Evaluation of All-Sky Assimilation of FY-3C/MWHS-2 on Mei-yu Precipitation Forecasts over the Yangtze-Huaihe River Basin

作     者：Yu LI Keyi CHEN Zhipeng XIAN Yu LI;Keyi CHEN;Zhipeng XIAN

作者机构：School of Atmospheric SciencesChengdu University of Information TechnologyChengdu 610025China International Center for Climate and Environment SciencesInstitute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of SciencesBeijing 100049China 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2021年第38卷第8期

页      面：1397-1414页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：the National Natural Science Funds of China(Grant No.41875039) the Fengyun-3 meteorological satellite ground application system project the development of the application software for southwest regional road traffic using the Fengyun-3 satellite remote sensing monitoring service(Grant No.ZQC-J19193)are also appreciated to support this research 

主　　题：all-sky assimilation FY-3C MWHS-2 mei-yu rainfall 

摘      要：All-sky (i.e., clear, cloudy, and precipitating conditions) assimilation of microwave observations shows potentially positive impacts on the improvement of the forecasts of cloud-associated weather processes. In this study, a typical mei-yu heavy precipitation event that occurred in 2017 was investigated, and the Weather Research and Forecasting data assimilation (WRFDA) as well as its 3D-Var assimilation scheme (excluding cloud and precipitation control variables) were applied to assimilate the Fengyun-3C (FY-3C) Microwave Humidity Sounder-2 (MWHS-2) observations under clear- sky (excluding the observations that are strongly affected by ice clouds and precipitation) and all-sky conditions. Three experiments including a control experiment without assimilating any observations, clear-sky, and all-sky experiments with only FY-3C/MWHS-2 observations assimilated were carried out. The results show that the all-sky assimilation approach that provides more cloud and precipitation information and increased more than 10% of the satellite data usage than the clear-sky experiment. Meanwhile, as compared with the control experiment, the all-sky assimilation reduced nearly 0.5% of the root mean square errors in the humidity fields, leading to more accurate forecast performances regarding the distribution and intensity of heavy rainfall;but it exhibited a neutral to negative impacts on the wind and temperature. Although the system used to conduct all-sky assimilation is only able to adjust control variables for moisture-, wind-, and temperature- related variables in the presence of cloud and does not benefit directly from cloud or precipitation information, the positive effects on heavy rainfall forecasts achieved in this study indicate a potential future benefit regarding disaster prevention and mitigation.