改进的雷达资料同化方案在梅雨期暴雨预报中的应用  

Application of an Improved Radar Data Assimilation Scheme in Heavy Rain Forecast in Meiyu Period

作　　者：彭菊香[1] 谢元富 康兆萍 李红莉[1] PENG Juxiang;XIE Yuanfu;KANG Zhaoping;LI Hongli(Hubei Key laboratory for Heavy Rain Monitoring and Warning Research,Institute of Heavy Rain,China Meteorological Administration,Wuhan 430205,Hubei,China;Chinese Academy of Meteorological Sciences,Beijing 100081,China)

机构地区：[1]中国气象局武汉暴雨研究所暴雨监测预警湖北省重点实验室,湖北武汉430205 [2]中国气象科学研究院灾害天气国家重点实验室,北京100081

出　　处：《高原气象》2020年第5期1007-1022,共16页Plateau Meteorology

基　　金：政府间国际科技创新合作重点专项(2016YFE0109400);国家自然科学基金项目(41620104009)。

摘　　要：雷达资料同化对提高数值天气预报准确率具有重要意义。针对2016年7月5-6日武汉一次梅雨期暴雨过程,采用改进的雷达资料同化方案STMAS(Space and Time Multiscale Analysis System)同化雷达径向速度和反射率因子。通过与LAPS(Local Analysis and Prediction System)方案的结果对比初始动力场、水汽条件、热力场、预报天气形势、降水和雷达回波等的差异,并着重分析了STMAS方案对初始场及降水预报的改进及其原因。结果表明:(1)同化雷达径向速度时,STMAS方案在三维变分基础上引入连续方程做强约束条件,对初始场中动力场改善效果较为明显。(2)同化雷达反射率因子时,STMAS方案增加利用雷达回波直接调整湿度步骤,强迫雷达回波高于阈值区域饱和,使得初始场的水汽条件更加充沛,对流不稳定能量更大。(3)由于STMAS方案初始场的改善,使得预报场中高低空天气系统配置较好,最终使得预报的雨带和强降水落区在位置和强度上更接近实况,其中100 mm以上强降水预报能力尤为突出。The radar data assimilation is practical for enhancingthe accuracy of numerical weather prediction in precipitation,yet few systems have correct and practical results.This research used a Space and Time Multiscale Analysis System(STMAS)in assimilating radar radical velocity and reflectivity factor,to compare with the previous Local Analysis and Prediction System(LAPS)results in the initial wind field,water vapor condition,weather prediction,precipitation,and radar reflection.The case study in the Mei-Yu event,in Wuhan on 5 July 2016,showed that the STMAS method provides a better initial condition in the wind field,water vapor condition and hence improved precipitation prediction.First,when assimilating the radar radical wind velocity,STMAS added the continuity equation as a strong constraint,which significantly improves the dynamic field in the initial condition.Second of all,STMAS saturated the water vapor when assimilating the radar reflection higher than the threshold,which provided more water vapor to the initial condition.This process can increase the instability,and trigger the convection.The last and the most important part is that,since the STMAS method helped to improve the initial condition,the patterns of the high altitude in the forecast is more realistic,which lower the bias of the prediction of precipitation in location and strength,especially in the prediction of the strong event which is larger than 100 mm.

关 键 词：雷达资料同化 STMAS同化系统 梅雨期暴雨 

分 类 号：P456.7[天文地球—大气科学及气象学]