall, so suggest to not remove any of these stations.
South America: CHIRPS shows an anomalous pattern of dry-wet-dry for the areas around southern Columbia (dry), northern-central Brazil (wet), and southern Brazil/Uruguay/Argentina (dry). Some of the anomalous dryness was due to enhancement of CHIRP signal by stations. Each of these regions had >25 stations with convergent reports, expect for southern columia which had the extreme dry coming from ~15 stations. Persianne data also shows this pattern of anomalous dry-wet-dry. INMET brazil site also shows high > 250mm rainfall in same area as CHIRPS (http://www.inmet.gov.br/portal/index.php?r=tempo2/mapasPrecipitacao). Overall, the pattern and station reports appear robust.
Western Australia: As a result of Cyclone Kelvin, CHIRPS station data was much higher than CHIRP estimates, especially across the central and southern regions of Western Australia.
Contributors: Laura Harrison, Libby White, Marty Landsfeld
January 2018
Overview: There are no wiki entries this month. However, a full Rchecks was done on the January 2018 data. 14 stations were identified as problem data. All 14 recommendations were taken-- these stations were removed from the final version of January CHIRPS. For more information, we point you to the January 2018 section of the CHIRPSv2 station watchlist, which has comments and group discussions from the Rchecks.
Contributors: Laura Harrison, Sari Blakeley, Will Turner, Marty Landsfeld
December 2017
Southern Africa dryness in December 2017: As the dryness is shown across large area of southern Africa, comparison of z-scores from CHIRP vs CHIRPS is helpful for gauging extremity of situation. In CHIRP, Dec rainfall was around -0.5 standard deviation in parts of Botswana, all of Zimbabwe, southern Zambia, central and southern Mozambique, northern and southern South Africa, and parts of Namibia; in CHIRPS the pattern is more defined spatially, with December dryness being more focused and intense (z of -1 to -2) in parts of the area covering central/southern Botswana, northern SA, to central/eastern Zimbabwe and western areas of Mozambique. Also parts of Namibia and southern South Africa. Anomalies show below average Dec rainfall across most areas of southern Africa south of 15S. Exception is in an area in eastern South Africa. Something to also note is that there is quite good station coverage in Namibia (~40) and South Africa (~50)
East Africa dryness in December 2017: Below average Dec rainfall in Uganda, Kenya, northern Tanzania, much of Ethiopia and Somalia according to both CHIRP and from stations (CHIRPS).
Ethiopia: A note on the relatively large number of stations that report to CHIRPS in Ethiopia, which is typically undersampled in global precipitation data sets. There are consistently around 30 stations in Ethiopia in Dec (and November, October), thanks to contributions from Ethiopia NMA. Really nice to see this amount of measured rainfall coming into CHIRPS. Note that these are all 0mm in December, as expected based on climatology, but that in previous months there was more variability.
Southern Mozambique: December CHIRPS shows below average rainfall in central and southern MZ, with average anomalies aorund 75mm. This follows a below average November in southern MZ.
Central Kenya: Two instances of station duplication resulted in removal of the stations. One was near Mt. Kenya (triple counted) and one was to south (2x counted). The latter was removed because it had a moderate-large z-score (~ -2.6) and we did not want this to have more influence on regional CHIRPS than other stations, which also showed below average December 2017 rainfall but to a lessor magnitude.
Zimbabwe: 0 stations reporting; normally we have 5-15 GTS and GSOD. CHIRPS shows anomalies of 125-150mm in central and eastern areas of the country and below average by 10-50mm for most other areas of the country. Compared to CHIRP, CHIRPS anomalies are amplified by approx 10-30mm in most areas, and in some areas of central eastern areas with large anomalies, by 50-60mm. Given that there are no stations in Zimbabwe contributing to these estimates, this amplification is due to station(s) in other countries. CHIRPS estimates in Zimbabwe should be considered uncertain for this reason.
Brazil: Several stations in the western portion of Brazil's Amazon rainforest and the northern portion of Bolivia identified an anomalously wet December that was not represented in CHIRP. The station values were congruent with each other, and the resulting wet patterns in CHIRPS are congruent with patterns seen in December PERSIANN data (made available by CHRS, http://chrsdata.eng.uci.edu/).
Europe: All of Spain (except for the Northern coast) showed below average rainfall in CHIRPS for December, continuing a dry trend from the months before. Northeastern Italy has a station reporting surprisingly low values (added to station watchlist - #201424).
North America: The Pacific Coast - from the top of CHIRPS (Vancouver island) stretching down to the California Bay Area, and then inland along the Sierra Nevadas, down to Sequoia National Park - shows extremely dry conditions in CHIRP, the stations, and CHIRPS. December was a particularly dry month, with many stations reporting 0mm of rainfall, following from a relatively normal November and dry October. The stations pick up very dry conditions along the Central Coast (in Santa Barbara and then stretching to LA, San Diego, and to the Inland Empire). Several surprising blotches of high rainfall values in New Hampshire and West Virginia present only in the r-checks file (@ -79.8, 38.7 & @-71.1,44.4)
CHIRPS algorithm issues to explore and fix: Issue of station duplication was explored in more depth. Analysis showed that throughout the CHIRPS time series (back to 1981) there are typically 300 to 1400 stations that are included in CHIRPS more than once in a given month. This reoccurs in some known areas, like Kenya and southern Brazil, but analysis showed that it also occurs in areas of the African Sahel, eastern South America, the US, Australia, southern Africa, and elsewhere. Many instances were not visible in Rchecks because of location overlap. Steps to stop this duplication were discussed more, and consensus was that it would require an algorithm correction and reprocessing of CHIRPS to a newer version 2.1. Other improvements could also be implemented. More discussion will continue.
Contributors: Laura Harrison, Emily Williams, Will Turner, Marty Landsfeld, Libby White
November 2017
Northeastern Kenya/Southern Somalia: Very high amounts of rainfall occurred in early November 2017 in some parts of this region, as reported by FAO SWALIM stations. CHIRP also shows above average conditions in NE Kenya and across the northern parts of southern Somalia, though CHIRP anomalies are much smaller (up to 35 mm above average). Two Bay region (Somalia) stations reported around 400 mm rainfall, and that most of it came between Nov 1 and Nov 12. Nearby SWALIM stations reported much lower amounts ranging from 65mm to 185mm. Support for anomalous wet rainfall in that area also comes from ARC2, which shows positive anomalies for most of southern Somalia. Several important points are: 1) These storms do not seem to have affected southern areas of eastern Kenya and southern Somalia, 2) Despite the storms in some areas, products indicate below average rainfall for the October to December period for much of eastern Kenya and southern Somalia CHIRPS prelim ARC2, 3) For agriculture, the below average October and below average conditions after these early November storms are concerning. It should also be noted that the CHIRPS reality check process was especially useful in this case. Those two Bay stations interacted with the CHIRPS algorithm to produce an artificially widespread area of highly above average rainfall across the region. Discussions and experimentation yielded a solution. These stations were not included in CHIRPS, though other wet SWALIM stations were, and the extent of the anomalous rainfall became smaller. By not including these extreme stations in November 2017 data, CHIRPS is able to portray a more accurate pattern at the regional scale.
Stats
New CHIRPS - CHIRP high for all of Africa. This is may be plausable since areas of Somalia, Madagascar, S. Africa, Kenya and Gabon were increased by the stations observations.
New CHIRPS - CHIRP low for all of the Great Lakes region. This looks reasonable since many stations in Wisconsin lowered the values for the CHIRPS product.
CHIRPS algorithm issues to explore and fix:
1) Perhaps interpolation oddness to correct in V3. On the east coast of South Africa there are 4 stations on the coast showing high rainfall (~260) whereas CHIRP says ~120. Because there are no stations in the ocean to bolster the coastal ones the inland stations dominate and the high stn values essentially aren't being used. CHIRPS with these stations overlaid
2) See influence of extreme stations in top entry. Could be that larger impacts are in cases where a) stations are added in 2nd step e.g. SWALIM vs. anchor stations, which are included in 1st step, b) stations are in drier areas with larger decorrelation distance or deviations from average are very pronounced, c) other. Should be looked into more for V3. Note that initially, anomalously wet double-counted stations on Mt. Kenya were thought to be the main cause, but removing these had nearly no impact on the data.
Perth, Australia: There is a thick cluster of stations in Perth (fGTS amd fGSOD), some of which may be double counted or overlapping.
Andaman Islands: There is widely varying pixel values over this area due to the influence of the CHPclim. There is only one station on the Andaman Islands.
Contributors: Africa: Marty Landsfeld, Will Turner, Laura Harrison; Europe, India: Will Turner; East Asia and Oceania: Libby White; Middle East: Marty Landsfeld; South America: Seth Peterson
October 2017
Current East Africa IPC Acute Food Insecurity Phase Level 3 & 4 (Crisis & Emergency) areas http://www.fews.net/: October rainfall was below average and led to late start of the OND 2017 season by 10 to up to 30 days in some areas of southern Somalia. Some of these areas have experienced multiple back to back below average major rainfall seasons in 2016-2017.
Kenya: In northwest Kenya CHIRPS shows a large area of near zero values. In reality, substantial rainfall occurred her in October (and station report shows supports this). The reason CHIRPS does not show this rainfall is the estimates are a deviation from climatology in the CHIRPS algorithm, and teh climatology is near zero. Next version of CHIRPS will improve this aspect of algorithm so that extreme wet events are better captured.
Panama: Along the southern coast of Panama, CHIRP and RCHECKs shows wetter than average conditions; however, the CHIRPS prelim show it as drier than average. May be being forced by stations in Columbia or further north.
Contributors: Africa: Marty Landsfeld, Will Turner, Laura Harrison; East Asia and Oceania: Libby White; Caribbean, North & Central America, Europe: Emily Williams; Middle East: Laura Harrison; and South America: Seth Peterson
September 2017
Current East Africa IPC Acute Food Insecurity Phase Level 3 & 4 (Crisis & Emergency) areas http://www.fews.net/: September rainfall was mildly below average by 10-20 mm in some of these areas in Ethiopia (southern Oromia and central Somali), Somalia (Bakool in north part of southern Somalia), and Kenya (coastal zone). Rainfall in the next 1-2 months is most important to the current season in these IPC Phase 3+ areas, but average to below average September rainfall is not a good start. Some of these areas have experienced multiple back to back below average major rainfall seasons in 2016-2017.
Nigeria: There is a rather large disparity between CHIRPS and ARC2 in Nigeria for the month of September - CHIRPS is relatively wet in central/northern Nigeria, and relatively dry in the southern portion of the country; ARC2 shows nearly opposite anomalies in the same regions, with a large wet anomaly in far south/coastal area. RFE2 anomalies in Nigeria are similar to CHIRPS. Floodlist (http://floodlist.com/africa/nigeria-floods-kogi-september-2017) reports considerable flooding in central Nigeria, supporting the anomaly values from CHIRPS. Floodwaters from the Niger and Benue Rivers put downstream cities at risk (Sarkin Noma, Lokoja and Ibaji in Kogi State).
East Africa: Across a large area of continental eastern Africa June to September rainfall accumulations were above average. This includes southern Chad, Sudan, South Sudan, Uganda, Ethiopia, and western Kenya. In some Ethiopia and Kenya highland areas the June to September totals were around 2.5 standard deviations above normal. Above average rainfall in September contributed to these seasonal wet anomalies in parts of all these countries.
