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《Meteorology and Disaster Reduction Research》 2007-02
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Nonlinear Distribution Characteristics of Summer Precipitation Anomalies over China

JU Li-li,GUO Pin-wen,XU Tong(Jiangsu Key Laboratory of Meteorological Disaster,NUIST,Nanjing 210044,China)  
Nonlinear distribution characteristics of the precipitation anomalies over China during the last five decades were investigated by applying a feed-forward neural-network-based nonlinear principal component analysis(NLPCA) method to the rainfall anomalies data for summer.The results show that the summer precipitation anomalies has certain extent nonlinearity.The space distribution pattern according to the leading NLPCA mode assimilation manifest obvious asymmetry corresponds to the maximum and minimum nonlinear principal component value.The leading NLPCA mode assimilation is more realistic to the original precipitation anomalies data than that of the leading PCA mode assimilation.
【Fund】: 江苏省“六大人才高峰”项目资助
【CateGory Index】: P426.613
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