GEM: Comprehensive Assessment of the Space Weather Modeling Framework for Magnetic Field Mapping

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Global magnetohydrodynamic (MHD) models are the most self-consistent way of mapping features from the ionosphere to the magnetosphere. However, stand-alone MHD models cannot account for the kinetic ring current physics in the inner magnetosphere, which strongly affects the accuracy of mapping. Coupling inner magnetosphere models with global MHD models is an important step forward in establishing a reliable means of mapping. Other features of MHD models, such as anisotropic pressure can better describe some features of magnetospheric dynamics such as magnetic reconnection and may improve mapping as well. Recent developments of the Space Weather Modeling Framework (SWMF) include implementation of two-way coupled inner magnetosphere models and the global MHD model, Block Adaptive Tree Solar-wind Roe-type Upwind Scheme (BATSRUS). The BATSRUS model has also recently been extended to incorporate more sophisticated physics, such as anisotropic pressure, multi-species and multi-fluid. This project will compare the simulation results with various observations and proxies, such as the boundary between open and closed magnetic field lines, the location of the reversal in the direction of plasma convection and the boundary between isotropic and anisotropic pitch-angle distributions of energetic particles. The project will investigate which model describes the observations best under various geomagnetic conditions, and will identify what physics associated with that model is the key to the improvement. Mapping between the ionosphere and the magnetosphere is an important but difficult problem in studying the geospace system. Uncertainty associated with mapping prevents our understanding of fundamental physical mechanisms that are responsible for important space weather events. The objective of this project is to assess the weaknesses of existing mapping techniques and determine how global simulations of the ionosphere/magnetosphere system compare with reality in terms of mapping.