West Africa: For a large area of West Africa, CHRPS shows September rainfall was below average. This occurred in Ghana, Togo, Benin, Senegal, southern Mali, eastern Guinea, Burkina Faso, Niger, northern and southern Nigeria. According to CHIRPS, it was a continuation of dryness that also occurred in August in some of those areas (eastern Guinea, southern Mali, parts of Burkina Faso, Niger, and northwest Nigeria). Burkina Faso and eastern Guinea also had a drier than average July.
Australia: Two stations were removed, one in Victoria and the other in Queensland. There were also several climatology artifacts across Australia.
Fiji: One station was removed as it was much, much lower (4mm) than CHIRP climatology showed. Station did not impact CHIRPS much.
Philippines: Station values are in agreement in CHIRPS, but show higher precipitation (sometimes upwards of 1,000mm as opposed to 500mm) than in CHIRP. The ~20 stations in the Philippines greatly influenced CHIRPS.
Taiwan: Station values are in agreement across the island, show significantly lower values than in CHIRP. However, we only have station data for the lower elevations, and most of the precipitation shown in CHIRP is in the higher elevations.
Japan: Station values in agreement but show less precipitation than in CHIRP. The station values seem to have had a high impact this month.
North & South Korea: There is a sharp contrast between the CHIRP (higher than average precipitation) and the CHIRPS (lower than average precipitation). Stations appear to be in agreement with each other, so values were kept.
Spain and Portugal: CHIRPS shows September rainfall was below average across both countries, which continued a severe drought in some areas. More recently, massive wildfires in northern Portugal and northwest Spain have consumed forests and killed at least 39 people.
France: Northern France (in the Cotentin Peninsula, in the Caen region) has a noticeable artifact. This artifact is present for all months in CHIPClim.
Croatia: The coastal part of Croatia had a large positive rainfall anomaly that is captured in CHIRP, but is intensified with the rain gauges in the region.
CHIRPS algorithm issues to explore and fix: Rchecks efforts identified 18 stations to be removed from the pre-final version of CHIRPS. Some of these were stations with what appeared to be possible bad values, and the values were applied to two or three locations. This procedure of allowing a station value to be used in more than one location needs to be corrected (stopped). It is especially problematic in areas with low station density.
Contributors: Africa: Laura Harrison, Will Turner, Emily Williams; East Asia and Oceania: Libby White; Europe and Middle East; Sari Blakeley; Caribbean, Central, and South America: Marty Landsfeld; North America: Laura Harrison
August 2017
Ethiopia: In northern Ethiopia, data shows a swath of above average rainfall. No stations reporting there. Anomaly values agree with ARC2: 125-200mm above average. Between CHIRPS and ARC2 there are differences in spatial extent of wet anomalies- CHIRPS has them focused on north-central areas, ARC2 has them across northwestern areas. Overall JJA CHIRPS anom is above average because of anomalous August rainfall. Rainfall in late July and August is important for seasonal totals; June-July were deficit months.
Coastal West Africa: Above average August precipitation; consistent with reports of flooding in Guinea/Sierra Leone (Africa hazards report: (ftp://ftp.cpc.ncep.noaa.gov/fews/threats/afrhaz20170831.pdf)
Côte d'Ivoire: A station in southern Ivory Coast was put on the watchlist for having a much higher value than both nearby stations and CHIRP (333mm vs. ~160mm).
Nigeria: Three Kukua stations were drastically lower than CHIRP and surrounding stations (~16mm vs. ~200mm). These stations were removed.
Tanzania: Data show above average rainfall in some areas of northeastern Tanzania including along coast and islands. Based on 4 stations and CHIRP to a minor extent.
DR Congo: Data shows strange blob of below average rainfall in east Congo. Possible from a weak below average signal in CHIRP; maybe from additional influence of moderate below avg stations in Rwanda/Burundi?
Southern Mexico, Guatemala, Belize: CHIRPS shows below average rainfall in these areas; based on ~50 stations in Mexico, several stations to the south of Guatemala, and to a lessor extent CHIRP. 0 stations in Guatemala and Belize contribute reports to CHIRPS.
Australia: The south eastern Australian coast is somewhat dryer according to station data when compared with CHIRP.
Indonesia: Northwestern Papua had a station removed because it was showing inconsistently lower rainfall than CHIRP and the surrounding stations.
Brunei: A station just outside Brunei was provisionally removed because it reported over 1,000mm of rain vs. ~400mm in CHIRP and surrounding stations.
China/the Koreas: Hubei, Anhui, Jinlin, and most of both North and South Korea station data reported heavier rainfall than CHIRP. Hubei and Anhui stations reported twice as much and Jinlin and the Koreas reported roughly half again as much as CHIRP.
Hurricane Harvey: CHIRPS shows the extreme rainfall associated with Hurricane Harvey in Texas, Louisiana, Oklahoma, and Arkansas. Stations increased the above average signal in CHIRP. CHIRPS anomalies are +300mm for large areas.
CHIRPS algorithm issues to explore and fix: 1) Double-counting stations 2) SETH'S MYSTERY. 1) Currently, when a report from a station is not available, the algorithm looks to a neighboring station to fill it. This can result in the same station value being counted two or more times. This method can cause large problems when double-counted values are bad values; in less extreme cases is still hard to assess what data is right or wrong. Overall, there should be a catch implemented to prevent double-counting. 2) SETH"S DESCRIPTION : in coastal central Brazil, near the town of Salvador, CHIRP shows relatively low rainfall, all of the nearby stations also show low rainfall, somehow RCHECKS/CHIRPS showed a massive increase in rainfall 180 to 373mm, 101 to 219mm are two examples.
Contributors: Laura Harrison, Africa & North & Central America; Libby White, Africa & East Asia and Oceania; Will Turner, Africa & Eurasia; Seth Peterson, South America
July 2017
Ethiopia: Below normal rainfall in July 2017 in north eastern Ethiopia. A consistent story across data products (CHIRPS, CHIRPS and stations, ARC2, PERSIANNE, NMA mid-season assessment)
Sudan: V artifact in Sudan (from CHIRP)
Japan: Hokkaido stations report slightly dryer conditions than indicated in CHIRP.
Australia: There is a strange square artifact in New South Wales.
Central America: Above average July rainfall in eastern Honduras, eastern Nicaragua, northern Costa Rica, Panama. Below average in western areas, southern Mexico, Guatemala, Belize, some coastal areas of Mexico (Pacific and Gulf). Overall agreement with PERSIANNE data in terms of this pattern of anomalous rainfall. There are gaps in station reports in Central America this month. Guatemala has 0 stations. Same for June 2017. In May and earlier in 2017 typically had 2 or more (GTS & GSOD). Honduras, Costa Rica, 0 stations. Panama, 3 GTS. Honduras typically has 2 GHCN-v2, Costa Rica has 2 (GTS and GSOD).
Southern Mexico/Guatemala central border area and Belize: Circular below average features. Coming from CHPclim, which has higher climatology in those areas (% of normal applied to higher values translates into larger anomalies). No stations in these areas to compare to.
Northern US and British Columbia: In western areas, CHIRPS shows a swath of below average rainfall for July (1 to 2 standard deviations below normal). Similar area as recent wildfires. Anomalies are average in most of Western US (no rain), with exception of Arizona (and NW mexico) with above average by 25-75mm. Above average rainfall in SE Colorado, SE Oklahoma, and regions near Lake Michigan and Lake Erie including Ohio, Indiana and southern Wisconsin. Also above average in mid Atlantic seaboard. Below average mixed with average in much of SE US, southern Texas, and central US.
CHIRP issues in Indian Ocean: Artifact in CHIRP climatology in July—mottled rainfall pattern across southern Indian Ocean including Madagascar area. June also has a (different) mottled pattern in CHIRP climatology. This needs to be addressed before offering CHIRPS data or CHIRP-based data products over ocean.
Contributors: Laura Harrison, Africa & North & Central America; Marty Landsfeld, South America and regional stats; Libby White, East Asia and Oceania; Sari Blakeley, Africa & Eurasia; Will Turner, Africa
June 2017
Ethiopia: Inclusion of stations enhanced the magnitude of June rainfall anomalies in some areas, compared to satellite-based estimates from CHIRP. Across Oromia and central Ethiopia anomalies increased from ~ -20 mm (in CHIRP) to ~-50 to -70 mm (in CHIRPS). In northwestern highlands area, including the stations led to the extension of anomalously wet conditions from east Sudan into and across the NW highlands of Ethiopia.
West Africa: CHIRPS shows there was a good start to the JJAS rainfall season, based anomalously wet conditions in the June data. In regard to the positive rainfall anomalies, stations and satellite-based estimate (CHIRP) were in general agreement across Gulf of Guinea region; stations added information in Senegal, Burkina Faso, and Niger.
Senegal In Senegal, there was evidence of high rainfall in the interior (near Tambacounda) through ANACIM’s rainfall page (http://www.anacim.sn/ and http://www.anacim.sn/meteorologie/produits-du-gtp/).
Madagascar: Madagascar has some very high rainfall amounts along the eastern coast. There is elevated rainfall along this zone in the CHPclim, and two stations nearby with high rainfall amounts probably contributed to the overall high rainfall along the eastern coast. To note- this data should be used with caution.
Georgia (country): Very high rainfall has occurred in southern Russia along the border with Georgia. There are news articles supporting above average rainfall in Georgia here (http://www.bbc.com/news/world-europe-33125879).
Central Kalimantan, Indonesia: Oddly low station (150.8 mm) among higher satellite and other station readings (~200-400 mm), but could be due to Geography. Station was put on watchlist but not removed from CHIRPS.
Jakarta, Indonesia: Values in CHIRPS much higher than CHIRP - station itself did not seem to have unreasonable values, but because it was counted twice it seemed to be influencing the calculations to an unreasonable degree. The station was removed.
10 stations removed, 15 added to watchlist Also, the need for an improvement in the CHIRPS algorithm was highlighted by a case in Rwanda where a station report was double-counted (and that station happened to have a bad value). Station was removed and issues was noted with data curator.
Contributors: Laura Harrison, Africa & North & Central America; Marty Landsfeld, South America and regional stats; Libby White, East Asia and Oceania; Sari Blakeley, Africa & Eurasia; Will Turner, Africa
May 2017
SouthEast Asia: Thailand, Cambodia, Southern Vietnam and Southern Laos as well as Sumatra and Indonesia are wetter than usual by 100 mm or more. Northern Vietnam, Taiwan, West Coast of Myanmar and the Chinese provinces of GuangDong, Fujian and Jiangxi are dryer than usual by 100 mm or more.
Australia:
Southern coastal Angola: SASCAL stations report above average rainfall, with totals of 20-60mm.
Tanzania: As part of an above average rainfall signal along coastal TZ and SE Kenya in May 2017, a GTS station in Zanibar reports 638 mm. In terms of standardized anomaly at a station (z-score of 3.2), this is one of most extreme reports of global stations. Something also to note is that there are some extremely large values in CHIRPS (>1000 mm) in this area. CHIRPS anomalies are mainly 200-300 mm above average, but there are a few pixels with anomalies 500-900 mm. They are a product of the algorithm, as CHIRP rainfall totals are around 600-800 mm and anomalies are 300-400 mm.
East Africa, Lake Victoria area: High rainfall values- from 200-460 mm reported by 4 stations. Several others nearby also report positive anomalies.
Niger, Chad, Sudan: Data artifacts in northern parts of country. These are from the CHIRPS climatology, CHPclim. New TAMSAT v3 data also has them because they also use CHPclim as their climatology. Artifacts previously noted in this wiki. Needs attention in next version of CHIRPS/CHPclim.
