卫星降水产品在陇东2022年7月特大暴雨事件中的适用性评估

Applicability evaluation of satellite-derived precipitation products in the torrential heavy rainfall event in East Gansu in July 2022

以地面雨量站观测数据、中国气象局多源融合降水数据(CMPAS)为基准,通过定量、分类、结构相似度3种方法综合评估8种卫星降水产品(FY-4A、CMOPRH-RT、IMERG-Early、IMERG-Late、GSMaP-Now、GSMaP-Gauge、PERSIANN-Now、PERSIANN-CCS)在甘肃陇东2022年7月一次破历史记录的极端性强降水过程中的适用性。结果表明:(1)8种卫星降水产品基本反映降水中东部大、西北小的空间分布特征,除GSMaP-Now产品外,其余7种产品均低估暴雨中心降水量。(2)8种卫星降水估算产品对于强降水峰值的描述能力较好,强降水过程的2个峰值阶段均有体现,但均严重低估大暴雨及以上量级降水。(3)GSMaP-Gauge对暴雨以下量级降水估算最优,而CMOPRH-RT对暴雨及以上量级降水估算最优,所有产品对特大暴雨量级降水均无法正确命中。(4)CMOPRH-RT产品能从降水总量、降水量级、形态分布三方面最好地表现降水过程的结构分布。对本次降水事件,CMOPRH-RT降水产品在各方面表现综合最优。

Based on the rainfall station observations and the products of Multi-source Merged Precipitation Analysis System of China Meteorological Administration(CMPAS),eight kinds of satellite-based precipitation products(FY-4A,CMOPRH-RT,IMERG-Early,IMERG-Late,GSMaP-Now,GSMaP-Gauge,PERSIANN-Now,PERSIANN-CCS)are comprehensively evaluated during the recordbreaking extremely heavy precipitation process in East Gansu on July 15,2022 by using quantitative analysis,classification and struc⁃tural similarity methods.The results show that eight kinds of satellite-based precipitation products basically reflect the spatial distribu⁃tion characteristics of precipitation with more in the central and eastern regions and less in the northwest.Except for the GSMaP-Now product,the other seven satellite-based precipitation products all underestimate the precipitation at the center of the rainstorm.The eight kinds of satellite-based precipitation products have a good ability to describe the peak value of heavy precipitation,and both peak stages of the heavy precipitation process are reflected,but all of them seriously underestimate the magnitude of heavy rainfall and above.For precipitation of different magnitudes,the GSMaP-Gauge is the best for estimating precipitation of magnitude below torrential rain,while the CMOPRH-RT is the best for heavy rain and above,and all products cannot correctly hit the precipitation of torrential heavy rainfall.In terms of the structural similarity index,the CMOPRH-RT product can best represent the structural distribution of the precipitation process from three aspects of total precipitation,precipitation magnitude,and precipitation morphological distribution.In summary,for this precipitation event,the CMOPRH-RT precipitation product had the best performance in all aspects.