自忆谱模式及其初步应用

取一个数值预报模式作为动力核，基于相应的自忆性方程，可设计一个自忆预报模式。现以美国AFGL谱模式作为动力核，推导了一个能使用多时刻资料的自忆谱模式。运用全球网格点资料，通过复最小二乘估计，求得模式中的记忆系数。用该模式试作全球高空温度场的30天平均预报。预报检验表明，自忆谱模式的预报技巧是相当高的。

Self-Memory Spectral Model and its Preliminary Application

Taking a numerical prediction model as a dynamical kernel, a self-memory prediction model can be developed on the basis of the corresponding self-memorization equation The self-memory spectral model, which is capable of involving multi-time initial data, was built with US AFGL spectral model as the dynamical kernel By utilizing the complex least square for the global network data, the memory c oe fficients in the self-memory spectral model were acquired Several forecasts for 30-day mean field of global up-level temperature were made with the model Verifications of the forecasts indicate that the forecasting skill of the self-memory spectral model is quite satisfactory