Kenya: A bad station value at a GCHN-v2 station in Garissa was identified and removed from CHIRPS. It was identified using a report of MAM 2017 rainfall from the Kenyan Met Agency. A neighboring GTS station reported 13 mm, which is more realistic.
Argentina: Above average rainfall in NE (see Brazil entry). In western part of Argentina CHIRPS data has a visible north-south artifact line.
Brazil: In southern Brazil and NE Argentina CHIRPS is correctly showing an area with concentrated high rainfall values. This is based on comparison to Argentina Met Agency maps. In northern Brazil and eastern Columbia, CHIRPS shows a widespread below average rainfall signal. This comes from ~11 stations and in part of the anomalous area, CHIRP. Circular data artifacts are seen in southern Brazil. These artifacts were previously noted in this wiki. Needs attention in next version of CHIRPS.
N. America: Stations had a large effects in the midwest and eastern seaboard. CHIRP did not do well in these regions but the station adjustments corrected that.
Italy removed a false zero in south central region.
Regional Statistics checks The Africa region contained a new high for the maximum value in the region of 1716.9 on the island of Zanzibar. Globally, a new high for the maximum value of nearly 2400 was detected near Chichi-jima Island south of Japan.
March 2017
Madagascar: Northern Madagascar has highly above average rainfall in March CHIRPS, with anomalies on the order of 200 mm to 500 mm and March totals up to 900 mm (35"). This information comes from stations and the satellite-based CHIRP. In the first week of March a strong tropical cyclone named Enawo made landfall in northern Madagascar. Enawo is the strongest cyclone to make landfall in Madagascar in 13 years. It was equivalent to a Category 4 hurricane. 20,000 homes were destroyed.
Angola: CHIRPS shows below average rainfall for large area in central western Angola. This information is coming from one station (which has a reasonable rain value) and also CHIRP. The satellite-based products ARC2 and CHIRP both show below average rainfall in that area. According to CHPclim this area typically gets 200-250 mm in March (ARC2 shows 150-200 mm in its climatology). The station and CHIRPS report 100-130 mm in the area. Persistent dryness has been an outgoing issue in this part of Angola for the October to May season, with suppressed rainfall since December.
East Africa: CHIRPS shows below normal rainfall across much of this region: In Kenya, northern Tanzania, southern Somalia, and southern Ethiopia. This indicates a poor start to the March to May rainy season. The negative anomalies are supported by 40+ stations (many of these are in Somalia), by CHIRP, and also by ARC2. Concern for the season due to the poor start is detailed in the CHC blog.
Northern Somalia: An area with one station reporting 41 mm rain that is near stations reporting 0 mm rain was examined. Support for the idea that this mix actually occurred came CHIRP and RFE2, which showed that satellites also picked up on some rainfall there. Should be noted that CHPclim shows this area is typically wetter than surroundings.
Honduras: An area of northeastern Honduras, near San Pedro Sula, has three GSOD stations that report above average rainfall. One of those has a very high rain total of 411 mm, another reports 206 mm. Together, and with input from CHIRP, they are responsible for above average rainfall in CHIRPS in this area. The anomaly at the very wet station was ~300mm. Given such a large magnitude wet anomaly, and convergence from these stations, we expected to find support for a wet event in other data sources. CHIRP shows a small wet anomaly. Otherwise, no support comes from PERSIANN or CMORPH rainfall products. No news reports were found online. These stations seem to report on a semi-monthly basis, rather than monthly, and tend to report high rainfall values. We retained these stations in CHIRPS, but added them to the watchlist for future review.
Australia: Despite [record breaking rainfall in March http://www.news.com.au/technology/environment/the-wettest-march-in-recent-history-is-on-the-cards-as-sydney-clocks-up-16-rainy-days-and-more-than-a-week-to-go/news-story/988409de59d01a92197439139509d007], including a particularly intense [cyclone https://www.washingtonpost.com/news/capital-weather-gang/wp/2017/03/28/cyclone-debbie-roars-ashore-in-australia-with-160-mph-wind-gusts-and-30-inches-of-rain/?utm_term=.0603b199256a], there were a few very low/zero value stations that we tossed out.
China: Heilongjian and Altay China had several stations that were showing unfeasible high values (300mm+) in relatively dry regions. No evidence of localized weather events could be found to support them, so they were tossed out. Similarly, Jiangxi had some suspiciously low values (~40mm), especially when viewed in anomaly, so they were tossed out as well.
Argentina contained two stations that were outliers, compared to their neighbors, and were removed. One GSOD station had a z-score of 5.28.
South America had the highest mean CHIRPS value for March in our records. The CHIRPS Mean regional statistics shows the highest mean value on record and by far the highest Maximum CHIRPS value on record. We investigated these values and found the there were record rains reported along the Peru/Ecuador border by The Atlantic and Earth Chronicles websites.
19 stations removed, 25 added to watchlist 19 stations were removed from the preliminary version of CHIRPS due to being identified as unrealistic values during the Rchecks process.
Contributors: Laura Harrison, Africa, Central America; Marty Landsfeld, North, South & Central America; Libby White, East Asia and Oceania; Sari Blakeley Africa & Eurasia
February 2017
South Africa Two very wet stations in northeast (near 24.5S, 30E) attracted our attention. The wetter was more than 350mm above average with a value of ~ 550mm. These are on the eastern edge of mountain range. Conditions were wetter than normal across the region. Due to these factors, the station values were deemed ok and retained in CHIRPS. If these station are indeed accurate, they are valuable to have in CHIRPS because captures the impact of orographic rainfall enhancement in the region. Will keep an eye on them going forward.
Tanzania A GHCN station in Tabora (central TZ) was removed. It reported ~15mm and seemed to be responsible for surrounding negative anomalies in CHIRPS. In comparison, CHIRP doesn’t show a negative anomaly- it shows near average in the area; RFE2 shows above average. ARC2 daily time series shows rain for many days in February (~100mm total).
Northern Mozambique Large negative anomalies. Station and CHIRP in agreement. Drought has affected this region for most of the past several months [3].
Australia Very wet February in western Australia. Stations and CHIRP show the extreme conditions. In Perth, Feb 2017 was the wettest in decades at many sites. According to Australia's BoM: Monthly rainfall totals were in the 80-140 mm range across Perth, and were more than five times higher than normal. Perth Metro's monthly total was the second-highest February rainfall total on record at the site and the wettest for 62 years, since the record high of 166.3 mm in February 1955.
California, USA CHIRPS shows the extreme rainfall that helped to end the drought for a majority of California [4]. Atmospheric river events in February brought flooding, landslides, and damaging winds.
Contributors: Laura Harrison, Africa, North America, East Asia and Oceania; Marty Landsfeld, Africa, South & Central America; Sari Blakeley Africa & Eurasia
January 2017
Southern-Eastern Africa rainfall dipole continues January CHIRPS shows the anomalous wet (dry) conditions in southern (eastern) Africa that persisted since November. The dipole was most prevalent in December and January. January CHIRPS shows rainfall 150mm+ above average in Botswana, South Africa, southern Malawi, Zimbabwe, and Mozambique, with the largest anomalies (250mm-400mm) in eastern Zimbabwe/central Mozambique. Deadly flooding occurred in Limpopo and Mpumalanga (South Africa) [5]. CHIRPS shows northern Mozambique and Madagascar with January totals that are 100-250mm below average. Rainfall was more than 2.5 standard deviations from the norm in some of these areas. In Tanzania rains were 50-75mm below average across much of the country.
Kenya Rchecks identified three stations that reported questionable values in western and southern Kenya, and these were not included in CHIRPS final. Two appeared to be false zeros, and one appeared to have an erroneous high value that would have influenced data near Nairobi and over Mt. Kilimanjaro in Tanzania.
Ethiopia Many near-zero value stations earned a closer look. They seemed reasonable given January is a relatively dry month in most areas. In SW Ethiopia, where there typically is rain, CHIRPS and stations showed agreement with CHIRP and RFE2 about the area being below average by ~20mm in SNNPR.
Western Sahara On the coast of Western Sahara there are several artifacts that must be a part of CHPCLIM.
Thailand Southern Thailand's extreme wet January rainfall was one of the most extreme locations globally in the CHIRPS domain (50S to 50N). Five Thailand stations had rain reports that were more than 2.7 standard deviations from the norm. These stations measured 500mm-800mm (~20"-30") rainfall. CHIRPS shows that some areas received 500mm above average rains. Extreme values in CHIRPS are corroborated by NASA GPM data [6]. In mid January, 43 people had been killed and 1.6 million people were affected [7].
Pakistan Unusually high rainfall amounts in Pakistan were observed in January, in line with reporting of floods and high snowfall in the mountains.The Pakistan government has requested aid from the Pakistan Red Crescent Society. http://reliefweb.int/disaster/fl-2017-000017-pak
California, USA CHIRPS shows above average rainfall across the state, with wettest anomalies in the northern Coast Ranges and Sierra Nevada mountains. Much was attributed to [8] a series of atmospheric river storm systems [9]. The wettest station along the central coast was in Big Sur, which received 19" rain, as was forecast [10].
Queensland, Australia One zero value CHCNd station surrounded by higher value stations was tossed out.
Taiwan One zero value fGSOD station among stations reporting higher values was tossed out.
21 stations removed, 30 to watchlist Rchecks examination identified these stations as having values that were not accurate, based on careful comparison to other data, neighbor stations, and to reports. Past reports from these stations were also incorporated in decisions. See the watchlist for more details. [11]
Contributors: Laura Harrison, Africa, North & Central America; Marty Landsfeld, Africa, North, South & Central America; Libby White, East Asia and Oceania; Sari Blakeley Africa & Eurasia
December 2016
Tanzania, northern Mozambique, northern Zambia, Madagascar, southern Kenya and Uganda: CHIRPS shows drier than normal conditions across this large region. Largest deficits are 100-150 mm. The CHIRPS anomalies come from reports by approximately 20 stations and also from the CHIRP satellite signal. Central/southern Tanzania and northern Mozambique were the epicenter of deficits according to CHIRP. The combined influence of stations and satellite resulted in December rainfall estimates that are 1.5 to 2 standard deviations below average across the region.
Zimbabwe, east Botswana, southern Mozambique, northeast South Africa: Above average rainfall in these areas. Multiple products (CHIRPS, ARC2, TAMSAT, CHIRP) are in agreement about this dipole pattern of rainfall [12]. Stations in Zimbabwe and South Africa were especially scrutinized because of high variability. Several stations in this region, and the Kenya/Tanzania/Zambia region, were removed due to extreme values. See our station watchlist for more information.
Ethiopia: A GHCN-v2 station that reported extreme wet value was removed (36.8E, 7.7N)
Nigeria: Removed station with strange value at a station (=110204); an error from new station source (Kukua) that made it past pre processing.
Nicaragua, Honduras: Large wet anomaly along eastern coast, with CHIRPS showing show areas recieved 650mm (200 mm above average). A feature from CHIRP, as there are no stations reporting in area. The PERSIANNE-CCS precipitation dataset also shows this wet feature.
Argentina: Three GCHN-v2 stations in different locations report the same value (267 mm). Curious and questionable. Added these to station watchlist to keep an eye on in future; based on previous months, there are no known issues at these stations.
Australia: A few stations with suspicious zero values were thrown out in Western Australia and Queensland.
Kochi, India: Suspicious zero value station was removed.
