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基于T213物理量产品的闽北冰雹客观预报方法
引用本文:张信华,马昌明,朱艳萍,叶福銮,胡旭美.基于T213物理量产品的闽北冰雹客观预报方法[J].气象科技,2012,40(3):406-410.
作者姓名:张信华  马昌明  朱艳萍  叶福銮  胡旭美
作者单位:1. 福建省武夷山市气象局,武夷山,354300
2. 福建省气象台,福州,350001
摘    要:利用2003—2005年闽北冰雹出现站数与实况物理量求相关,得到与闽北不同季节(春季3—4月、汛期5—6月)降雹相关密切的物理量因子。利用T213数值预报物理量产品与福建省多年预报经验总结的实况物理量产品相结合,运用指标叠加法来建立闽北不同季节(春季3—4月、汛期5—6月)冰雹客观预报系统,该系统在2008—2010年近3年的应用中,取得了很好的效果:3年中未出现冰雹漏报,且该模式运用独具特色的消空条件后,空报率也较低。

关 键 词:物理量  冰雹  客观预报
收稿时间:2010/11/24 0:00:00
修稿时间:5/3/2011 12:00:00 AM

An Objective Forecasting Method of Hail Weather Based on T213 Physical Element Products in Northern Fujian
Zhang Xinhu,Ma Changming,Zhu Yanping,Ye fuluan and Hu xumei.An Objective Forecasting Method of Hail Weather Based on T213 Physical Element Products in Northern Fujian[J].Meteorological Science and Technology,2012,40(3):406-410.
Authors:Zhang Xinhu  Ma Changming  Zhu Yanping  Ye fuluan and Hu xumei
Institution:Wuyishan Meteorological Service, Fujian, Wuyishan 354300;Fujian Meteorological Observatory, Fuzhou 350001;Fujian Meteorological Observatory, Fuzhou 350001;Wuyishan Meteorological Service, Fujian, Wuyishan 354300;Wuyishan Meteorological Service, Fujian, Wuyishan 354300
Abstract:Based on the relevance between the number of the stations where had a hail weather in the northern Fujian and the physical element fields from 2003 to 2005, the physical factors closely related to hail weather in different seasons (March to April in spring, and May to June in flood season) in the northern Fujian are identified. In combination with the numerical physical element forecast products of T213 and the actual physical element products summarized from the practical forecast experiences of several years in Fujian, the objective forecasting system of hail weather for different seasons in the northern Fujian is established by using the index superposition method. This system achieved good result in operation from 2008 to 2010, in which there was no missing alarm and very low false alarm rate after using the unique elimination conditions in the model.
Keywords:T213 product  hail  objective forecasting
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