Presentation - Copernicus.org

Comparative statistical evaluation
of the global daily precipitation data set FDD
at GPCC using ETCCDI Climate Indices
Kristin Raykova, Elke Rustemeier, Markus Ziese, Kirstin Schamm, Anja Meyer-Christoffer, Udo Schneider, Peter Finger, Bodo Ahrens, Andreas Becker
Motivation
Climate variability and potential climate changes in the last three decades
couple of months during the hurricane seasons. Very high precipitation is
measured also on the West Coast of Canada and the US, due to
(1988-2013), along with their effects on climate and weather extremes, are
orographic effects and large-scale atmospheric circulation patterns.
investigated on the basis of the new global gridded daily precipitation data
set Full Data Daily (FDD) by the Global Precipitation Climatology Centre Highest values are established for Peru for RX1day (536 mm/day), Taiwan
for RX5day (1238 mm/(5days)) and Colombia for the number of days with
(GPCC). The extremes are analysed using the precipitation related ETCCDI
greater precipitation than the 95-th percentile (28 days). The maximum
Climate Change Indices which are calculated on an yearly base.
Moreover, comparison of FDD is taken with the global dataset CMORPH
number of days with more than 10 mm precipitation (R10) is found also in
Colombia (~213 days). In Europe falls averagely between 3 mm and 6 mm
over land by NOAA`s Climate Prediction Center (CPC).
Measurements in FDD are gathered only from rain gauges. The data are
precipitation on a wet day (SDII).
In the Atacama Desert and the Sahara are measured the longest dry
gridded on a regular global grid with spatial resolution of 1° x 1° (-180° to
periods with almost 8 years and at least 26 years (see CDD), respectively.
180° longitude and -90° to 90° latitude).
CMORPH combines bias corrected precipitation estimates from low orbiter The ETCCDIs are calculated for a reference period of 16 years for both
satellite microwave observations and geostationary satellite IR data with land FDD and CMORPH and then the difference is taken (here shown only for
RX5day, R10 and R95p[mm] – third row). The biggest differences are
station data from rain gauges. The spatial resolution has been reduced from
found to be in northern South America (Bolivia, Peru, Ecuador, Colombia,
0.25 to 1° by 1° allowing inter-comparison with FDD.
Venezuela) and in the Tropics of Africa (see middle plot on 3rd-row).
Results
Regarding the calculation of the maximal 5-day precipitation sums, the two
Greatest precipitation amounts are measured along the ITCZ (Colombia
and Venezuela, Middle West Africa, Oceania etc.) and especially in countries datasets exhibit more inconsistency.

Further work focus on examining the temporal evolution of yearly
mainly influenced by the monsoon seasons (West Africa, West India, East
development of the ETCCDIs between 1988 and 2013.
China etc.). The Gulf of Mexico is characterized by strong precipitation for a
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CPC`s CMORPH Version 1..0: ftp://ftp.cpc.ncep.noaa.gov/precip/CMORPH_V1.0/.
K. Schamm, M. Ziese, A. Becker, P. Finger, A. Meyer-Christoffer, U. Schneider, M. Schröder und P. Stender, „Global gridded precipitation over land: a description of the new GPCC First Guess Daily product“, Earth System Science Data 6, 49–60 (2014).
K. Schamm, M. Ziese, K. Raykova, A. Becker, P. Finger, A. Meyer-Christoffer und U. Schneider, GPCC Full Data Daily Version 1.0 at 1.0°: Daily Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data, (2015)
ftp://ftp.dwd.de/pub/data/gpcc/html/fulldata-daily_v1_doi_download.html.
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U. Schneider, A. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese und B. Rudolf, „GPCC‘s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle“, Theor. Appl. Climatol. 115, 15–40 (2014).
Visualize and Download GPCC Products: ftp://ftp-anon.dwd.de/pub/data/gpcc/html/download_gate.html.
X. Zhang, L. Alexander, G. C. Hegerl, P. Jones, A. K. Tank, T. C. Peterson, B. Trewin und F. W. Zwiers, „Indices for monitoring changes in extremes based on daily temperature and precipitation data“, WIREs Climate Change 2, 851–870 (2011).
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