Various CHPclim artifacts: CHIRPS is being repeatedly affected by the following December CHPclim problems: Extreme value on Canary Island, striping in western Sahara, small wet area in Algeria near 1E, 29N creates strange symbol-like feature in CHIRPS. Also a large artifact in Egypt (a 1.5 degree radius splotch of low values).
Contributors: Laura Harrison, Africa & Central America; Marty Landsfeld, Africa, North, South & Central America; Libby White, East Asia and Oceania; Sari Blakeley Africa & Eurasia
November 2016
NW Argentina: Area is generally dry except for an area of high precipitation around the village of San Miguel de Tucuman. A newspaper report from November 7th notes that a soccer/futbol game was canceled because there was water on the field.[13]
Italy: In north-western Italy there is a wet anomaly, and then a dry anomaly to the east; various reports back this up [14] [15] [16]
Czech Republic: There is a dry anomaly in Ceske Budejovice, checks out according to sources [17]
Alanya, Turkey: Dry along southern coast [18]
Iran: The east tends to be dry, but there was a station that showed an increase in 14 cm of rain (small amount); this showed up as an extremely positive z-score.
India: Southern India (into Sri Lanka) is showing up as extrememly dry, which is correct and backed up by sources indicating the monsoon season has had few rain days and ran a large deficit by the end of the month [19] [20] [21][22]
Contributors: Emily Williams, Eurasia; Marty Landsfeld, North & Central America; Libby White, East Asia and Oceania
October 2016
Somalia and east African horn: CHIRPS and stations show expansive areas of below average rainfall in October. Areas of largest deficits are in southern Somalia (more than 100 mm below average) and central Kenya, near Meru (more than 200mm below average). The deficits are highly concerning in Somalia as the October is generally one of the wettest months of a very short cropping season.
Gabon: CHIRP and 3 stations in agreement about below average rainfall in western Gabon.
Sudan: No stations are reporting to CHIRPS in Sudan this month. The number of stations reporting in this country seem to oscillate between either 0 or around 10.
Southern India: CHIRPS shows deficits of 100-200 mm in southern India. The data correctly indicate widespread drought conditions, which have been reported to be negatively impacting water resources for agriculture and other uses. In Kerala state, "most of the water reservoirs across the state have recorded a water deficit of 50 per cent. The South West monsoon has been deficit by 34% while the North East monsoon is expected to be deficit by 69%." news report
Indonesia: Stations in the region are generally high value and backed up by weather reports; however, a few stations showed great variation with their neighbors, some over 300mm higher.
China: Several stations around Qinzhen and Shenzhen showed ~300mm higher values than their neighboring stations.
Yonaguni, Japan: One station shows a value ~250mm higher than its neighboring values.
Contributors: Marty Landsfeld, North and Central America and Africa; Libby White, Oceania and East Asia; Seth Peterson, South America and Africa; Sari Blakeley, Europe; Laura Harrison, Africa and Oceania
September 2016
New Zealand: the pattern in CHIRPs of North Island wet, South Island dry is correct [23]
Ethiopia: the pattern in CHIRPs of the SW part of the country being dry is correct [24]
Brazil: southern Brazil was indeed dry in September [25]
Contributors: Marty Landsfeld, Europe and West Asia; Seth Peterson, South America, Australia, NZ, & Africa; Sari Blakeley, North America & Africa
August 2016
Japan: A few stations were able to capture the heavy rains on Japan's east coast better than CHIRP alone (~400mm - 500mm as opposed to CHIRP's less than 200mm on average). [26] [27]
Shandong, China: Two stations reported nearly 500mm in rain, while surrounding stations and CHIRP report less than 200mm (on average). Weather reports do not indicate high levels of localized rain in that region.
Hainan, China: Typhoon Dianmu seems to be responsible for the very high (847.59mm) precipitation recorded, though CHIRP did not capture this rainfall as well (reported between ~200mm to ~500mm).
Contributors: Marty Landsfeld, Europe and West Asia; Libby White, Oceania & East Asia; Seth Peterson, South America & Africa; Sari Blakeley, North America & Africa
July 2016
Somalia: Many stations reported zero or near-zero values, while CHIRP estimated non-trivial values but it was decided that since CHIRP will over-estimate low values in these conditions that the station data probably was correct. Having viewed July estimates of ARC2, the decision was supported.
Madagascar: Discontinuous patterns of precipitation, especially anomaly and z-score values, were noted but Pete explained how this is part of the climatology and will hopefully be fixed in the next version of CHIRPS.
Multiple countries: 17 stations with suspect values were added to the watch list. It was determined that their effects were minimal so were not removed to create another version.
Central America: Good overall agreement with ARC2 product. It was noted that there are only 5 stations for all of Honduras, Nicaragua, El Salvador & Panama which unfortunately is typical.
Brazil: Many zero values new Sao Paulo/Rio area that generate "dimples" in the product but viewing precipitation map from INMET website confirmed dryness.
Mexico: Station data reduced CHIRP values south of Mexico City and near Santa Cruz.
China: Stations in Hubei, Shanghai, and Shanxi picked up on heavy rains not present in CHIRP [28] [29]
Time Series Statistics Plots: All regions within normal ranges with the exception of southern Africa which tied CHIRPS Maximum value. It was a very localized occurrence and accepted.
Contributors: Marty Landsfeld, North America and Africa; Libby White, Oceania & Asia; Seth Peterson, South America & Africa; Sari Blakeley, Europe & Africa
June 2016
Colombia: Colombia was generally drier before stations added, stations made it wetter. One station (20758) led to a z-score about -4.5 (value of 30mm, where surrounding area was 200-300mm), and was therefore temporarily removed.
Guyana: A station (205606) reported 1380.6mm of rain on the coast; while there were a couple of reports of flooding [30], none matched the magnitude of the station, and was therefore temporarily removed.
Brazil: Several stations (205639, 205664, 205655, 205651, 205645) all had values of over 1000mm in climatologically drier areas. All were removed. A station in SE Brazil (285717) had a high rainfall value in a climatologically wet area, creating a wet “bubble” in anomaly space, and was temporarily removed.
Southern Chile: Dry anomalies/z-scores, which match up with TRMM.
Costa Rica: A station in Costa Rica/Nicaragua shows a high positive anomaly, where CHIRP and TRMM shows negative. Weather Underground reports 242mm [31] , matching the CHIRP value but not the station value. Therefore is temporarily removed.
Mexico: Tropical storm Danielle caused flooding, shows up in CHIRPS well [32] ; Mexico City showed up with z-score of 4.34.
United States: In California and Nevada, the z-scores for CHIRP are high for slightly high anomalies, explained by their having very dry climatologies. In West Virginia heavy rain showed up in CHIRPS, backed up by national forest alert [33]
Indonesia: There was heavy rain on the island of Java, leading to flooding [34], as well as on Sulwesi. This matches with reports [35].
Taiwan: A station (203670) off the northern coast of the island reported 1440.40mm, while another station (203682) on the island reported 1383.09. Super Typhoon Nepartak came through in June, reportedly dumping 154 mm in one day [36] . TRMM reports high anomalies in the area (300-500mm extra) [37], but not nearly as high as the station values.
Oceania: New South Wales was hit with an intense storm system, ranging from Brisbane to Sydney and even reaching Tasmania. [38] [39]
Ethiopia: New stations! The addition this month is ~25 stations from Ethiopia’s National Meteorology Agency. The stations had particular influence on CHIRPS in the northern Oromia region. Here, CHIRP estimated below average rainfall but the station observations showed the deficiency was larger in magnitude—at three stations June anomalies were 116-130 mm below average. Across climatologically wet parts of Ethiopia, the final CHIRPS product shows N/S oriented swaths of above average rainfall along the Sudan border region, below average June rainfall along western highland areas (anomalies -30mm to -90 mm), and average to slightly above average June rainfall in eastern highlands areas.
Guinea/Sierra Leone: The GSOD station 276516 (Data=688.59 mm, CHPclim ~ 350 mm) at Conakry, Guinea was checked due to its large positive rainfall anomaly. It was deemed ok to retain in CHIRPS based on convergence with NOAA’s ARC2 data, which also shows above average rainfall in the Guinea and Sierra Leone area in June. Compared to ARC2, CHIRPS shows smaller magnitude anomalies, which range from 50-200mm. ARC2 shows 300-500mm anomalies.
Madagascar: Some visible block patterns in CHIRPS data. These are also seen in CHIRPS Prelim and CHIRP. Note that there is blockiness in CHIRPS data in many low rainfall areas in the general region, but these stand out in Madagascar because of some high rainfall values mixed in.
Europe: CHIRPS shows above average rainfall in June across large areas of western Europe, southern Europe (excluding Spain, Portugal), and parts of south eastern Europe (especially Romania). In some areas, based on the CHIRPS standardized anomalies (z-score maps), the magnitude of rain received in June 2016 classified as 1 in 7 year to 1 in 50 year events. Photos and descriptions of some of the damage can be seen here: [40]
China: Heavy rainfall and reports of flooding in southern and eastern China [41], plus the reports from >50 stations substantiate the above average rainfall shown in CHIRPS (100-200mm anomalies).
Japan. CHIRPS shows positive rainfall anomalies of 50-200mm in southern Japan. These are substantiated by ~30 stations and Floodlist reports of deadly floods and landslides. On June 21st for example, Kosa in Kumamoto prefecture received over 180 mm rain in two hours: [42]
**Due to Rchecks** 26 station reports were removed from the final June 2016 CHIRPS product. Please see the R Checks STATION WATCHLIST for more information (under Helpful Links)
Contributors: Emily Williams, Americas & some of Oceania; Libby White, Oceania; Laura Harrison, Africa Europe & Asia
May 2016
Columbia Comparing CHIRP and CHIRPS, CHIRPS has more negative anomalies on the western coast and positive anomalies on the eastern border. There is a station near the Panama/Columbia border with a low value which drives the area down, but it’s confirmed in a separate precipitation report [43].
Brazil There is a station in the Southeast with a very high value (1107.0) that is surrounded by low value stations. CHIRP shows low rainfall values for that area. The addition of the station led to a circular artifact in the area, and was subsequently removed. It was a GTS station, with seq-num of 205708.
There are two more stations in Southern Brazil also creating circular artifacts; however, their values are not high enough to warrant removal. They have been added to the watchlist (205722).
Central America It is very, very dry with a historical low maximum temperature, however, nothing looks out of place [44].
Liberia The CHIRP and CHIRPS products both show dry anomalies inland and wet anomalies along the coast; however RFE and ARC2 [45] show the opposite. After adding up precipitation values from a site (not verified for accuracy)[ http://www.accuweather.com/en/lr/monrovia/361788/may-weather/361788?monyr=5/1/2016&view=table], the values reached 84 mm, which backs up the ARC2 story. However, there were some flooding reports for Monrovia [46] [47]. Overall, it is unclear as to whether or not CHIRPS is right on this one so we should watch trends in Liberia in the future.
Contributors: Emily Williams, Liberia & Central & South America;
April 2016
Central America Dry along Eastern coast of Costa Rica and Panama. Station on S. coast of Panama shows anomalously high value but seems to match with TRMM [48]. Weather underground report says in April it got 4.59 inches, or 116 mm [49]. Didn’t have visual impact on CHIRPS so can leave it.
United States April was the record wettest in southern plains, and the record warmest in northwest; [50];CHIRPS shows this very clearly. Station near Wichita Falls, Texas was permanently thrown out as it showed a super dry anomaly in the middle of very wet anomalies, and has historically given anomalously low values [51]. Station near Jarbidge, Nevada reported a high positive anomaly (138.0 mm) where adding up the daily rain amounts gives us 56mm [52]. Topographically, however, it could make sense, so it goes on the watchlist but isn’t thrown out.
