Data Availability and its Effect on the USU GAIM Data Assimilation Model

Details Data Availability and its Effect on the USU GAIM Data Assimilation Model Data Availability and its Effect on the USU GAIM Data Assimilation Model

Dec 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufmsa33a1144t&link_type=abstract

American Geophysical Union, Fall Meeting 2004, abstract #SA33A-1144

Physics

2415 Equatorial Ionosphere, 2443 Midlatitude Ionosphere, 2447 Modeling And Forecasting

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). The USU GAIM Gauss-Markov Kalman Filter (GMFK) uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of measurements; in either near real time or historical study modes. 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 1400km. It takes account of five ion species (NO+, O2+, N2+, O+, H+). The Gauss-Markov filter assimilates bottom-side electron density profiles from a variable number of ionosondes, slant TEC from a variable number of GPS satellite/ground station combinations, in-situ electron density from DMSP satellites, and line-of-sight UV radiances from satellite-based instruments. With the GMFK model the ionospheric densities obtained from IFM are used as a background upon which perturbations are imposed based on the available data and their errors. The density perturbations and associated errors evolve over time via a statistical Gauss-Markov process. The fidelity of the GMFK result is dependent on the quality and quantity of data available to specify the perturbations. We will compare results from the GMFK using various combinations of data types and data quantities.

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