Enhanced ensemble-based 4DVar scheme for data assimilation

被引:25
|
作者
Yang, Yin [1 ]
Robinson, Cordelia [1 ,2 ]
Heitz, Dominique [2 ]
Memin, Etienne [1 ]
机构
[1] Inria, F-35042 Rennes, France
[2] UR TERE, Irstea, F-35044 Rennes, France
关键词
Data assimilation; Optimal control; Ensemble methods; Shallow water model; Depth sensor; VARIATIONAL DATA ASSIMILATION; SEQUENTIAL DATA ASSIMILATION; KALMAN FILTER; PART I; MODEL; FORMULATION; 4D-VAR; NWP;
D O I
10.1016/j.compfluid.2015.03.025
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Ensemble based optimal control schemes combine the components of ensemble Kalman filters and variational data assimilation (4DVar). They are trendy because they are easier to implement than 4DVar. In this paper, we evaluate a modified version of an ensemble based optimal control strategy for image data assimilation. This modified method is assessed with a shallow water model combined with synthetic data and original incomplete experimental depth sensor observations. This paper shows that the modified ensemble technique is better in quality and can reduce the computational cost. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:201 / 210
页数:10
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