Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method——A Case Study of a Mesoscale Convective System  

作　　者：Ruhui GAN Yi YANG Qian XIE Erliang LINi Ying WANG Peng LIU 

机构地区：[1]Key Laboratory of Climate Resource Development and Disaster Prevention in Gansu Province,College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000 [2]Research Center for the Development of the Earth System Model of Lanzhou University,College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000 [3]School of Marine Science,Nanjing University of Information Science&Technology,Nanjing 210044

出　　处：《Journal of Meteorological Research》2021年第2期329-342,共14页气象学报（英文版）

基　　金：the National Key Research and Development Program of China (2017YFC1502102);National Natural Science Youth Fund of China (41905089)。

摘　　要：Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of nowcasting and short-term forecasting. Physical initialization combined with the three-dimensional variational data assimilation method(PI3 DVarrh) is used in this study to assimilate two kinds of observation data simultaneously, in which radar data are dominant and lightning data are introduced as constraint conditions. In this way, the advantages of dual observations are adopted. To verify the effect of assimilating radar and lightning data using the PI3 DVarrh method, a severe convective activity that occurred on 5 June 2009 is utilized, and five assimilation experiments are designed based on the Weather Research and Forecasting(WRF) model. The assimilation of radar and lightning data results in moister conditions below cloud top, where severe convection occurs;thus, wet forecasts are generated in this study.The results show that the control experiment has poor prediction accuracy. Radar data assimilation using the PI3 DVarrh method improves the location prediction of reflectivity and precipitation, especially in the last 3-h prediction, although the reflectivity and precipitation are notably overestimated. The introduction of lightning data effectively thins the radar data, reduces the overestimates in radar data assimilation, and results in better spatial pattern and intensity predictions. The predicted graupel mixing ratio is closer to the distribution of the observed lightning,which can provide more accurate lightning warning information.

关 键 词：radar data lightning data data assimilation physical initialization combined with the three-dimensional variational data assimilation method(PI3DVarrh) convection Weather Research and Forecasting(WRF) 

分 类 号：P427.3[天文地球—大气科学及气象学]