卡尔曼滤波方法在天气预报中的应用

The Application of Kalman Filter in Weather Forecasts

从气象应用角度介绍了卡尔曼滤波的基本原理及其速推算法。为了说明卡尔曼滤波递推算法的应用方法，制作了北京１９９３年１月份逐日最低气温３６小时预报。预报结果令人满意，表明该方法很有实用价值，与ＭＯＳ方法相比，它的优点是不需要收集大样本历史资料，因此，它容易适应数值预报模式的变化。

he principle of Kalman filter (KF) and the recursive algorithm of KF are introduced from the view point of meteorological applications. In order to describe the application of the recursive algorithm of KF, a daily minimum temperature up to 36h ahead has been made for Beijing city for the period from 1 to 30 Jan. 1993. The results are satisfactory and approve that the method of KF is mostly practical. The advantages of KF compared to that of MOS method are that one do not have to collect large historical data. So KF will adapt easily to numerical weather prediction model changes.