Tanzania, south eastern Kenya, Uganda, South Sudan CHIRPS shows above average rainfall over large areas of the region, with April values 100-200 mm above average. Kilimanjaro (TZ) shows 400 mm above average. CHIRP and ~15 stations contributed to these data. Extreme rainfall was reported in many of these areas. Some of the most damaging events were in Nairobi and Mombasa (KN), Kasese and Kampala (UG), Mbeya, Zanzibar, Kilimanjaro, and Morogoro (TZ).
Angola There is a station on the West coast just inland of another station that shows half the value of the coastal one. The station seems to be anomalously low for flooding reports in the area and the values CHIRP assigns to the area. It is on the watchlist.
Madagascar Tropical cyclone Fantala skirted Madagascar’s northern coast, resulting in the extremely high station value [53]. There is another station on the SE coast that reported a high value where CHIRP reported low values-it is now on the watchlist.
Ethiopia There is a station in the NW of the country that is reporting a high rainfall value in the middle of very low values; it doesn’t have an impact on the final CHIRPS product, but will go on the watchlist to see what happens next month.
Chile Two stations, CHIRP, and CHIRPS final show above average rainfall in the Santiago area. Anomalies are 20-100 mm, which put rainfall in the 95th percentile (2+ standard deviations from the April mean). Floodlist reported that heavy rains and floods in Santiago left 2 people dead and 10 missing
Southern Brazil, Uruguay, Eastern Argentina CHIRPs final, from support by 30+ stations and CHIRP showed rainfall anomalies of 150-300mm in this region. CHIRPS totals in south Brazil are similar to INMET April accumulations (150-500mm). Link to report CHIRP shows a SE-NW oriented swath of heavy rain. The heavy rainfall was associated with several extreme events through the month, with greatest impacts in Uruguay. In early April, Argentina media reports claimed that over 500 mm of rain has fallen in some areas, including Alejandra in Santa Fe, San José de Feliciano in Entre Ríos, in the space of 4 days. Uruguay River rose to concerning levels. Then in mid April, more heavy rain occurred in Uruguay (150-180mm in 24 hours) and was accompanied by a tornado. 7 people died and 3,000+ people were displaced. Continuation of the severe conditions led to more flooding and displacement of 10,000 people.
Brazil Below average rainfall for much of the country (exceptions are south and north regions). CHIRPS shows rainfall as 25 to 75mm below average for most areas, with enhanced deficits (up to 150 mm anomalies) in States of Tocantins, Maranho, and Para. This general pattern is similar to the anomalies shown by INMET, Brazil’s Instituto Nacional de Meteorologia: Link to map
Australia While mostly dry, there were some moderate rains (more rain that usual - ~10-20 mm more on average) in Western Australia. [54]
South East Asia Despite an overall drought across South East Asia[55][56], Papua New Guinea experienced higher than normal rain in the north [57]. CHIRPS shows more precipitation in Indonesia (Sulawesi Selatan and Kalimantan Barat) than CHIRP alone, although not significantly above average.
Eastern China & Southern Japan Heavy rains in China and Japan are reflected in the CHIRP as well.[58][59]
Taiwan EWX classifies Taiwan as China (likely due to GAUL) - worth noting that while the PRC would be happy with that classification, Taiwan would not.
**Reality Checks update** Several station reports were removed from CHIRPS final product for April 2016. A list of these stations can be found on the Station WATCHLIST (link under Helpful Links at top of page)
March 2016
Somalia CHIRPS has 50 new stations reporting rainfall observations in Somalia, thanks to FAO SWALIM. Previously, CHIRPS relied on satellite information (CHIRP) and influence from stations in the general region to give information about Somalia rainfall. The new stations were helpful in portraying how Somalia's MAM 2016 rainy season began. Parts of southern Somalia began with negative March anomalies of ~20 mm. This is corroborated by analyses based on other data that indicate poor March and April rainfall in the region. See FEWS NET Hazards Report and discussion below for more information. Another benefit of the Somalia station addition is that some stations contributed information in northeast Kenya (shown by the March decorrelation distance map in EWX).
Kenya, southeast Uganda, northern central Tanzania CHIRPS shows below average rainfall by 25 to 50 mm, with some areas like Kilimanjaro (TZ) up to 100 mm below average. General agreement with ARC2 March anomalies. A station near Kilimanjaro at Moshi (37.1E,3.4S) reports only 13 mm rainfall in March, with an anomaly of -90 mm. The exception to CHIRPS and ARC2 agreement is central TZ, where ARC2 shows average to slightly above average and CHIRPS shows average leaning to below average. In that area CHIRPS uses two stations (32.8E,5S and 35.7E, 6.2S). These report anomalies of -32 mm and 9 mm, respectively.
Ethiopia The pattern for March rainfall anomaly looks similar to NOAA's ARC2 and Ethiopia NMA Maproom data. March rainfall was below average by 25 to 50 mm across southwest to north central Ethiopia. A minor difference between Ethiopia NMA data and CHIRPS (and ARC2) is that Ethiopia data shows slightly above average rainfall in areas along west boundary with Sudan and South Sudan.
South Africa and Lesotho Near Lesotho and Free State (South Africa), several stations report low values that are below average. ARC2 shows similar below average March rainfall in these areas.
Angola SASSCAL station at 13.4E, 14.8S reported much higher rainfall value than its neighbor. Happened in Feb 2016 also. Checked and explained by topographic gradient (~1000 m higher than its neighbor).
Namibia SASSCAL station value at 17.3E, 20.4S removed due to reporting 0 mm next to neighbor station report of 72 mm. Same issue occurred in Feb 2016. Station is now on watch list.
Brazil Southeastern Brazil, along the coast, received very heavy rainfall, leading to flooding [60]. In general, the Amazon got more rainfall this month than it has in past months – however some of the values are suspiciously high. INMET, the Brazilian met agency, reports values closer to 300-400 mm, but CHIRPS is reporting values 400-700 [61]. There are two stations in the Amazon that drove this value up, both due to our own methodology – both stations had several days missing and we interpolated the values. One station (seq num 205630) reported 618mm but we filled in 709mm; the other (seq num 205638) reported 608mm but we filled in 650mm. We recommend taking out a different station in Brazil, in the north east (seq num 21432). This station has historically been lower than it should and significantly alters CHIRP into lower CHIRPS values. This month, the value was 21mm, surrounded by 200-400mm. The area should be wetter in the final CHIRPS. This station report was removed from CHIRPS March 2016 and the station is now on the watch list.
Columbia The round egg-shaped feature is still in Columbia, an artifact of smoothing with the station value. There are also quite a few stations reporting 0mm along the northern coast, backed up by other station data [62].
Peru CHIRPS reports a lot of rain in the north, not backed up by TRMM [63]. However, flooding reports back up CHIRPS in catching this flooding event [64].
Pakistan and surrounding region Above average rainfall, comes from ~18 stations. Other areas nearby that CHIRPS shows with above average rainfall are far northern India (~5 stations), Afghanistan (0 stations), and Jammu Kashmir (0 stations), and eastern Oman (~11 stations). Spatial extent can be attributed to CHIRP and to influence of stations mentioned above. Pakistan’s heavy rain was reported via reliefweb.int in early March in parts of Balochistan, with concerns of flash flooding. The storms continued into mid March across 6 provinces and led to flash floods, inland floods, and landslides that collapsed houses and other buildings. In the first half of March 121 people were killed and 127 were injured in Pakistan.
Balkan Peninsula countries Serbia, Montenegro, Macedonia, Bulgaria and Greece. CHIRPS shows above average rainfall (25 mm to 100 mm above average). Largest anoms were in Serbia and Montenegro. More than 50 stations reported the wet conditions across the region. According to Floodlist.com, heavy rainfall in early March created emergency situations in Serbia after flooding and landslides damaged homes and transportation links in central and eastern parts of the country. By the end of March over 1000 families received aid from the Red Cross.
Switzerland, Austria, and parts of Italy, Spain, and Portugal CHIRPS shows rainfall was 10 to 50 mm below average. Supported by ~50 stations in total and CHIRP.
Southeast Asia Above average rainfall in Indonesia indicated in CHIRPS was backed up by news reports of flooding [65].
Australia ~6 stations, especially in the west and all from the GHCN dataset, showed either zero or significantly lower values that surrounding stations, CHIRP, or weather reports.
Contributors: Emily Williams, South America; Laura Harrison, Europe and Central Asia; Libby White, Southeast Asia and Oceania.
February 2016
Tajikistan, Kyrgyzstan, Uzbekistan, Afghanistan, Pakistan The general area around Tajikistan has very suppressed precipitation, with z-scored ranging from -1.5 to -3. Reports detail that this level of supressed rainfall may lead to a drought, impacting the water supply to neighboring countries [ http://www.azerbaijannews.net/index.php/sid/241799989]. The values are verieid by reports (ex/Dushanbe, Tajikistan at 7.40mm for hte month [ https://www.wunderground.com/history/airport/UTDD/2016/2/16/MonthlyCalendar.html?req_city=Dushanbe&req_statename=Tajikistan&reqdb.zip=00000&reqdb.magic=1&reqdb.wmo=38836]). 'Note: The decorrelation map has a strange V-like artifact over Tajikistan, which may be impacting the correlation of the stations.'
Indonesia & Malaysia Significant rainfall and flooding has been reported across Indonesia and Malaysia. Values have been verified by various reports [66] [67]. Some pixels in Indonesia show negative anomalies in a sea of positive anomalies (when working in anomaly space), but when the actual precip values are added up for the month at that station (ex//Semarang [68]), we find that the values are ok.
Philippines The Philippines are several months into a significant drought, backed up by reports [69].
Angola There is a large positive anomaly in Angola. The southern tip of it has a report of flooding [70]. Much of the rain fell in the last dekad of February, with the first two showing negative or no anomalies.
Madagascar The northern tip recieved 121mm of rain in one day [71]; 700,000 people in the south were impacted by the supressed rainfall, and 30,000 in the north by flooding [72].
Mozambique Large are of high precipitation in Zambezi region observed in CHIRPS that was not seen CHIRP product. It was determined that a nearby station perturbed the climatology which corresponded to a land surface elevation gradient.
Brazil and Argentina CHIRPS compared well, visually, with the monthly Met Services of each country.
South American CHIRPS Mean regional statistic hit a another new low for February which is consistent with the last 5 month.
January 2016
Zimbabwe, Mozambique, Madagascar January CHIRPS shows large negative rainfall anomalies in these countries, on the order of 100-200 mm below average. These are more than 2 standard deviations from the mean in southern Madagascar, Tete province (Mozambaique), Mashonaland provinces (Zimbabwe), and Southeast province (Zambia). Enhanced dryness in these areas is part of a spatially large and persistent condition affecting southern Africa that is due to El Nino. See the Joint EC, FAO, FEWS NET and WFP Statement on El Niño Impact in Southern Africa
Tanzania, northern Mozambique, northern Madagascar CHIRPS reports wet anomalies of more than 100 mm. These were historically extreme (more than 2.5 standard deviations above the mean, in the ~98th percentile) in Mozambique's Cabo Delgado province and Tanzania provinces Mtwara, Lindi, and Morogoro. The largest anomalies were in Morogoro (+400mm) and areas in northern Madagascar including the Comoros Islands (150-300 mm). The very wet conditions is supported by 15+ stations. In Tanzania's Dodoma province heavy rain, strong winds, and flooding from 17-18 January destroyed 145 houses and affected 2,800 people. Previously, extreme wet conditions destroyed 1,500 homes in northern Mozambique. Due to the intensification of heavy rain in January, 5 fatalities occurred in Cabo Delgado province.
