[P-EM10] Space Weather and Space Climate

[PEM10-P24] Development and Evaluation of Ionospheric Data Assimilation Model Using GAIA

*陣 英克¹、安藤 慧¹、垰 千尋¹、三好 勉信²、品川 裕之¹、藤原 均³ (1.情報通信研究機構、2.九州大学、3.成蹊大学)

キーワード：データ同化、電離圏、熱圏、宇宙天気

Prediction of the earth’s ionosphere and thermosphere is an important topic of space weather research, since the variation in these regions have impacts on the GNSS applications and communications as well as satellite operations. For the purpose of upper atmospheric prediction, we are developing a data assimilative model using a whole atmosphere-ionosphere model called GAIA (Ground-to-topside model of Atmosphere and Ionosphere for Aeronomy) and ionospheric observations such as TEC (total electron content) derived from GNSS receivers and radio occultation measurements by FORMOSAT/COSMIC satellites. We adopted a data assimilation platform, DART, developed by NCAR, which provides ensemble Kalman filter approach. The approach calculates the most probable solution considering the observation errors and model uncertainties. It is necessary for the approach to be effective so that the model uncertainty is well reproduced by the ensemble. For this reason, we first extracted uncertain parameters used in GAIA that lead to the uncertainty of model outputs and then derived the covariance between the parameters and ionospheric observations. Based on the analysis, we constructed an ionospheric data assimilation model.