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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Development and Application of Ensemble-Variational Data Assimilation Methods

Xiong Chunhui 1,2, Zhang Lifeng 1, Guan Jiping 1, Tao Hengrui 3, Su Jiajia 4   

  1. 1.College of Meteorology and Oceanography,PLA University of Science and Technology, Nanjing 211101,China;2.Unit No.95903 of Airborne Troops of Air Force, Wuhan 430331, China;3. Aviation University of Air Force, Changchun 130022, China;4.Unit No.71521 of PLA, Xinxiang 453002, China
  • Received:2013-01-31 Revised:2013-04-25 Online:2013-06-10 Published:2013-06-10

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 cuttingedge issues of atmospheric data assimilation. The ensemblevariational 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 ensemblevariational DA is expanded. Then, the application of ensemblevariational DA in the Great Britain and the U.S. is introduced. Finally, the main issues of ensemblevariational DA are reviewed and the prospect of the future development trend is listed.

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