Particle Filtering in Geophysical Systems

被引:478
作者
van Leeuwen, Peter Jan [1 ,2 ]
机构
[1] Univ Reading, Dept Meteorol, Reading RG6 6BB, Berks, England
[2] Univ Utrecht, Inst Marine & Atmospher Res Utrecht, Utrecht, Netherlands
关键词
ENSEMBLE KALMAN FILTER; SEQUENTIAL DATA ASSIMILATION; MONTE-CARLO; PARAMETER-ESTIMATION; MODEL; PREDICTION;
D O I
10.1175/2009MWR2835.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The application of particle filters in geophysical systems is reviewed. Some background on Bayesian filtering is provided, and the existing methods are discussed. The emphasis is on the methodology, and not so much on the applications themselves. It is shown that direct application of the basic particle filter (i.e., importance sampling using the prior as the importance density) does not work in high-dimensional systems, but several variants are shown to have potential. Approximations to the full problem that try to keep some aspects of the particle filter beyond the Gaussian approximation are also presented and discussed.
引用
收藏
页码:4089 / 4114
页数:26
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