气象学报（英文版）2022，Vol.36Issue(5)：798-808,中插28-中插40,24.
高分辨率卫星对"21·7"河南特大暴雨监测能力分析
Assessing 10 Satellite Precipitation Products in Capturing the July 2021 Extreme Heavy Rain in Henan, China
摘要
Abstract
On 20 July 2021, a sudden rainstorm happened in central and northern Henan Province, China, killing at least 302 people. This extreme precipitation event incurred substantial socioeconomic impacts and resulted in serious losses. Accurate monitoring of such rainstorm events is crucial. In this study, qualitative and quantitative methods are used to comprehensively evaluate the abilities of 10 high-resolution satellite precipitation products [CMORPH-Raw (Cli- mate Prediction Center morphing technique), CMORPH-RT, PERSIANN-CCS (Precipitation Estimation from Re- motely Sensed Information Using Artificial Neural Networks), GPM IMERG-Early (Integrated Multisatellite Re- trievals for Global Precipitation Measurement), GPM IMERG-Late, GSMaP-Now (Global Satellite Mapping of Pre- cipitation), GSMaP-NRT, FY-2F, FY-2G, and FY-2H] in capturing this extreme rainstorm event, as well as their per- formances in monitoring different precipitation intensities. The results show that these satellite precipitation products are able to capture the spatial distributions of the rainstorm (e.g., its location in central and northern Henan), but all products have underestimated the amount of precipitation in the rainstorm center. With the increase in precipitation intensity, the hit rate decreases, the threat score decreases, and the false alarm rate increases. CMORPH-RT is better at capturing the rainstorm than CMORPH-Raw, and it depictes the rainstorm process well; GPM IMERG-Late is more accurate than GPM IMERG-Early; GSMaP-NRT has performed better than GSMaP-Now; and PERSIANN- CCS and FY-2F perform poorly. Among the products, CMORPH-RT performs the best, which has accurately cap- tured the center of the rainstorm, and is also the closest to the station-based observations. In general, the satellite pre- cipitation products that integrate infrared and passive microwave data are found to be better than those that only make use of infrared data. The satellite precipitation retrieval algorithm and the amount of passive microwave data have a relatively greater impact on the accuracy of satellite precipitation products.关键词
河南暴雨/CMORPH/FY/GPM/PERSIANNKey words
heavy rain/CMORPH (Climate Prediction Center morphing technique)/FY (Fengyun)/GPM (Global Precipitation Measurement)/PERSIANN (Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks)分类
天文与地球科学引用本文复制引用
刘松楠,汪君,王会军..高分辨率卫星对"21·7"河南特大暴雨监测能力分析[J].气象学报（英文版）,2022,36(5):798-808,中插28-中插40,24.基金项目
Supported by the National Natural Science Foundation of China(41991283 and 42175170).国家自然科学基金项目(41991283和42175170). （41991283 and 42175170）
