Summertime daily precipitation statistics over East China in CFSv2

• Published in: Physics and chemistry of the earth. Parts A/B/C 2020-02, Vol.115, p.102841, Article 102841
• Main Authors: Guo, Yan, Nie, Huiwen
• Format: Article
• Language: English
• Subjects: Bias correction; CFSv2; Daily precipitation statistics; Extreme precipitation
• ISSN: 1474-7065; 1873-5193
• DOI: 10.1016/j.pce.2020.102841

Abilities of Climate Forecast System version 2 (CFSv2) in predicting seasonal mean precipitation quantities have been demonstrated utility, but it did not address the questions related to the specific character of daily precipitation statistics, which are in high demand of final users. In this study, summertime daily precipitation statistics from the CFSv2 reforecasts were evaluated over East China. The daily precipitation statistics considered included the number of wet days, precipitation intensity (represented mean precipitation), and four extreme precipitation indices. Simulations of the climatological daily precipitation statistics by CFSv2 have been examined. The most significant bias in CFSv2 is that it produces excessive consecutive light and moderate precipitation but misses most short-duration heavy and extreme precipitation events over South and Northeast China, which further limits the simulation of precipitation intensity and precipitation extremes there. Some possible causes for model biases have been discussed. Direct application of CFSv2 in impact modelling studies is hampered by model biases. A simple bias correction of precipitation frequency was used to ensure better agreement with observation. After adjustment of the wet day threshold in CFSv2, simulation of number of wet days and extreme precipitation days were completely corrected. Moreover, simulation of precipitation intensity as well as four extreme precipitation indices all showed improvement. •CFSv2 produces excessive consecutive light and moderate precipitation over East China, especially over Southeast China.•CFSv2 misses most short-duration heavy and extreme precipitation events over Southeast and Northeast China.•Bias correction of precipitation frequency in CFSv2 improves its simulation of precipitation intensity and extremes.