Data assimilation models for space weather applications

Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon (OTH) radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the FAA's Wide-Area Augmentation System (WAAS). In an effort to mitigate and/or forecast the adverse effects of the space weather, we developed several physics-based data assimilation models of the ionosphere-upper atmosphere. Two of our models were developed under a program called Global Assimilation of Ionospheric Measurements (GAIM). One of them is now in operational use at the Air Force Weather Agency (AFWA) in Omaha, Nebraska, and it is also being used at the Air Force Research Laboratory, Naval Research Laboratory, and Community Coordinated Modeling Center. This model is a Gauss-Markov Kalman Filter (GAIM-GM) model, and it uses a physics-based model of the global 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 covers the E-region, F-region, and topside ionosphere from 90 to 1400 km. The second data assimilation model uses a physics-based ionosphere-plasmasphere model and a Kalman filter as a basis for assimilating the different data types. This Full Physics model (GAIM-FP), which is global and covers the altitude range of from 90 to 30,000 km, is more sophisticated than the Gauss-Markov model, and hence, should provide more reliable specifications in data poor regions and during severe weather disturbances. The GAIM-FP model is scheduled for operational use in 2012. Both of these GAIM models assimilate 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, line-of-sight UV emissions measured by satellites, and occultation data. Quality control algorithms are provided for all of the data types and are an integral part of the GAIM models and these models take account of latent data (up to 3 hours). The current status, validation efforts, and future plans for the USU GAIM models will be discussed.