Improving the regional model forecasting of persistent severe rainfall over the Yangtze River Valley using the spectral nudging and update cycle methods: a case study

被引：5
作者：
Zhao, Yanfeng [1 ,2 ,3 ]
Wang, Donghai [1 ,4 ]
Xu, Jianjun [5 ]
机构：
[1] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Coll Atmospher Sci, Nanjing, Jiangsu, Peoples R China
[3] George Mason Univ, Global Environm & Nat Resources Inst GENRI, Coll Sci, Fairfax, VA USA
[4] Sun Yat Sen Univ, Sch Atmospher Sci, Guangdong Prov Key Lab Climate Change & Nat Disas, Guangzhou, Guangdong, Peoples R China
[5] Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang, Peoples R China
来源：
ATMOSPHERIC SCIENCE LETTERS | 2017年 / 18卷 / 02期
基金：
中国国家自然科学基金;
关键词：
persistent severe rainfall; precipitation forecasting; spectral nudging; update cycle; EXTREME PRECIPITATION; CHINA; WEATHER; PARAMETERIZATION; PREDICTABILITY; SIMULATION; RESOLUTION; EVENTS; SYSTEM; SCHEME;
D O I：
10.1002/asl.731
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
China's worst flooding since 1998 occurred over the Yangtze River Valley from 30 June to 6 July 2016. This study investigated the event using a new method-the spectral nudging and update cycle (SN+UIC)-in the regional Weather Research and Forecasting model, fuller use of small-scale features by using multi-scale blending. The SN+UIC was found to be successful in improving the prediction of this persistent severe rainfall event; and the larger the magnitude and longer the lead time, the more obvious the improvement. It was also found that the use of this new method decreased the root-mean-square error for related meteorological variables.
引用
收藏
页码：96 / 102
页数：7
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