一种基于EOF分析的迭代方法在业务预报中的应用

A DOWNSCALING METHOD BASED ON THE EMPIRICAL ORTHOGONAL FUNCTION (EOF) AND ITS APPLICATION IN SEASONAL PREDICTION

用传统的EOF分析迭代方法,利用国家气候中心CGCM模式夏季预报产品、前冬季的500hPa高度场和SLP等实况资料,进行了2003～2005年我国夏季降水、温度预测的Downscaling试验对比。结果显示:该方法在解释温度预测时效果比降水预测的好,应用时截断阶数取2时的效果最好;另外,模式产品的平均Downscaling效果比前期冬季500hPa高度场和SLP的Downscaling效果好,比这3年实际业务预报的平均效果高。

Based on the traditional method of Empirical Orthogonal Function （EOF）, the products of CGCM for summer, the observed SLP and 500 hPa geography height over the North Hemisphere in winter were used to Downscale the summer prediction in China from 2003 to 2005. After comparing the predictions with observation at 160 stations in China, the temperature prediction is much better than that of rainfall prediction and a better assessment was obtained when the truncation order was at two. The mean effect （2003 - 2005）, which was obtained from CGCM products, was a little better than that from other observed winter data.