Gabon, Congo, and northern DRC CHIRPS shows rainfall as below average in January in western areas of central Africa. The estimates come from CHIRP and also ~12 stations in the area. NOAA's ARC2 data also reports a drier than normal January 2016 in this area.
More stations in Africa CHIRPS The station coverage has improved in southeast Africa. From November 2015 to January 2016 the number of reporting stations doubled in Botswana (7 to 14) and Zambia (8 to 17) and increased greatly in Angola (1 to 17). Improvements come from integration of the SASCAL dataset.
Brazil, Paraguay In central eastern and southern areas in Brazil and Paraguay CHIRPS reports wet anomalies of 100-150 mm and to +300 mm above average. More than 60 stations reported these conditions, in addition to CHIRP. According to FloodList more than 215,000 people were affected by flooding in January in Rio de Janiero, Mato Grosso, and Parana states (Brazil).
South America (northern/eastern and Amazon area) CHIRPS estimates January rainfall as being around 100mm below average from the Atlantic coast, through northern Brazil, and into southern Columbia. Some coastal zones of French Guinea show 200-300mm dry anomalies. The spatial pattern of dryness in CHIRPS is similar to what the satellite-based CHIRP data estimates, but the dry anomalies are also sourced from approximately 20 stations across the region (mainly in Brazil and to the east)
Columbia Columbia's Pacific coast area show very dry anomalies (200-400mm below average). Caution should be applied to the data in this zone as the anomalies are historically extreme (more than 2 standard deviations below the mean) but there are no stations reporting in the immediate area. Interesting effects seem to be coming from CHIRP and neighboring stations. Influence from neighboring stations is heavy in the southern section, as CHIRP shows above average in that area. Dryness in the northern section, which climatologically is drier, seems to come mainly from CHIRP.
Florida (US) and Cuba Extreme wet conditions in January in southern Florida and parts of Cuba. Rainfall was 100-250 mm above normal. The dense station coverage in the United States supports these estimates. Many areas experienced rainfall higher than the 95th percentile. Some areas broke records for January. In Fort Myers, FL for example it rained more than 8.5 inches in January (average is less than 2 inches). This followed their hottest Christmas on record.
California (US) January CHIRPS shows above average rainfall in northern California, with 50-150mm positive anomalies for most areas north of 35N. These estimates come from CHIRP and more than 40 stations. Depending on location rainfall ranged from the 68th to 90th percentile compared to previous January CHIRPS estimates.
Contributors: Laura Harrison (Africa, South America, Latin America, U.S.); 2/19/16
December 2015
Zimbabwe Thus far into the 2015-2016 season, drought conditions have affected many countries of Southern Africa, including Angola, South Africa, Botswana, Zambia, Zimbabwe, Lesotho, Swaziland, and Mozambique. This was due to a delayed start and erratic distribution of rainfall since the start of the season in October. December rainfall was a key contributor to season total deficits in Zimbabwe. CHIRPS shows large rainfall deficits across the country ranging from 50 to 150 mm below the December average. The largest deficits are in central-eastern and northern Zimbabwe. There is high confidence in CHIRPS data in Zimbabwe due to agreement from 7 stations, CHIRP, and ARC2 in most areas.
Mozambique CHIRPS shows below average for most of the country, with anomalies in northern region of -15 to -75mm and larger deficits in the central and southern region (-75 to -150mm). The northern region dryness is in contrast to what NOAA’s ARC2 and RFE2 products show for December, which is above average rainfall (50-100 mm anomalies) in Cabo Delgado province. The CHIRPS dryness seems to be coming from CHIRP, and from influence of a station in northwest Mozambique. Another difference between CHIRPS and ARC2 is in central-southern Mozambique in southern parts of Manica and Sofala provinces. Here, ARC2 shows rainfall surplus and CHIRPS shows deficit. These deficits in Manica seem sourced mainly from CHIRP and from nearby Zimbabwe stations, as a GTS station in Manica did not report a large deficit. There is congruent evidence of very poor December rainfall in southern Mozambique, with reports of deficits from three stations and agreement with CHIRP and ARC2.
Zambia CHIRPS shows that most of Zambia, in particular the southern parts, experienced below average December rainfall. Ten of the twelve stations reporting to CHIRPS in Zambia reported deficits. The worst deficit reported was near Lusaka at 181 mm below average. Poor December rainfall may have exacerbated problems with food security that were previously identified in western, southern, and eastern areas. Overall, ARC2 and CHIRPS are not in agreement in Zambia. ARC2 shows above average conditions in northwest and north central provinces. Both products agree that southeast province was below average.
Tamil Nadu, India: CHIRPS continue to show the reported continued anomalous rainfall in southern India. However, rainfall was not as severe as November, and most rainfall seems to have occurred early in December. Two stations in and around Puducherry, south of Chennai, reported 200-500 mm above the average rainfall.
Kazakhstan/Northwest China: CHIRPS reported very wet conditions in Kazakhstan, especially near the border of China's Xinjian province. Rainfall appears to be two to three times the average, with one station on the border reporting six times the average rainfall. Seven stations in the area reported above average rainfall. CHIRP generally agreed with CHIRPS, but not to the extent of the station on the border. No news reports regarding especially heavy rainfall in the region were found.
Philippines CHIRPS shows the very wet conditions that occurred in the Philippines in December due to multiple major storms. Rainfall surpluses of 250 to 900mm are shown in the data. December totals along the east coast ranged from 650 to 1400mm. According to a report from Emergency Management, the rain was caused by a cold front, dragged into the country by Typhoon Nona (international name: Melor) and Tropical Depression Onyok, which hit the country in succession in mid-December. The December storms were responsible for at least 45 fatalities.
East Indonesia/Papua New Guinea CHIRPS shows large rainfall deficits that range from 150 mm to 300 mm below average for December. This area received only 30 to 70 percent of average December rainfall, based on the CHIRPs climatology. These conditions are consistent with those experienced for several months in the region. Drought and erratic rainfall here are linked with El Nino. Impacts through the end of 2015 were depletion of food sources and lack of water for household use. These problems have caused increased disease risk due to poor sanitation and use of non-sustainable coping mechanisms, such as households selling needed assets.
Southeast China Above average rainfall in southeast China is due to more than 25 station reports and also CHIRP satellite-based estimates. The wet conditions are linked to the series of major storms, including Typhoon Nona/Melor that moved through the Philippines and the South China Sea.
United States The Midwest and Southeast US continued with above normal rains creating flooding in the Midwest. CHIRPS captured this rainfall with large areas of the country in excess of 150 mm for the month.
Colombia A large region in the center of the country, "the blob", was estimated to have received above normal rainfall after station values were applied. There was no indication of the blob in the CHIRP data field. A group of station on the northeast end of the blob may have caused the creation of this above normal rainfall pattern. There is a group of three stations with very low values of 2 mm and then one 30km to the west with a higher reading of 179mm. We think there may be some effect of the autocorrelation field causing this pattern when there is a large differential between these to estimates. The pattern is seen in the previous three months but to a lesser extent. The pattern is not seen in previous years since these data contain many more stations in the region and wash out the effect. We will continue to investigate this phenomenon.
South America Paraguay, Brazil, Argentina, Urugay: Flooding in these four countries. Asuncion, Paraguay saw a lot of flooding shown in the r-checks file[[73]] ; South Brazil saw flooding [[74]]; these reports are backed up by TRMM [[75]].
Sao Paulo, Brazil: Report says that Sao Paulo received less than normal rain in December [[76]]; pre-station CHIRPS labels the area as wet, but station data backs up a negative anomaly, and CHIRPS did a good job of incorporating the station data to drive down the final CHIRPS value in the immediate area. This lack of rainfall for December is very localized.
Brazil: The northern parts of Brazil (part of the Amazon Basin) have been in a terrible drought in 2015, which has continued in December; this patterns is backed up by Brazil’s INMET [[77]].
Peru: Artifact of flooding in northern Peru backed up by reports [http://floodlist.com/america/heavy-rain-peru-landslides-floods]
Notes on CHIRPS in South America
Station artifacts: There are circular artifacts in Southern Brazil and Paraguay, similar to the ones seen in previous months (see November's "Recurrent CHIRPS Issues"); they seem to be station-driven as they don’t exist in CHIRP.
Regional statistics
- Global CHIRPS Maximum exceed 2200 mm for a new high for December. This is still under investigation.
- South American CHIRPS Mean hit a new low for December but this is in agreement with reports from the continent.
- Southern Africa CHIRPS Max hit a new low for December but this is in agreement with reports from the continent.
Contributors: Emily Williams (South America), Libby White w/Laura Harrison (Asia), Martin Landsfeld (U.S., Latin America, Statistics); 1/19/16
November 2015
United States: CHIRPS shows the very wet conditions that occurred across the South and southern Midwest. November rainfall was 100-200 mm above average in northeastern Texas, eastern Oklahoma, Arkansas, Missouri, and in Georgia, North Carolina, and South Carolina. Monthly totals in Arkansas and Missouri were the highest on record in November 2015 (record dates to 1895). CHIRPS shows below average rainfall in coastal Oregon and coastal northern and southern California.
Mexico, Belize, Guatemala, El Salvador: The region encompassing the Yucatan Peninsula and south to the Pacific received heavy, above normal rainfall. A Guatemala station near the Caribbean Sea, Puerto Barrios, reported 680mm, which is 15 inches above normal. Reports from Guatemala explain that much of the heavy rain occurred in the second half of November. It led to dangerously high river levels and flooded communities in Alta Verapaz region. Flooding displaced thousands of people in Guatemala, Belize, and Mexico.CHIRPS also shows Panama as receiving above average rainfall.
Southern Africa: November CHIRPS shows widespread dryness across most of southern Africa, with anomalies of -30mm to -80mm. Some of the affected areas experienced below normal rainfall in October (South Africa, Zimbabwe, Mozambique, Angola). A below average rainfall season tends to occur in the region during El Nino conditions. The November dryness contributed to substantial season-to-date negative anomalies that pose a risk to cropping and pastoral activities.
Uganda, Kenya, Tanzania: November totals were 75mm to 150mm above average across most of Uganda and the Lake Victoria Basin. Similar magnitude anomalies occurred in other areas of southern Kenya and east and west Tanzania. The November wetness marks the second consecutive month month of anomalous rainfall in Uganda and west Tanzania, according to CHIRPS and the NOAA ARC2 product (Oct ARC2; Nov ARC2)
Qatar and Saudi Arabia: Areas received record rainfall in November, but CHIRPS did not pick it up. Qatar's Met Department reported a year's worth of rain in Doho (80mm) on Nov 25th. There were no Qatar stations reporting in CHIRPS. The satellite-based CHIRP product did not show sign of the wet events. There were several stations in Saudi Arabia reporting to CHIRPS in areas with reported flooding, but only one of them had a large anomaly (Hafr Al-Batin, at 90mm above normal). The influence of this particular station is not seen in the final CHIRPS product. Overall, CHIRPS shows a slightly wetter than average November in northern Saudi Arabia and no sign of the historic events noted here.
Southern Europe: CHIRPS shows below average rainfall across the region. Italy was particularly dry, with northern Italy at 150mm below average.
