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《Meteorological Monthly》 2008-10
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Application of Classification and Integration to Rainfall Forecast

Cao Xiaozhong1 Min Jingjing2 Liu Huanzhu3 Zhao Shengrong3 Wang Shigong2 (1.Training Center,China Meteorological Administration,Beijing 100081; 2.Lanzhou University;3.National Meteorological Center)  
A method of forecasting rainfall based on numerical prediction products is presented.According to the idea of artificial intelligence classification and integration,numerical prediction products of T213,Japanese and German models are integrated together by using the Back-Propagation neural network,and it will contribute advantages of various means and form an integrated forecast system.On this basis,self-organizing neural network is used to classify the weather type according to the situation of height field and temperature and humidity on the surface layer in forecasting area.Then different forecast elements are selected and different forecast models are established for different weather types.Using the method mentioned above,the forecast model is built by using the data from May 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-Huaihe River basin.The result shows that the method is quite practicable.
【Fund】: 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
【CateGory Index】: P456.7
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