A mollified ensemble Kalman filter

被引:48
作者
Bergemann, Kay [1 ]
Reich, Sebastian [1 ]
机构
[1] Univ Potsdam, Inst Math, D-14469 Potsdam, Germany
关键词
data assimilation; ensemble Kalman filter; mollification; incremental analysis updates; DATA ASSIMILATION; DYNAMIC-INITIALIZATION; SMALL MODEL; LOCALIZATION; BALANCE;
D O I
10.1002/qj.672
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
It is well recognized that discontinuous analysis increments of sequential data assimilation systems, such as ensemble Kalman filters, might lead to spurious high-frequency adjustment processes in the model dynamics. Various methods have been devised to spread out the analysis increments continuously over a fixed time interval centred about the analysis time. Among these techniques are nudging and incremental analysis updates (IAU). Here we propose another alternative, which may be viewed as a hybrid of nudging and IAU and which arises naturally from a recently proposed continuous formulation of the ensemble Kalman analysis step. A new slow-fast extension of the popular Lorenz-96 model is introduced to demonstrate the properties of the proposed mollified ensemble Kalman filter. Copyright (C) 2010 Royal Meteorological Society
引用
收藏
页码:1636 / 1643
页数:8
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