An Extension of the Dimension-Reduced Projection 4DVar  

作　　者：SHEN Si LIU Juan-Juan WANG Bin 

机构地区：[1]State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences [2]College of Earth Science, University of Chinese Academy of Sciences [3]Ministry of Education Key Laboratory for Earth System Modeling, Center of Earth System Science (CESS), Tsinghua University

出　　处：《Atmospheric and Oceanic Science Letters》2014年第4期324-329,共6页大气和海洋科学快报（英文版）

基　　金：supported by the National Basic Research Program of China (973 Program, Grant No. 2010CB951604);the National Key Technologies Research and Development Program of China (Grant No. 2012BAC22B02);the National Natural Science Foundation of China (Grant No. 41105120)

摘　　要：This paper extends the dimension-reduced projection four-dimensional variational assimilation method(DRP-4DVar) by adding a nonlinear correction process,thereby forming the DRP-4DVar with a nonlinear correction, which shall hereafter be referred to as the NC-DRP-4DVar. A preliminary test is conducted using the Lorenz-96 model in one single-window experiment and several multiple-window experiments. The results of the single-window experiment show that compared with the adjoint-based traditional 4DVar, the final convergence of the cost function for the NC-DRP-4DVar is almost the same as that using the traditional 4DVar, but with much less computation. Furthermore, the 30-window assimilation experiments demonstrate that the NC-DRP-4DVar can alleviate the linearity approximation error and reduce the root mean square error significantly.This paper extends the dimension-reduced pro- jection four-dimensional variational assimilation method （DRP-4DVar） by adding a nonlinear correction process, thereby forming the DRP-4DVar with a nonlinear correction, which shall hereafter be referred to as the NC-DRP- 4DVar. A preliminary test is conducted using the Lorenz-96 model in one single-window experiment and several multiple-window experiments. The results of the single-window experiment show that compared with the adjoint-based traditional 4DVar, the final convergence of the cost function for the NC-DRP-4DVar is almost the same as that using the traditional 4DVar, but with much less computation. Furthermore, the 30-window assimilation experiments demonstrate that the NC-DRP-4DVar can alleviate the linearity approximation error and reduce the root mean square error significantly.

关 键 词：data assimilation linear approximation nonlinear correction OSSE 

分 类 号：P456.7[天文地球—大气科学及气象学]