中文摘要：

资料误差和模式误差都是制约数值预报结果准确性提高的关键因素，传统四维资料同化都是假设模式完全正确仅对初始资料进行修正，忽略了模式误差本身造成的预报误差。伴随模式同化系统不仅具有修正资料误差的能力，也可应用于修正模式误差方面的研究。本文将卫星中心导风系统提供的GMS5卫星风场与非常规温度资料用于MM5伴随同化系统修正模式地形误差进行试验性研究表明，该方法能够反演出一个既与初始气象要素场相匹配，又与模式更协调的地形场，得到比一般包络地形更好的效果，改善模式对强降水中心及降水区域的预报；数值试验结果还揭示模式误差对模式预报造成一定的影响，用伴随方法对观测资料进行修正的同时也对模式误差进行修正的方法是可行的。

英文摘要：

Model errors and data errors are the limiting factors to the improvement of the numerical weather prediction（NWP） models. In 4-dimension data assimilation, the model is often assumed to be precise, correcting initial observations and neglecting the forecast error caused by the model error. Adjoint-model Assimilation System can be used in the correction of initial conditions and model parameters. Terrain is one of the multiple factors governing atmospheric circulation and also an important ingredient of numerical weather prediction（NWP） models, responsible directly for the results. Model terrain adjustment is carried out by means of the Pennsylvania State University（PSU）/National Center for Atmospheric Research（NCAR） non-hydrostatic mesoscale model MM5 with its adjoint-model assimilation system（AMAS） including GMS5 cloud-derived winds and non-conventional temperature from the Nation Satellite Meteorological Center（NSMC）.There are two conclusions ：（1） the corrected terrain coordinates with the initial observations and the model can improve the model results varying with the range and intensity of the of model errors on prediction, the application of AMAS model parameters. meso-scale heavy-rain center. （2） Considering the effect is a new feasible approach to the improvement of NWP model parameters.