扩展经验正交函数(EEOF)及其在月、季降水预测中的应用

本文提出一种降水长期预测的新方案，用扩展经验正交函数(EEOF)展开连续月组成的月（季）降水分布场，求取各月的特征向量场和对应的时间权重系数，分析各场的天气学意义及前后承替的相互关系，用前期出现的特征向量场的特征来预测后期的降水场分布趋势，同时利用特征向量场所对应的时间系数作二维点聚图，估算预报月（季）份的降水总趋势。

Extended Empirical Orthogonal Function (EEOF) and Applications to Monthly (Seasonal) Rainfall Prediction

In this paper, a new scheme for long rang forecast has been presented. The monthly (seasonal) rainfall distribution field which are consist of continuous monthly data is expanded by EEOF. Each monthly characteristic vector field and correction to time weighted coefficient is evaluated, the synoptic signification of each field and its continuance evolution are analysed. Finally, the monthly and seasonal rainfall distribution field is predicted by the earlier characteristic vector field. Simultaneously, the rainfall tendency of monthly (seasonal) is evaluated by the two dimensional scatter diagram of the time coefficient.