A Heavy Rainfall Event in Autumn over Beijing-Atmospheric Circulation Background and Hindcast Simulation Using WRF

被引:7
|
作者
Li, Xiangrui [1 ,2 ]
Fan, Ke [1 ,2 ,3 ]
Yu, Entao [1 ,3 ,4 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, Nansen Zhu Int Res Ctr, Beijing 100029, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Jiangsu, Peoples R China
[4] Chengdu Univ Informat Technol, Joint Lab Climate & Environm Change, Chengdu 610225, Sichuan, Peoples R China
关键词
heavy rainfall; WRF model; water vapor supply; autumn; Beijing area; EXTREME RAINFALL; JULY; 2012; SNOW; PARAMETERIZATION; FORECASTS; IMPACT; CHINA;
D O I
10.1007/s13351-018-7168-9
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Heavy rainfall events often occur in Beijing during summer but rarely in autumn. However, during 3-5 September 2015, an exceptionally heavy rainfall event occurred in Beijing. Based on the reanalysis data and the Weather Research and Forecasting (WRF) model simulations, the main contributing factors and the predictability of this heavy rainfall event were examined through comprehensive analyses of vorticity advection and water vapor transport/ budget. The results indicate that a "high-in-the-east-low-in-the-west" pattern of 500-hPa geopotential height over the Beijing area played an important role. The 850-hPa low-level jet (LLJ) provided a mechanism for rising motion and transported abundant water vapor into the Beijing area. Two-way nested hindcast experiments using WRF well reproduced the atmospheric circulation and LLJ. Quantitative analysis indicates that the WRF model with the rapid update cycle (RUC) land surface scheme and the single-moment 6-class (WSM6) microphysics scheme exhibited the best skill, and the model performance improved with a higher resolution. Further analysis indicates that the bias in the precipitation forecast was caused by the bias in water vapor transport.
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页码:503 / 515
页数:13
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