GRAPES全球模式的模式误差估计

现代数值天气模式考虑的物理过程和边界条件越来越复杂, 但是它描述的大气状态和真实的大气流体运动轨迹还有一定的差距, 存在模式误差。在以往的研究中, 模式误差往往被忽略, 在集合卡尔曼滤波同化系统中, 如果忽略模式误差会导致滤波发散现象。本文用不同分辨率的模式预报差异估计了GRAPES全球模式的模式误差, 研究发现模式误差随着分辨率降低而线性增加, 而且模式误差随着预报时效的增加呈现线性增长的趋势。

Estimation of Model Error for the Global GRAPES Model

The model error exists for the reason that a certain difference is present between the weather state described by the model and the true weather state though more and more physical processes and complicated boundary conditions are considered in numerical weather prediction models. Filter divergence was found in the ensemble Kalman filter system when the model errors were neglected in previous studies. In this paper, it is shown that the model errors increase linearly with the decrease of resolution and the increase of the model error is obvious with the increase of model forecasting length through estimating the discriminations among the forecasting fields at different resolutions.