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2010年7月14~18日四川大暴雨过程区域模式预报性能分析
引用本文:何光碧,屠妮妮,张利红,卢萍,肖玉华.2010年7月14~18日四川大暴雨过程区域模式预报性能分析[J].高原山地气象研究,2010,30(4):8-17.
作者姓名:何光碧  屠妮妮  张利红  卢萍  肖玉华
作者单位:1. 中国气象局成都高原气象研究所, 成都 610072;
基金项目:西南区域重大科研项目,2010年行业专项
摘    要:本文应用高空与地面常规观测资料,自动站资料以及2010年西南涡科学观测试验资料等,就西南区域气象中心运行的GRAPES模式、AREM模式、MM5模式以及基于WRF模式的RUC系统对发生在2010年7月14~18日四川大暴雨过程预报情况进行分析。结果表明,从降水预报,到影响系统,以及单点地面、高空要素预报,尽管各区域模式表现出对此大暴雨过程有一定的预报能力,但存在着不同程度差异,如降水落区、降水强度偏差,影响系统的偏离等。当分析模式定点预报时,预报偏差更为明显。相对而言,WRF模式预报结果略好于其它模式的预报。造成模式预报偏差的原因还有待作进一步分析研究。 

关 键 词:大暴雨    数值模式    预报性能
收稿时间:2010-09-02

Prediction Capability Analysis of Limited-area Numeric Models on Sichuan Heavy Rainstorm Process in Sichuan
HE Guangbi,TU Nini,ZHANG Lihong,LU Ping,XIAO Yuhua.Prediction Capability Analysis of Limited-area Numeric Models on Sichuan Heavy Rainstorm Process in Sichuan[J].Plateau and Mountain Meteorology Research,2010,30(4):8-17.
Authors:HE Guangbi  TU Nini  ZHANG Lihong  LU Ping  XIAO Yuhua
Institution:1. Institute of Plateau Meteorology, CMA, Chengdu, 610072;2. Sichuan Meteorological Observatory, Chengdu, 610072
Abstract:By using upper-air and surface observation data, automatic station data, as well as observatory data of south-west vortex atmospheric science test in 2010, the prediction capability analyses on SiChuan heavy rainstorm process during 14-18 July in 2010 have been done for GRAPES model, AREM model, MM5 model and RUC system based on WRF model which run in South-West Region Meteorology Center.The results show that although all models have a certain degree prediction capability from precipitation, affecting systems, as well as surface and upper-air meteorological elements prediction on single point, there are differences such as precipitation areas, precipitation intensity, affecting systems prediction and so on.When analyzing the prediction of models on definite point, the difference is more obvious.Comparatively, the prediction result of WRF mode is better than that provided by the other models.The further cause analyses on bring about model prediction differences should been done 
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