Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance

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题名:	Ionospheric assimilation of radio occultation and ground-based GPS data using non-stationary background model error covariance
作者:	林其彥;Lin, C. Y.;Matsuo, T.;Liu, J. Y.;Lin, C. H.;Tsai, H. F.;Araujo-Pradere, E. A.
贡献者:	太空科學與科技研究中心
关键词:	Analysis;Computer simulation;Correlation;Correlation analysis;Covariance;Data;Data assimilation;Data collection;Density;Density distribution;Density profiles;Distribution;Electron density;Electron density profiles;Electrons;Empirical analysis;Empirical orthogonal functions;Global Positioning System;Global positioning systems;GPS;Ground-based observation;Incoherent scatter radar;Ionosphere;Ionospheric electron density;Ionospheric models;Kalman filters;Markov chains;Orthogonal functions;Radar;Radar data;Radio;Radio occultation;Total Electron Content
日期:	2015-01-12
上传时间:	2026-04-23 11:03:29 (UTC+8)
出版者:	Copernicus Gesellschaft mbH;Katlenburg-Lindau: Copernicus Publications
摘要:	摘要： Ionospheric data assimilation is a powerful approach to reconstruct the 3-D distribution of the ionospheric electron density from various types of observations. We present a data assimilation model for the ionosphere, based on the Gauss–Markov Kalman filter with the International Reference Ionosphere (IRI) as the background model, to assimilate two different types of slant total electron content (TEC) observations from ground-based GPS and space-based FORMOSAT-3/COSMIC (F3/C) radio occultation. Covariance models for the background model error and observational error play important roles in data assimilation. The objective of this study is to investigate impacts of stationary (location-independent) and non-stationary (location-dependent) classes of the background model error covariance on the quality of assimilation analyses. Location-dependent correlations are modeled using empirical orthogonal functions computed from an ensemble of the IRI outputs, while location-independent correlations are modeled using a Gaussian function. Observing system simulation experiments suggest that assimilation of slant TEC data facilitated by the location-dependent background model error covariance yields considerably higher quality assimilation analyses. Results from assimilation of real ground-based GPS and F3/C radio occultation observations over the continental United States are presented as TEC and electron density profiles. Validation with the Millstone Hill incoherent scatter radar data and comparison with the Abel inversion results are also presented. Our new ionospheric data assimilation model that employs the location-dependent background model error covariance outperforms the earlier assimilation model with the location-independent background model error covariance, and can reconstruct the 3-D ionospheric electron density distribution satisfactorily from both ground- and space-based GPS observations. 出版者： Katlenburg-Lindau: Copernicus Publications 出版日期： 2015-01-12 出處： Atmospheric Measurement Techniques, 2015-01, Vol.8 (1), p.171-182 資源來源： Publicly Available Content Database 版權： COPYRIGHT 2015 Copernicus GmbH 版權： Copyright Copernicus GmbH 2015 識別號： ISSN: 1867-8548 識別號： ISSN: 1867-1381 識別號： EISSN: 1867-8548 識別號： DOI: 10.5194/amt-8-171-2015
显示于类别:	[太空科學與科技研究中心] 期刊論文

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