Diagnosis of Moist Vorticity and Moist Divergence for a Heavy Precipitation Event in Southwestern China

作     者：Gang LI Daoyong YANG Xiaohua JIANG Jing PAN Yanke TAN 

作者机构：Xichang Satellite Launch CenterXichang 615000China State key Laboratory at Numerical Modelling for Atmospheric Sciences and Geophysical Fluid DynamicsInstitute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Meteorology and OceanographyPLA University of Science and TechnologyNanjing 211101China 

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1期

页      面：88-100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：jointly supported by the National Department Public Benefit Research Foundation(Grant No.GYHY201406003) the 973 Program(Grant Nos.2013CB956203 and 2012CB957803) the National Natural Science Foundation of China(Grant Nos.41490642,41475070 and 41305045) the Jiangsu Natural Science Foundation(Grant No.BK20151447) 

主　　题：moist vorticity moist divergence heavy precipitation southwestern China 

摘      要：A regional heavy precipitation event that occurred over Sichuan Province on 8-9 September 2015 is analyzed based on hourly observed precipitation data obtained from weather stations and NCEP FNL data. Two moist dynamic parameters, i.e., moist vorticity （mζ and moist divergence （mδ）, are used to diagnose this heavy precipitation event. Results show that the topography over southwestern China has a significant impact on the ability of these two parameters to diagnose precipitation. When the impact of topography is weak （i.e., low altitude）, rn（ cannot exactly depict the location of precipitation in the initial stage of the event. Then, as the precipitation develops, its ability to depict the location improves significantly. In particular, m（ coincides best with the location of precipitation during the peak stage of the event. Besides, the evolution of the m（ center shows high consistency with the evolution of the precipitation center. For mδ, although some false-alarm regions are apparent, it reflects the location of precipitation almost entirely during the precipitation event. However, the mδ center shows inconsistency with the precipitation center. These results suggest that both m（ and mδ have a significant ability to predict the location of precipitation. Moreover, m（ has a stronger ability than mδ in terms of predicting the variability of the precipitation center. However, when the impact of topography is strong （i.e., high altitude）, both of these two moist dynamic parameters are unable to depict the location and center of precipitation during the entire precipitation event, suggesting their weak ability to predict precipitation over complex topography.