夏季分县降水量集成预报试验

将国家气象中心Ｔ１０６和ＨＬＡＦＳ、山西省气象台ＢＰ神经元和动力相似方法输出的降水预报值作为预报因子，运用灰色理论分别将以上４个预报因子原始数列和降水实况数列作一次累加生成处理，分别得到随机性被弱化的单增数列，用卡尔曼滤波法进行递推计算，得到降水预报值。将得到的降水预报值作还原处理，即累减生成后，最终输出降水量分县预报。此方法用于１９９８年夏季，取得了良好的预报效果。

Composite Prediction Experiment of County Rainfall in Summer with NWP Products

The rainfall predicting values from T106 and HLAFS of NWC, BP neuron and dynamic similar method of Shanxi Meteorological Observatory were used for prediction factors.By using of grey theory, the original sequence of the predicting factors and actual rainfall sequence were conducted for accumulating process, respectively,then the random weakened increasing sequence were obtained.The recurrence calculation with Kalman filter method was used to acquire the rainfall predicting values.The values were retrieved to initial state,and the rainfall prediction for every county was given.The experiment in Summer in 1998 was conducted and obtained a good result in rainfall prediction.