Advances in Earth Science ›› 2013, Vol. 28 ›› Issue (6): 648-656. doi: 10.11867/j.issn.1001-8166.2013.06.0648
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Xiong Chunhui 1,2, Zhang Lifeng 1, Guan Jiping 1, Tao Hengrui 3, Su Jiajia 4
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Xiong Chunhui, Zhang Lifeng, Guan Jiping, Tao Hengrui,Su Jiajia. Development and Application of Ensemble-Variational Data Assimilation Methods[J]. Advances in Earth Science, 2013, 28(6): 648-656.
In recent years, ensemble-variational Data Assimilation (DA) methods have become cuttingedge issues of atmospheric data assimilation. The ensemblevariational DA methods which adopt the advantages of ensemble Kalman filter and variational DA is an effective way to the integration of ensemble prediction system and DA system in the Numerical Weather Prediction (NWP) system. Firstly, the concept of ensemble-variational DA is introduced after the comparison of advantages and disadvantages between variational DA and ensemble Kalman filter. Secondly, the ensemble-variational DA methods are divided into two categories by different ways of background error covariance generation. One is simple linear combination of static and ensemble covariance, and the other is augmentation of control variables. Moreover, the related development is introduced and the concept of ensemblevariational DA is expanded. Then, the application of ensemblevariational DA in the Great Britain and the U.S. is introduced. Finally, the main issues of ensemblevariational DA are reviewed and the prospect of the future development trend is listed.