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Evaluation of extreme precipitation based on satellite retrievals over China

Huang, Xuerongzi, Wang, Dashan, Liu, Yu, Feng, Zhizhou, Wang, Dagang
Frontiers of earth science 2018 v.12 no.4 pp. 846-861
probability distribution, rain, satellites, summer, time series analysis, winter, China
The objective of this study is to evaluate satellite precipitation extremes of the Tropical Rainfall Measuring Mission (TRMM) 3B42 Version 7 product over China during the period of 2009–2013. Eight extreme indices are used to characterize precipitation extremes: monthly maximum 1-day precipitation (RX1day), monthly maximum consecutive 2-day precipitation (RX2day), monthly maximum 5-day consecutive precipitation (RX5day), simple daily intensity index (SDII), annual total precipitation amount for the wet days (PRCPTOT), annual wet days (R1), consecutive dry days (CDD), and consecutive wet days (CWD). The precipitation amount for indices RX1day, RX2day, RX5day, and PRCPTOT is well captured by TRMM 3B42-V7, as verified by lower mean relative bias and normalized root mean square error and the high spatial correlation coefficient. In contrast, the performance of TRMM 3B42-V7 in depicting the indices on intensity and duration (i.e., SDII, R1, CDD, and CWD) is not as good as its performance in depicting the precipitation amount indices. TRMM 3B42-V7 can reproduce extreme indices better in eastern China than in western China, and better in summer than in winter. Probability density function is also calculated better for RX1day, RX2day, RX5day, and PRCPTOT than for SDII, R1, CDD, and CWD. Investigation on the monthly time series of RX1day, RX2day, and RX5day at different spatial scales indicates that TRMM 3B42-V7 performs better at the large spatial scale than at the grid cell scale. Caution should be observed when the satellite-based extreme indices are used.