Difference between revisions of "CHIRPS Reality Checks"

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'''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]).
 
''Italic text''Contributors: Laura Harrison, Marty Landsfeld, Emily Williams; 9/17/15''Italic text''
 
  
 
====Notes on Rchecks resources====
 
====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.
 
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.

Revision as of 10:40, 23 September 2015

CHIRPS v2.0 monthly Reality Checks

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. Rchecks country highlights has information that CHIRPS users may find helpful, for example, notes about major rainfall anomalies in the data. Notes on Rchecks resources is information for CHG to continually improve the Reality Checks process. 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.


August 2015

Rchecks country highlights

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 ([1],[2]) . 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. [3]

South Korea CHIRPS dry anomaly confirmed. Stations show low August rainfall (verified by news reports), which has created an overall poor season there [4]. 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 ([5]), 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 ([6] ,[7]) , 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 ([8]). Santiago: CHIRPS wet anomaly confirmed. Report ([9]) 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” ([10]).

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.