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投稿时间：2008-03-04 修订日期：2008-03-17
投稿时间：2008-03-04 修订日期：2008-03-17
中文摘要: 介绍一种利用数值预报产品进行降雨预报的方法。该方法按照人工智能分类与集成的思想，
利用前馈神经网络将T213、日本、德国的数值预报产品集成在一起，构成一个集成型的预报
系统。在此基础上，利用高度场的天气形势和预报区域近低层流场和温湿条件，采用自组织
神经网络进行天气分型，并针对不同的天气类型选用不同的预报因子，建立不同的预报模型
。按照上述方法，选用江淮流域68个站点2003—2005年的5—9月数据，逐站建模，用2006
—
2007年5—9月的数据进行分级降水试报。各级降水预报结果表明，集成多家数值预报信息好
于仅用单一模式的信息，采用天气分型建模优于不分型的建模。因此，多模式（型）预报结
果的综合集成方法的研究，是数值预报解释应用中很值得探索的方向。
Abstract:A method of forecasting rainfall based on numerical prediction products is prese
nted. According to the idea of artificial intelligence classification and integr
ation, numerical prediction products of T213, Japanese and German models are int
egrated together by using the Back Propagation neural network, and it will cont
ribute advantages of various means and form an integrated forecast system. On th
is basis, self organizing neural network is used to classify the weather type a
ccording to the situation of height field and temperature and humidity on the su
rface layer in forecasting area. Then different forecast elements are selected a
nd different forecast models are established for different weather types. Using
the method mentioned above, the forecast model is built by using the data from M
ay to September in 2003 to 2005, and is tested by forecasting rain
fall from May to September in 2006 to 2007 at 68 stations in the Changjiang Hua
ihe River basin. The result shows that the method is quite practicable.
文章编号： 中图分类号： 文献标志码：
基金项目:本文得到中国气象局重点课题：“天气要素精细预报业务系统建设与改进”的资助
引用文本：
曹晓钟,闵晶晶,刘还珠,赵声蓉,王式功,2008.分类与集成方法在降雨预报中的应用[J].气象,34(10):3-11.
Cao Xiaozhong,Min Jingjing,Liu Huanzhu,Zhao Shengrong,Wang Shigong,2008.Application of Classification and Integration to Rainfall Forecast [J].Meteor Mon,34(10):3-11.
曹晓钟,闵晶晶,刘还珠,赵声蓉,王式功,2008.分类与集成方法在降雨预报中的应用[J].气象,34(10):3-11.
Cao Xiaozhong,Min Jingjing,Liu Huanzhu,Zhao Shengrong,Wang Shigong,2008.Application of Classification and Integration to Rainfall Forecast [J].Meteor Mon,34(10):3-11.