The potential of the ensemble Kalman filter for NWP - a comparison with 4D-Var

被引：556
作者：
Lorenc, AC [1 ]
机构：
[1] Met Off, Exeter EX1 3PB, Devon, England
来源：
QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY | 2003年 / 129卷 / 595期
关键词：
error covariance modelling; numerical weather prediction;
D O I：
10.1256/qj.02.132
中图分类号：
P4 [大气科学（气象学）];
学科分类号：
0706 ; 070601 ;
摘要：
The ensemble Kalman filter (EnKF) is reviewed for its expected assimilation characteristics and ease of implementation, and compared to the currently more popular four-dimensional variational assimilation (4D-Var). The EnKF is attractive when building a new medium-range ensemble numerical weather prediction (NWP) system. However it is less suitable for NWP systems with uncertainty in a wide range of scales; it may not use hieh-resolution satellite data as effectively as 4D-Var. For limited-area mesoscale NWP systems a hybrid method is attractive.
引用
收藏
页码：3183 / 3203
页数：21
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