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Chinese Journal of Space Science ›› 2017, Vol. 37 ›› Issue (2): 168-176.doi: 10.11728/cjss2017.02.168

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TIEGCM Ensemble Kalman Filter Assimilation Model Design and Preliminary Results

ZHANG Yanan1,2, WU Xiaocheng1, HU Xiong1   

  1. 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190;
    2. University of Chinese Academy of Sciences, Beijing 100049
  • Received:2016-01-25 Revised:2016-03-11 Online:2017-03-15 Published:2017-03-02

Abstract:

By using the parameterized ionosphere model TIEGCM as the background model, and based on the COSMIC observations, the global ionospheric electron density assimilation model is established using ensemble Kalman filter. Result shows that this model can effectively assimilate the observations into background model and acquire three-dimensional ionospheric electron density. By comparison to the background, the error between analysis and observations decreases significantly. The Root Mean Square Error (RMSE) of NmF2 decreases by about 60% for observations with assimilation, and 20% for observations without assimilation. The RMSE of hmF2 does not get improvement except for mean error. The results of Simultaneous Assimilation (SA) and Batches Assimilation (BA) are compared for this case. The time that the two methods spend in assimilation is about 6 to 7 minutes, which does not differ very much. SA needs nearly 8GB storage while BA needs less than 2GB. The statistic of electron density error shows that they nearly acquire the same mean error, but the SA gets relative better improvement in RMSE above 250km height.

Key words: Ionosphere, Data assimilation, Ensemble Kalman filter, Simultaneous assimilation

CLC Number: