Data Assimilation Models for Space Weather Specifications and Forecasts
In an effort to specify and forecast space weather disturbances, we developed several physics-based data assimilation models of the ionosphere-upper atmosphere. Two of the models were developed in association with a program called Global Assimilation of Ionospheric Measurements (GAIM). The first is a Gauss-Markov Kalman Filter model (GAIM-GM) and it uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of measurements. The physics-based model is the Ionosphere Forecast Model (IFM), which is global and covers the ionosphere from 90 to 1400 km. The second data assimilation model uses a physics-based ionosphere-plasmasphere model and an ensemble Kalman filter as a basis for assimilating the measurements. This full physics model (GAIM-FP) is global, takes account of six ion species (NO+, O2+, N2+, O+, H+, He+), and covers the altitude range of from 90 to 30,000 km. The GAIM models can assimilate bottom-side Ne profiles from hundreds of ionosondes, slant TEC from 1000 ground GPS/TEC receivers, in situ Ne from 4 DMSP satellites, occultation data from multiple satellites, and both limb and disk UV emissions measured by satellites. A third data assimilation model that we developed is a physics-based ensemble Kalman filter for high-latitude ionosphere dynamics and electrodynamics. This model assimilates cross-track ion velocities from the 4 DMSP satellites, line-of-sight ion velocities from the SuperDarn radar system, and magnetic perturbations from about 100 ground magnetometers. The GAIM-GM model is an operational model running at the Air Force Weather Agency and the Utah State University Space Weather Center; GAIM-FP is scheduled to become operational in early 2016; and the high-latitude data assimilation model will become operational within a few years.
The characteristics and uses of these models for applications (HF propagation and geo-location) and the effect that different data types have on the ionospheric reconstructions will be presented.