Application of a Three-dimensional Variational Method for Radar Reflectivity Data Correction in a Mudslide-inducing Rainstorm Simulation

作     者：Hongli LI Xiangde XU 

作者机构：State Key Laboratory of Severe WeatherChinese Academy of Meteorological SciencesBeijing 100081China Nanjing University of Information Science and TechnologyNanjing 210044China Hubei Key Laboratory for Heavy Rain Monitoring and Warning ResearchInstitute of Heavy RainChina Meteorological AdministrationWuhan 430205China 

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

年 卷 期：2017年第34卷第4期

页      面：469-481页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 08[工学] 0837[工学-安全科学与工程] 0706[理学-大气科学] 0816[工学-测绘科学与技术] 0825[工学-航空宇航科学与技术] 

基　　金：supported by a National Department of Public Benefit Research Foundation of China(Grant No.GYHY201406001) NSFC(National Science Foundation of China)project(Grant Nos.41105072,41130960,41375057and 41375041) Hubei Meteorological Bureau project(Grant No.2016S02) 

主　　题：cloud analysis Doppler radar data rainstorm LAPS 

摘      要：Various types of radars with different horizontal and vertical detection ranges are deployed in China, particularly over complex terrain where radar blind zones are common. In this study, a new variational method is developed to correct threedimensional radar reflectivity data based on hourly ground precipitation observations. The aim of this method is to improve the quality of observations of various types of radar and effectively assimilate operational Doppler radar observations. A mudslide-inducing local rainstorm is simulated by the WRF model with assimilation of radar reflectivity and radial velocity data using LAPS（Local Analysis and Prediction System）. Experiments with different radar data assimilated by LAPS are performed. It is found that when radar reflectivity data are corrected using this variational method and assimilated by LAPS,the atmospheric conditions and cloud physics processes are reasonably described. The temporal evolution of radar reflectivity corrected by the variational method corresponds well to observed rainfall. It can better describe the cloud water distribution over the rainfall area and improve the cloud water analysis results over the central rainfall region. The LAPS cloud analysis system can update cloud microphysical variables and represent the hydrometeors associated with strong convective activities over the rainfall area well. Model performance is improved and the simulation of the dynamical processes and moisture transport is more consistent with observation.