Multimodel Ensemble Prediction System for Space Weather Applications

The Earth's Ionosphere-Thermosphere-Electrodynamics (I-T-E) system is highly nonlinear and varies markedly on a range of spatial and temporal scales. Recently, we have created a Multimodel Ensemble Prediction System (MEP S) that is based on data assimilation models, with the goal being to specify and forecast the global I-T-E system (Schunk et al., 2012). Our team has 7 first-principles-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and mid-low latitude ionosphere-electrodynamics. Hence, we can conduct ensemble modeling of the I-T-E system with different data assimilation models and then compare model reconstructions, which should help distinguish between the underlying physics and model artifacts.