Effects of inferring unobserved thermospheric and ionospheric state variables by using an Ensemble Kalman Filter on global ionospheric specification and forecasting

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題名:	Effects of inferring unobserved thermospheric and ionospheric state variables by using an Ensemble Kalman Filter on global ionospheric specification and forecasting
作者:	劉正彥;Hsu, Chih-Ting;Matsuo, Tomoko;Wang, Wenbin;Liu, Jann-Yenq
貢獻者:	地球科學學院太空科學與工程學系
關鍵詞:	Data assimilation;Data collection;Density;Ensemble Kalman Filter;FORMOSAT-3/COSMIC;Impact analysis;Ionosphere;Ionospheric electron density;Ionospherics;Joining;Mathematical models;State variable;thermospheric-ionospheric coupling;Variables
日期:	2014-01-01
上傳時間:	2026-04-23 11:03:38 (UTC+8)
出版者:	Wiley-Blackwell;Washington: Blackwell Publishing Ltd
摘要:	摘要： This paper demonstrates the significance of ion‐neutral coupling to ionospheric data assimilation for ionospheric specification and forecast. Ensemble Kalman Filter (EnKF) is used to assimilate synthetic electron density profiles sampled according to the Formosa Satellite 3/Constellation Observing System for Meteorology, Ionosphere, and Climate into the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIEGCM). The combination of the EnKF and first‐principles TIEGCM allows a self‐consistent treatment of thermosphere and ionosphere coupling in the data assimilation and forecast. Because thermospheric variables affect ionospheric electron densities, different combinations of an observed ionospheric state variable (electron density), and unobserved ionospheric and thermospheric state variables (atomic oxygen ion density, neutral temperature, winds, and composition) are included as part of the EnKF state vector in experiments. In the EnKF, the unobserved state variables are estimated and made dynamically and chemically consistent with the observed state variable, thus improving the performance of the data assimilation system. The impact on ensemble forecast is further examined by initializing the TIEGCM with the assimilation analysis. The main findings are the following: (1) by incorporating ion‐neutral coupling into the EnKF, the ionospheric electron density analysis, and forecast can be considerably improved. (2) Thermospheric composition is the most significant state variable that affects ionospheric analysis and forecast. (3) Thermospheric variables have a much longer impact on ionospheric forecast (>24 h) than ionospheric variables (2 to 3 h). (4) In the TIEGCM, the effect of assimilating electron densities is not completely transmitted to the forecast step unless the densities of ion species are estimated. Key Points The impacts of ion‐neutral coupling on ionospheric data assimilation are studiedNeutral composition is very effective to update on ionospheric data assimilationThe adjustment can last longer under the impact of thermospheric variables 其他題名： J. Geophys. Res. Space Physics 出版者： Washington: Blackwell Publishing Ltd 出版日期： 2014-11 出處： Journal of geophysical research : Space physics (2013 - Present), 2014-11, Vol.119 (11), p.9256-9267 資源來源： Wiley Online Library All Journals 版權： 2014. American Geophysical Union. All Rights Reserved. 識別號： ISSN: 2169-9380 識別號： ISSN: 2169-9402 識別號： EISSN: 2169-9402 識別號： DOI: 10.1002/2014JA020390
顯示於類別:	[太空科學與工程學系] 期刊論文

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