Cluster ensemble Kalman filter

被引：39
|
作者：
Smith, Keston W. [1 ]
机构：
[1] Woods Hole Oceanog Inst, Woods Hole, MA 02543 USA
来源：
TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY | 2007年 / 59卷 / 05期
关键词：
D O I：
10.1111/j.1600-0870.2007.00246.x
中图分类号：
P4 [大气科学（气象学）];
学科分类号：
0706 ; 070601 ;
摘要：
A modified ensemble Kalman filter (KF) is proposed which can enhance performance for highly non-linear prognostic models. The algorithm differs from the traditional ensemble KF by the addition of an expectation maximization step, which estimates the parameters of a Gaussian mixture model for the ensemble of forecast states. The algorithm is tested in twin experiments using a simple phytoplankton-zooplankton model.
引用
收藏
页码：749 / 757
页数：9
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