Ionospheric data assimilation with thermosphere-ionosphere-electrodynamics general circulation model and GPS-TEC during geomagnetic storm conditions

C. H. Chen, C. H. Lin, T. Matsuo, W. H. Chen, I. T. Lee, J. Y. Liu, J. T. Lin, C. T. Hsu

研究成果: Article同行評審

27 引文 斯高帕斯(Scopus)

摘要

The main purpose of this paper is to investigate the effects of rapid assimilation-forecast cycling on the performance of ionospheric data assimilation during geomagnetic storm conditions. An ensemble Kalman filter software developed by the National Center for Atmospheric Research (NCAR), called Data Assimilation Research Testbed, is applied to assimilate ground-based GPS total electron content (TEC) observations into a theoretical numerical model of the thermosphere and ionosphere (NCAR thermosphere-ionosphere-electrodynamics general circulation model) during the 26 September 2011 geomagnetic storm period. Effects of various assimilation-forecast cycle lengths: 60, 30, and 10 min on the ionospheric forecast are examined by using the global root-mean-squared observation-minus-forecast (OmF) TEC residuals. Substantial reduction in the global OmF for the 10 min assimilation-forecast cycling suggests that a rapid cycling ionospheric data assimilation system can greatly improve the quality of the model forecast during geomagnetic storm conditions. Furthermore, updating the thermospheric state variables in the coupled thermosphere-ionosphere forecast model in the assimilation step is an important factor in improving the trajectory of model forecasting. The shorter assimilation-forecast cycling (10 min in this paper) helps to restrain unrealistic model error growth during the forecast step due to the imbalance among model state variables resulting from an inadequate state update, which in turn leads to a greater forecast accuracy.

原文English
頁(從 - 到)5708-5722
頁數15
期刊Journal of Geophysical Research: Space Physics
121
發行號6
DOIs
出版狀態Published - 2016 六月 1

All Science Journal Classification (ASJC) codes

  • 空間與行星科學
  • 地球物理

指紋

深入研究「Ionospheric data assimilation with thermosphere-ionosphere-electrodynamics general circulation model and GPS-TEC during geomagnetic storm conditions」主題。共同形成了獨特的指紋。

引用此