基于扩散滤波的多尺度三维变分研究  

Multi-scale 3D-VAR based on diffusion filter

作　　者：李冬[1] 王喜冬[1,2] 张学峰[1,2] 吴新荣[1,2] 李威[1] 韩桂军[1] 

机构地区：[1]国家海洋信息中心国家海洋局海洋环境信息保障技术重点实验室,天津300171 [2]中国科学院南海海洋研究所LED重点实验室,广东广州510301

出　　处：《海洋通报》2011年第2期164-171,共8页Marine Science Bulletin

基　　金：国家重点基础研究发展计划课题(2007CB816001);国家自然科学基金项目(40776016、4103和40906016)联合资助

摘　　要：将扩散方程引入三维变分分析,揭示了传统3D-VAR不能有效提取多尺度观测信息的根本原因,即观测导致的目标函数梯度在空间的不连续分布。将扩散滤波融入基于梯度的最优化算法,发展了基于扩散滤波的多尺度3D-VAR。海表面温度数据同化试验结果表明,新方法可从长波至短波有效地提取多尺度的观测信息。The diffusion equation is introduced into 3D-VAR analysis in this paper.As it reveals,the root cause of the inefficiency of the traditional 3D-VAR scheme in extracting multi-scale information resolved by observations lies in the discontinuous distribution of gradient of the cost function caused by the inhomogeneous distribution of observations.A multi-scale 3D-VAR scheme is developed by incorporating diffusion filtering into gradient-based minimization algorithm.The new scheme is applied to a two-dimensional idealized SST assimilation experiment with real AVHRR SST observations,which shows a superior performance and the multi-scale observational information,and from longer to shorter wavelengths,such observational informationcan be extracted successively by this scheme.

关 键 词：三维变分 数据同化 各向异性 递归滤波 扩散方程 

分 类 号：P731.22[天文地球—海洋科学]