大气科学2011，Vol.35Issue(6)：1169-1176,8.
模式误差动力特征:模式参数误差和物理过程描绘缺失误差
Dynamics of Model Errors: Accounting for Parameters Error and Physical Processes Lacking Error
摘要
Abstract
Initial errors and model errors are the limiting factors to the improvement of the numerical weather prediction (NWP). Traditional NWP and variational data assimilation (VDA) always ignore the influence of model errors, but it is important to investigate the dynamics of model errors for deep research. Based on the nonlinear dynamic model, the model error equation and the mean quadratic error expression for short time which are independent of the particular model are obtained on the assumption that there exist model parameters error and physical processes lacking error in the prediction model, and the non-Markovian character of the probability density of the model error is proved with Liouville equation. Taking the Hopf bifurcating system and Lorenz low-order atmospheric systems as examples, the results indicate that the mean quadratic error is bound to behave like t2 in a short time; the mean quadratic error tends to a stable value after a long time; the parameters error is equivalent to the physical processes lacking error under certain condition. It will afford valuable information for the research of forecasting error correction and weak constraint VDA from the theoretic aspect关键词
参数误差/物理过程误差/Lorenz系统/变分同化Key words
model parameters error, physical processes lacking error, Lorenz system, variational data assimilation分类
天文与地球科学引用本文复制引用
钟剑,黄思训,费建芳,杜华栋..模式误差动力特征:模式参数误差和物理过程描绘缺失误差[J].大气科学,2011,35(6):1169-1176,8.基金项目
国家自然科学基金资助项目41005030和41175025 （）
