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《Acta Meteorologica Sinica》 2001-06
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THE STUDY ON APPLYING NEURAL NETWORK MODELS TO PREDICTION OF SUMMER PRECIPITATION IN HUBEI PROVINCE

Hu Jianglin(Wuhan Heavy Rain Institute,Wuhan 430074) Zhang Liping (Wuhan Central Weather Service,Wuhan 430074) Yu Rucong (LASG,Institute of Atmospheric,Chinese Academy of Sciences,Beijing 100029)  
The authors constructed artificial neural network (ANN) models of short-term climate forecasting to predict summer (June-August) precipitation in Hubei Province. The inputs of the model were the extended empirical orthogonal functions (EEOF) of the 500 hPa height field,the sea level pressure field in the Northern Hemisphere and sea surface temperature field over the Pacific before summer flood season (February-April), and the outputs were the empirical orthogonal functions of the summer precipitation totals of representative stations. The cross-validation over 41 years has shown that the forecasting skill score of ANN models is 0.246. Though the forecasting skills year by year are still unstable, positive skills exist obviously statistically for summer precipitation forecasting in Hubei Province.
【Fund】: 中国科学院大气物理研究所 LASG实验室提供资助
【CateGory Index】: P456
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