氣候場的主分量逐步回歸預測模型及應用

A prediction model has been presented of principal component stepwise regression of the climate field.The model changes the prediction of the climate field to that of the principal component of that field.From the 500 hPa height and the sea surface temperature of Pacific and Indian ocean and the sea-level pressure of global in various seasons and regions,excellent principal component factors have been extracted with high information content and important influence on the climate field.Through correlation screening and double test stepwise regression,a prediction equation is developed for the principal component of the climate field,and the relation of the climate field with multiple fields of factors has been established.But the model keeps the correlation between the two element fields.According to the approximate invariability of eigenvectors of the climate field,the prediction of climate field is obtained by return computation,together with the principal component.A test example is predicting the flood period rainfall in Guangdong.The principal component and the characteristics of special-temporal distribution and its classification are computed and analyzed.The prediction of field for 2003—2005 is made and comparisons with the field of observations and errors test are established.The results show that the predictive efficacy is remarkable.Questions concerning the predicted length(years),regional coverage,physical background of elements and factors will need further research.