Improving Global Magnetosphere Models with Optimized Ionospheric Boundary Conditions

Physics

Scientific paper

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2431 Ionosphere/Magnetosphere Interactions (2736), 2455 Particle Precipitation, 2736 Magnetosphere/Ionosphere Interactions (2431)

Scientific paper

Global magnetohydrodynamic (MHD) simulations typically employ semi-empirical relationships to transform standard MHD parameters like density and temperature into an average energy and flux of precipitating electrons. These in turn are used to drive an ionospheric model that establishes the inner boundary conditions for the MHD simulation. Using nonlinear estimation algorithms and inverted Polar UVI data for comparisons, we have optimized key empirical parameters in the Lyon-Fedder-Mobarry (LFM) global MHD model, which has until now relied on hand-tuned parameters trained on a very limited set of in situ observations to drive its ionospheric model. We present compelling evidence that these empirical relationships exhibit substantial time and spatial dependencies that must be considered before observations will match global magnetospheric models with reasonable accuracy.

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