Speaker
Description
Global numerical models are a key component of space weather forecasting. Recent work has highlighted the importance of cross-scale coupling in the ITM system, and the critical role of mesoscales in that coupling. Mesoscale phenomena, however, are difficult to quantitatively validate in the global models against observations. Data assimilative models can be used to reconstruct high-latitude ionospheric electrodynamic quantities using sparse observations, providing a new avenue for data-model comparisons. We demonstrate this new approach to data-model comparisons by assimilating global simulation output from Multiscale Atmosphere-Geospace Environment (MAGE) into Local mapping of the polar ionospheric electrodynamics (Lompe). We directly compare and find good agreement between the simulation output and real-data-assimilation patterns of field-aligned currents (FACs) and their constituent terms deriving from the divergence of the ionospheric Ohm's Law. We further calculate dayside and nightside reconnection electric fields and voltages in both observations and simulation. Our approach offers a significantly new capability for mesoscale data-model comparisons, with a concomitant impact on space weather modeling and forecasting.
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