A New Approach to Data‐Model Comparisons: Using MAGE and Lompe to Unravel Ionosphere‐Magnetosphere Electrodynamics

Abstract Global numerical simulations are valuable tools for understanding the Sun‐Earth interaction as they provide a more thorough picture of the system when compared to typically sparse observations. Yet, comparisons of these global models against observations is complicated by the inherent uncertainty that the observed phenomena occurred at the same time and location in the simulation domain. Therefore, aggregate measures of the Sun‐Earth interaction, such as activity indices (e.g., AL, AU, Dst, cross polar‐cap potential), are often used, with the downside of missing important underlying physical processes, especially at the mesoscales. Metrics or parameters that provide deeper insight into the physics but do not rely precisely on the location of the observations are therefore needed. 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 and their constituent terms deriving from the divergence of the ionospheric Ohm's Law. We further calculate reconnection electric fields and voltages and find good agreement during the initial expansion phase, but different behavior later in the event as MAGE enters into steady‐magnetospheric convection, in contrast to the observations, which indicated a classic substorm.