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CLC number: TP302.7; P409

On-line Access: 2013-08-02

Received: 2013-01-20

Revision Accepted: 2013-03-18

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Journal of Zhejiang University SCIENCE C 2013 Vol.14 No.8 P.634-641

http://doi.org/10.1631/jzus.C1300024


Notes and correspondence on ensemble-based three-dimensional variational filters


Author(s):  Hong-ze Leng, Jun-qiang Song, Fu-kang Yin, Xiao-qun Cao

Affiliation(s):  College of Computer, National University of Defense Technology, Changsha 410073, China

Corresponding email(s):   hzleng@nudt.edu.cn

Key Words:  3D-Var, Ensemble Kalman filter (EnKF), Ensemble transformation Kalman filter (ETKF), Physical space analysis system (PSAS), Ensemble data assimilation


Hong-ze Leng, Jun-qiang Song, Fu-kang Yin, Xiao-qun Cao. Notes and correspondence on ensemble-based three-dimensional variational filters[J]. Journal of Zhejiang University Science C, 2013, 14(8): 634-641.

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T1 - Notes and correspondence on ensemble-based three-dimensional variational filters
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Abstract: 
Several ensemble-based three-dimensional variational (3D-Var) filters are compared. These schemes replace the static background error covariance of the traditional 3D-Var with the ensemble forecast error covariance, but generate analysis ensemble anomalies (perturbations) in different ways. However, it is demonstrated in this paper that they are all theoretically equivalent to the ensemble transformation Kalman filter (ETKF). Furthermore, a new method named EnPSAS is presented. The analysis shows that EnPSAS has a small condition number and can apply covariance localization more easily than other ensemble-based 3D-Var methods.

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