A Statistical Forecasting Model for the High Temperature Disastrous Weather

In this paper, using empirical orthogonal function (EOF) expansion method, the temporal and spatial distribution features of high temperature weather causing disaster during the winter wheat milk-filling and milking maturity phases in North China and Weihe River reaches are analysed. Based on this analysis, the optimal regression model for high temperature weather forecasting have been developed by using the principal component reverse selecting method combined with multiple correlation coefficient criteria.