India: Exceptional amounts of rainfall were reported in southern India, and CHIRPS captured these anomalies well. Heavy rains occurred in areas that typically receive 150mm to 500mm in November, driving totals instead up to 2 times those amounts. The Chennai area received ~1000mm in November, according to news reports and to a GHCN-v2 monthly station that reported to CHIRPS. Some areas had the wettest November in 20 years.
East Asia: CHIRPS reported very wet conditions in southeast China, stretching from Guangi to the East China Sea coast near Shanghai. Anomalous wet conditions are also shown in Japan, South Korea, and the DPRK.
Indonesia: While most of Indonesia has below average rainfall values in November CHIRPS, there is an interesting rainfall dipole feature. Eastern Malaysia, Brunei, and western parts of Kalimantan, Indonesia show above average rainfall. The wetness is reported by multiple station observations and from CHIRP.
Brazil: Dryness persisted across the Amazon Basin in November. See October and September posts below. CHIRPS shows positive rainfall anomalies of ~100mm in areas of southeast Brazil (Sao Paulo and Rio de Janeiro). The wet November coincided with the collapse of a dam that released massive amounts of sludge and some toxic waste through the Rio Doce.
December 2015
Recurrent CHIRPS issues
- Circular-shaped artifacts are seen in the data, anomalies, and z-scores of CHIRPS data in southern Brazil. These tend to be centered at station locations. The issue needs more evaluation, but the origin seems to be from the CHPclim, which has similar but smaller features in the region. These features may increase in size according to the spatial influence of stations.
- Coastal data artifact along North America's west coast. CHIRPS is generally a land-only product, but in some areas the coverage extends 1 to 3 pixels beyond the coastal boundary. Along the West Coast these pixels have lower climatological mean values than the data on land. This results in substantially different rainfall estimates and anomalies. The differences may be due to extension of coverage of the CHPclim based on TRMM, and should be examined further. In the meantime, CHIRPS users may want to consider clipping their data to coastal boundaries to remove the artifact.
Contributors: Laura Harrison; 12/21/15
October 2015
United States: A storm complex that tapped into the moisture from Hurricane Joaquin off the south-eastern coast of the US hit the Carolina's, dumping 12-24 inches of rain (picked up in CHIRPS)[78]. Louisiana and Texas, in addition, were hit with the remnants of Hurricane Patricia, receiving a lot of rain (also visible in r-checks) [79].Finally, a dry-spell it the midwest showed up as well [80].
Mexico: Hurricane Patricia hit the south-west coast of Mexico, and rapidly downgraded, as shown in CHIRPS and backed up by FEWS early warning data [81]. Two stations however reported very low values (4 and 5 mm) along the northern border of Patricia's path. One of them, 400141, is blocked by mountains so might have a rain shadow. The other, 400984, however, is on the coast and is a station to keep an eye on. The path of Patricia can be seen here [82].
El Salvador, Honduras, and Nicaragua: The bay bordered by these three countries (where Choluteca is) has a very high station next to a low one. This is right where a severe gradient is that goes from high precipitation quickly to low. The mountains around this bay might act as a rain shadow. In El Salvador and Honduras, we see a similar pattern as the mountains block rain coming up from the south and a steep gradient occurs from high rain to very low.
Haiti: Haiti is showing a positive rain anomaly in the north west. While this area has been doing well, other reports show average instead of a positive anomaly. Might be good to keep an eye on it. [83]
East Africa: October CHIRPS is in general agreement with rainfall estimates from NOAA CPC ARC2 and RFE2 datasets in east Africa. Differences in magnitude occur in parts of Sudan and South Sudan, where CHIRPS estimates are approximately 30% lower than ARC2 and RFE. The products are all in agreement that October rainfall was above average in Sudan, South Sudan, and Uganda (CHIRPS, ARC2, and RFE2). The source of lower CHIRPS values may be (1) a drier climatology in October CHIRPS compared to ARC2 climatology and (2) features in the CHIRPS algorithm that lead to conservative estimates and low bias. Also, in an area of reported heavy rains with flooding (border of Ethiopia, Sudan, and South Sudan) there appears to be a drying influence of two GHCN-v2 stations in southeast Sudan used in CHIRPS- these reported low but reasonable values locally, but reduced the CHIRP estimate in the high rainfall area. Ethiopia contained 8 stations this month, a big improvement from the past few months.
West Africa: In October 2015, most of the station reports that contribute to CHIRPS in West Africa are from GHCN-v2, a source of monthly data that is highly ranked due to its quality control. CHIRPS compared well with CPC 30 day anomaly from the FEWS Hazards Report, 10/29/15, except in Guinea and Sierra Leone where CHIRPS is much drier.
South Africa: Stations between Lesthoso and Swaziland reported lower values than CHIRP estimated. The stations reduced the final CHIRPS which is in agreement with the FEWS Africa Hazards Report, 10/29/15, abnormal dryness polygon over the region.
Brazil: CHIRPS reports below average rainfall across much of the nation, with exception of heavy rainfall that occurred in Porto Alegre, Rio Grande do Sul state. Major flooding occurred in that area [84]. The rainfall deficits during October covered much of the Amazon rain forest and are highly concerning given the magnitude and persistence of drought conditions since 2014. The Amazon drought is reported as the worst in the past 80-100 years [85] and has created water shortages in major cities and rural areas [86][87]. Reality Checks monthly CHIRPS comparison identified the South America mean rainfall in September 2015 and October 2015 as being the driest since 1981, when the CHIRPS record began, and Brazil deficits play a major role in these continental scale deficits.
Asia: CHIRP did not perform well with Typhoon Mujigae, between Hong Kong and Hainan on Oct. 5-7th. The stations reported the precipitation amounts and CHIRPS estimates were increased in the area.
A GSOD station on northern border of Pakistan recorded 529 mm for the month. A neighboring station reported 179 mm. A news report claimed record rainfall in the area so we decided to keep the measurement.
Contributors: Laura Harrison (South America), Marty Landsfeld (Asia), Emily Williams (North and Central America, Hispanola), all-of-the-above and Shrad Shukla (Africa); 11/17/15
September 2015
Vietnam: Tropical Storm Vamco brought a lot of rainfall to central/northern Vietnam/Laos/Thailand (300+ mm with flooding and fatalities). CHIRPS picked up significant rainfall in Northern Vietnamn (around Hanoi), but CHIRPS's pattern is a bit north of the reports. [88] [89]
China and Taiwan: Typhoon Dujuan brought torrential rainfall to Northern Taiwan and Eastern China; CHIRPS shows it in E. China but not much in Taiwan. [90] [91] Stations, though, seem to be reporting well so may be an interpolation problem with the climatology.
Japan: Lots of rain and flooding along Western coast and center [92].
Malaysia, Indonesia, Papua: Massive dry swaths; many large uncontrolled fires from slash-and-burn agriculture (could be good to keep an eye on for next month).
Columbia : Station in Cali, Columbia looks low but looked at previous months values and it looks fine. Diego confirmed it has been dry there in July and August. The rains are returning now he says. SQL commands: select * from precip_monthly4 where station_seqnum=20777 select * from precip_monthly4 where station_seqnum= 205576
Brazil : Near Sao Pablo all the stations are higher than CHIRP estimate. INMET rainfall map confirmed the higher values. Brazilian rainfall map can be found at: http://www.inmet.gov.br/portal/index.php?r=home2/index Click the Mapas de Precipitacao tab and then the Plus button at the bottom of the map and an end date and time period can be selected (30 dias).
*South America record rainfall deficit* : Station comparison graphs showed a very low CHIRPS mean for South America. /home/CHIRPS/diagnostics.etc/v2.0/marty/chirps.s_amer.stats.09.png But examining the CHIRPS didn’t reveal any errors in processing and given such a strong El Nino and the warm water in the eastern Pacific to the north, it we decided it was a real phenomenon. Also, stations in NW Brazil and Columbia verify the low precip values.
Ethiopia : Ethiopia contains only 3 stations. A special check was done on the contribution these stations had for CHIRPS data and anomalies. The 3 stations (2 were co-located) showed below average September rainfall and enhanced CHIRP deficits. As a result, CHIRPS September rainfall shows ~100 mm below average in Addis Ababa and Dire Dawa areas-- roughly 25% of average September rainfall. The CHIRPS September values were compared to data plotted with the Ethiopia Met Agency's MapRoom, which is described as being satellite estimates merged with ~600 stations for the country. Similar magnitude September 2015 anomalies are seen in CHIRPS and the Ethiopia data [93] for these areas. The stations were retained in CHIRPS.
Somalia, Uganda, Rwanda and Burundi: All had 0 stations reporting
Contributors: Emily Williams (Asia, Australia, Pacific Islands), Marty Landsfeld (South America, Africa), Laura Harrison (North and Central America, Africa); 10/19/15 - 10/23/15
August 2015
North Korea: Removal of a GSOD station. DPRK experienced flooding associated with seasonal rains in early August, and from Tropical Cyclone Goni on 22-23 August, affecting South Hwanghae and North Hamgyong Provinces ([94],[95]) . The two GTS stations in the country are in these areas and reported heavy rains, which the CHIRPS reflects near these areas. GSOD stations (~12) in rest of the country report below average rain, making August an overall poor month for rain in DPRK. This has likely exacerbated the problems associated with late start to seasonal rainfall-- in June DPRK declared they were experiencing the 'worst drought in a century.' There have been major population impacts in the region, perhaps due to a combination of weather and political forces. Suggest removal of GSOD station #274228: Report is 9.19 mm in area with flooding. [96]
South Korea: CHIRPS dry anomaly confirmed. Stations show low August rainfall (verified by news reports), which has created an overall poor season there [97]. Makes North Korea dryness believable also.
China: Some cases of good stations not influencing CHIRPS local values. Saw several instances when neighboring stations swamped what looks like reasonable above average rainfall reports from some stations. Led to below average CHIRPS values in these areas. Examining monthly decorrelation distance maps may help identify scope of problem.
Ghana: Concern about station reports and conditions. Several stations reported 0-10 mm in August. These had some influence on CHIRPS. Were deemed ok stations as they had reasonable values in earlier months and seasonal rains have been below average due to active ITCZ enhanced rains in an abnormally northern position. Note: In July 2015 Ghana had only 1 reporting station in CHIRPS, as compared to 5-13 in other months.
Ethiopia: Exceptional dryness identified by ranked z scores. Z score=-2.6, station value=160 mm, Ethiopia highlands (10.33N, 37.740E). Determined CHIRPS value in area was representative of conditions. Also that this is an area of potential concern that needs highlighting on Hazards report-- GeoWRSI shows crops were in reproductive phase in August; Prelim CHIRPS shows September 1-10 was below average; ARC2 shows below average thru September there also.
India: Incorrect wet anomaly in northern India. India's Met Department shows below average ([98]), but CHIRPS shows strongly above average. Due to combination of: 0 India stations in area + very wet observation in NE Pakistan (verified by reports) + wet station in China + CHIRP shows wet anomaly. Otherwise, CHIRPS correctly identified August rainfall deficits across most of India and surplus in Bhutan.
Chile: Atacama desert, possible problem. Reports say significant rain in Atacama desert ([99] ,[100]) , which rounds to 15 mm instead of 5; CHIRPS isn’t really picking it up as it’s a very fine difference, but as that area is a desert area, that small increase in rainfall resulted in massive flooding and evacuation. CHIRPS showed significant precipitation inland of Concepcion, which agrees with rain and snow reports ([101]). Santiago: CHIRPS wet anomaly confirmed. Report ([102]) details increased rain, which is showing up in CHIRPS.
