USU GAIM: An Operational Data Assimilation Model of the Ionosphere

Details USU GAIM: An Operational Data Assimilation Model of the Ionosphere USU GAIM: An Operational Data Assimilation Model of the Ionosphere

Dec 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufmsa44a..02s&link_type=abstract

American Geophysical Union, Fall Meeting 2004, abstract #SA44A-02

Statistics

Applications

2415 Equatorial Ionosphere, 2443 Midlatitude Ionosphere, 2447 Modeling And Forecasting, 2467 Plasma Temperature And Density

Scientific paper

Physics-based data assimilation models of the ionosphere were developed at Utah State University as part of a DoD Multidisciplinary University Research Initiative (MURI) program. The USU effort was called Global Assimilation of Ionospheric Measurements (GAIM). One of the USU data assimilation models has been selected for operational use at the Air Force Weather Agency (AFWA) in Omaha, Nebraska. This model is a Gauss-Markov Kalman Filter (GMKF) model, and it uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. The physics-based model is the Ionosphere Forecast Model (IFM), which is global and covers the E-region, F-region, and topside from 90 to 1400 km. It takes account of five ion species (NO+, O2+, N2+, O+, H+). The Gauss-Markov Kalman Model assimilates bottom-side Ne profiles from a variable number of ionosondes, slant TEC from a variable number of ground GPS/TEC stations, in situ Ne from four DMSP satellites, and line-of-sight UV emissions measured by satellites. With the GMKF model the ionospheric densities obtained from the IFM constitute a background ionospheric density field on which perturbations are superimposed based on the available data sources and their errors. The density perturbations and the associated errors evolve over time via a statistical Gauss-Markov process. The configuration of the GMKF model and relevant applications will be presented.

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