Improvement of an Extreme Heavy Rainfall Simulation Using Nudging Assimilation  

作　　者：Taichen FENG Zhiyuan HU Shankai TANG Jianping HUANG 

机构地区：[1]Key Laboratory for Semi-Arid Climate Change of the Ministry of Education,College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000 [2]School of Atmospheric Sciences,Sun Yat-sen University,and Key Laboratory of Tropical Atmosphere-Ocean System of Ministry of Education,Zhuhai 519082

出　　处：《Journal of Meteorological Research》2021年第2期313-328,共16页气象学报（英文版）

基　　金：the National Natural Science Foundation of China (41521004, 41905013, and 41975088);Strategic Priority Research Program of Chinese Academy of Sciences (XDA2006010301);China University Research Talents Recruitment Program [111Project (B13045)]。

摘　　要：From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging(GN) and spectral nudging(SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting(WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface(NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes,and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.

关 键 词：extreme heavy precipitation grid nudging(GN) Weather Research and Forecasting(WRF)model 

分 类 号：P426.62[天文地球—大气科学及气象学]