Uruguay: CHIRPS wet anomaly confirmed. CHIRPS recorded above average rainfall for Uruguay for August 2015. The rainfall throughout the country, according to CHPClim, tends to be between 60 and 90 mm; however, CHIRPS reported it ranging from 190 to 240 mm, with the south-eastern coast receiving between 300 and 340mm for the month. This increase in rainfall is backed up by reports, including one from “floodlist” ([103]).
Burkina Faso (added 9/23/15): Station near capital (Ouagadougou) flooded in August, but CHIRPS didn’t pick it up. However, CHIRPS did pick up the rest of the flooding in the country.
September 2015
Notes on Rchecks resources
Regarding the rchecks-2.files: Reminder - The zscores in rchecks-2.files are not station zscores. They are zscores of CHIRPS data that has been placed at that station's pixel. Using the zscores in these files is helpful for identifying extreme CHIRPS that are caused by extreme station values. Using the zscores is not helpful for identifying stations that do not have influence much on CHIRPS BUT give bad reports (had concerns about this for some stations in Ghana, see above). We discussed routinely isolating a value that indicates this, so that we know which stations have issues. Basically we would do a sorting of the country information based on this value, like we do with the zscores (check.txt). Something to look into more. Also, we corrected a bug that limited the number of recheck text files. Now should have all countries.
Contributors: Laura Harrison, Marty Landsfeld, Emily Williams; 9/17/15
July 2015
Ethiopia: July’s r-check had quite a few high z-scores. Upon analysis, these discrepancies were coming from the highlands, near Addis Ababa, and south of Addis Ababa.
Station (10.33, 37.74; in town of Debre Markos) reported much lower than CHIRP and CHPClim, in the same way it reported low for August 2015. Station (8.86, 39.92; in town of Metehara Merti, near Addis Ababa) also reported much lower than CHIRP and CHPClim. ARC2 tells a similar story; ARC2 dictates the area having received 200-300mm[104]. ARC2’s anomaly map for July also roughly matched CHIRPS’ anomaly map, at a decrease of around -200m of normal[105].
One report stated “July’s seasonal rains did not come this year…” , while another confirmed that "the rain condition was ok for the first ten days during the month of June. It gradually declined and we started experiencing shortage in rain in July. But conditions are good in August…it has occurred several times in the past, including in 2005.”. The July rains (that didn’t come this year) tend to climb north-east across the highlands throughout June, July and August, the area showing a shortage in rain. It seems the stations are correct and Ethiopia experienced a drought this summer. However, due to the decreased number of stations since August 2014, it is possible that these stations are overestimating the level of drought.
Sudan: CHIRPS and CHIRP both indicate that in southwest Sudan, June was had normal rainfall, July was dry, and August returned to normal rainfall (aka summer rains came late). The proximity of the area to the Ethiopian highlands means it followed similar trends as seen in Ethiopia, as backed up by previous reports. HOWEVER, CHIRPS completely missed mass flooding in Darfur in July[106]; for that same time of mass flooding, CHIRPS reported a decrease in rainfall.
Burkina Faso: We may have a faulty station (or stations) in northeast Burkina Faso. The two stations are located at (14.03, -0.033; stn 277004); one reported 482 mm of rain, CHIRP reported 129, and CHPClim 117; the other station seems to bring the number ranges from 0-10. These stations combined, though, are driving up the CHIRPS rainfall estimates.
One report does state that regular rain started mid-July [107]. However, most reports indicate that the northeastern area had decreased, not increased, rainfall in July [108]; NOAA/FEWS NET reports for July show dryness as well in the west and southwest [109] [110] [111] [112] [113].
Guatemala: CHIRPS is fairly accurately picking up a drought in Guatemala, but may be overestimating it in some areas. Station (-88.59, 15.74) has a high value (154) compared to CHIRP (104), and yet CHIRPS is drug down for that pixel (84). There is a neighboring station in Honduras that has an extremely low station value that is most likely over-influencing CHIRPS, creating exaggerated estimates of low rainfall for Guatemala. Reports confirm the drought's severity: TRMM (anomaly and time series) shows drought in the north and west of the nation (-100- -200), in concurrence with CHIRPS (-200- - 300), and written articles confirm the precip data [114] [115]. CHIRPS is picking up the drought around El Salvedor and in southern Honduras, but again might be overestimating the drought in Guatemala.
Flooding occurred in July in Chinaulta (southeast) ; CHIRP and TRMM both reported higher than average rainfall in that area, but CHIRPS reported higher rainfall only along the coast and drought in Chinaulta. The underestimation of precipitation by CHIRPS might again be the influence of the station in the north of Honduras. It seems that stations are having too high an influence, especially when they are all reporting the same phenomenon and are then influencing another with the opposite (ex//drought all around, but flooding in Chinaulta).
Honduras: see above
CHIRPS shows a more extreme drought in the West than CHIRP shows, but TRMM reports similarly, suggesting CHIRPS is accurately reporting the drought and CHIRP underestimated it[116].
Contributors: Emily Williams; 9/23/15 - 9/24/15
June 2015
Honduras: CHIRPS reported Honduras having experienced flooding around the capital and the northern Caribbean coast. The flooding in the center was backed up by reports. However CHIRP reporting higher rainfall than the stations. Mid-June, Hurricane Bill formed along Honduras's northern coast, which could account for the flooding. However, NOAA/FEWS does not report any flooding, and in fact reports dryness along the Southwest of the country.
Nicaragua: CHIRPS picked up some significant rainfall (anomaly of +30-50mm) along Western Nicaragua. It was confirmed that the flooding seen in CHIRPS is roughly the pattern of flooding experienced on the ground [117]. NOAA/FEWS did not pick up this flooding in their reports [118].
Costa Rica: Costa Rica similarly experienced significant flooding in much of the country, also missed by NOAA/FEWS. However, it was picked up by TRMM.
Ethiopia: CHIRPS reporting lower-than-average rainfall for Ethiopia's highlands, which seems to be in line with the summer's drought. Compared to ARC1 estimates, CHIRPS might be overestimating the drought at this point, but it is nonetheless present. NOAA/FEWS have not captured the severity and distribution, and even declared "no drought" in Ethiopia at the end of June [119].
Kenya: Flooding in Nairobi that CHIRPS didn't catch [120]. Other general trends in climate are echoed by ARC1 [121]. There is a station in the southeast of Kenya (in the town of Mombasa) which reported a higher-than-average value for CHIRPS, but a low station value; this same area was subject to flooding [122].
In May, flooding in Mombasa, picked up by CHIRPS [123].
Madagascar: CHIRPS reporting higher-than-average rainfall along Madagascar's eastern coastline.
Senegal: One station is reporting an abnormally low value (7mm) for June, when CHIRP puts it around 100mm. However, Arc2 shows a decline in rainfall for that area in June [124]. The station looks okay for other months; may be good to keep an eye on though.
Mali: Station reporting a low value (99) in an area that tends to get 127; CHIRPS is reporting 139 for this area. The area is on the slope of a mountain, though, and on a rain gradient, so it's likely that the station is correct.
Ghana: CHIRPS failed to pick up flooding in coastal town of Accra during "biggest storm in the past 20 years". The station failed to pick it up, which is probably why CHIRPS didn't get it (station said 154mm, while the report said 250 mm in only the first 3 days.
Contributors: Emily Williams; 9/28/15
May 2015
Guatemala: There is a station in the far east of Guatemala which is reporting a significantly high rainfall value, but CHIRPS is reporting a value closer to CHIRP and CHPClim. There is, however, a station very near in Honduras which has an extremely low value which could be over-influencing CHIRPS at our station's location.
TRMM total rainfall anomolyis reporting lower-than-average rainfall for that period of time, but then a positive anomaly for June which aligns with our station.
However, TRMM's total rainfall time series from station values agrees with our station that is reporting higher rain[125], and disagrees with the Honduras station.
Honduras: The most notable station this month has a value of 1 in the North West of the country. However, the country as a whole had an anomaly of 100-200mm, lining up with TRMM values. The station is in a valley surrounded by mountains so it might be correct in that it received no rainfall there, but is something to keep an eye on.
Tajikistan: CHIRPS to picked up flooding in the Khatlon province of Tajikistan [126].
Kenya: CHIRPS is showing a high quantity of rain along the southern coast and boarder of Kenya. The ARC2 time series points up this claim, in addition to the estimates. Additionally, the RFE anomaly backs up the claim of high rainfall in the south, and low in the northwest [127].
Tanzania: CHIRPS and ARC2 both show an high positive anomaly of rain in Tanzania in the SE [128]. The RFE for the end of the month shows a negative anomaly for the same area [129], but a positive anomaly for the beginning [130]. Reports of flooding back up this claim [131].
Uganda: CHIRPS shows dryness through much of the country except for a high incidence of rain in the south near the lake. RFE and ARC2 show similar trends. ARC2 time series shows both the dryness just north of the lake (in correspondence with the low station value) and then the wetness to the west of the lake [132]. CHIRPS is correct for May.
Madagascar: Dry station on east (central/north) coast; ARC2 time series shows same dryness [133]; ARC2 month shows the same [134]. However, CHIRPS showing a lot of wetness along the rest of the eastern coast, but not backed up by ARC2. It seems like the coastal stations have been overreporting rainfall for May-July. ARC2 timeseries and month-estimates, RFE, and reports [135] show less rainfall than CHIRPS.
Burkina Faso: Country received high rainfall in West according to RFE and ARC2 [136] [137]. Station in CHIRPS shows the same story; however CHIRP is showing dryness across the country. ARC May estimates agree there should be more rainfall in the West. Seems like this station is being drowned out by dry stations and should have a higher influence on the area to make it come up as wet instead of dry/average.
Mali: Station in south of country shows wet values but is also being drowned out by surrounding drought area, making the area look average instead of wet.
April 2015
Cote D'Ivoire and Ghana: CHIRPS is struggling again to pick up anomalous wet periods when surrounded by dry areas. There were stations reporting wet values surrounded by stations reporting dry values, and CHIRPS didn't allow for the high value to significantly impact the area around it; RFE [138] and ARC [139] both indicate wetness for the southern part of the country, which CHIRPS under-reports.
Eastern Africa: CHIRPS did a good job in picking up the significant wetness stretching along the Eastern coast of Africa. ARC and CHIRPS are in agreement, where RFE is reporting much drier conditions throughout Kenya and parts of Tanzania.
Kenya Kenya was fairly wet in August. RFE and ARC show wet conditions in northern and western Kenya, though drier conditions in southern and eastern Kenya. CHIRPS isn't picking up the dryness. All the z-scores that stood out, however, are for stations that reported lower rainfall values than CHIRPS shows. Seems CHIRPS isn't heeding local station signals enough and relies too strongly to influences of surrounding precipitation conditions.
Honduras: There is a station that received nearly zero rain in April, but this is backed up by the RFE time series points.
Dominican Republic: CHIRPS picked up that very little rain fell along the northern and eastern coasts of the Dominican Republic.
Tajikistan: CHIRPS shows lower-than-average rainfall in north along ridgeline, and higher-than-average rainfall in the western-central portion of the country. Stations are reporting higher values for rain than the weather records [140] (130 vs 71). Difficult to verify if CHIRPS is accurately reporting or not due to limited precipitation data to compare with. Would be good to have NOAA's RFE png blown up a bit to see better whether our results correlate [141].
Contributors : Emily Williams, 10/16/15