Evaluation of three global gridded precipitation data sets in central Asia based on rain gauge observations

• The accuracies of gridded precipitation data sets are important for regional climate studies and hydrological models. In this study, the performances of Global Precipitation Climatology Centre (GPCC) V7, Climatic Research Unit (CRU) TS 3.22 and Willmott and Matsuura (WM) precipitation data sets were examined over central Asia by comparing them against observed precipitation records (OBS) from 586 meteorological stations during 1901-2010. The results show that all the three gridded data sets underestimated the observed precipitation at annual and monthly scales, especially in mountainous areas. Both GPCC and WM underestimated seasonal precipitation, especially for spring precipitation. Among the three gridded data sets, GPCC had the highest correlation and lowest bias compared with CRU and WM when against the OBS. WM had a higher correlation than that of CRU, and its bias was larger than that of CRU. In terms of the drought and heavy rainfall events, CRU had the best performance in capturing drought events, and GPCC was best at representing heavy rainfall events. These differences in the performances between the three gridded data sets were primarily induced by their different interpolation methods and the numbers of available meteorological stations used in the interpolations of the three gridded data sets. Therefore, compared to the other two data sets, GPCC is more suitable for studies of long-term precipitation variations over central Asia.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Meteorologi och atmosfärforskning (hsv//swe)

NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Meteorology and Atmospheric Sciences (hsv//eng)

Nyckelord

central Asia

evaluation

gridded precipitation data set

rain gauge observation

land-surface precipitation

air-temperature

satellite

products

topography

reanalysis

resolution

climate

region

error

Meteorology & Atmospheric Sciences

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