Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis

The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs.