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

作者：Leng, Hong ze^*; Song, Jun qiang; Yin, Fu kang; Cao, Xiao qun

来源：Journal of Zhejiang University-Science C(Computers and Electronics), 2013, 14(8): 634-641.

DOI：10.1631/jzus.C1300024

• 3D-Var
• Ensemble Kalman filter (EnKF)
• Ensemble transformation Kalman filter (ETKF)
• Physical space analysis system (PSAS)
• Ensemble data assimilation

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.

• 出版日期2013-8
• 单位中国人民解放军国防科学技术大学