TIEGCM Ensemble Kalman Filter Assimilation Model Design and Preliminary Results
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摘要: 选择参数化的电离层热层理论模型TIEGCM作为背景模型,基于COSMIC掩星观测的电子密度廓线数据,应用集合卡尔曼滤波方法建立全球电离层电子密度同化模型,实现了全球电离层的电子密度同化.同化结果表明,该同化模型能将观测资料有效同化到背景模式中,获得全球三维电离层电子密度.与背景模式相比,同化得到的电子密度相对于观测值的偏差显著下降.对于有同化和无同化参与的试验,NmF2的标准偏差分别降低约60%和20%.此外,分组同化与同时同化的结果对比显示,平均偏差改善基本一致,同时同化后的标准偏差在峰值高度以上略有减小.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.
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Key words:
- Ionosphere /
- Data assimilation /
- Ensemble Kalman filter /
- Simultaneous assimilation
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