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In this study, a detailed metric survey on the “Galaxy 15” (April 2010) space weather event is conducted to validate MAGNetosphere–Ionosphere–Thermosphere (MAGNIT), a semi-physical auroral ionospheric conductance model characterizing four precipitation sources, against AMPERE measurements via field-aligned current (FAC) characteristics. As part of this study, the comparative performance of three ionosphere electrodynamic specifications involving auroral conductance models, MAGNIT, Ridley Legacy Model (RLM) (empirical), and Conductance Model for Extreme Events (CMEE) (empirical), within the Space Weather Modeling Framework (SWMF), is demonstrated. Overall, MAGNIT exhibits marginally improved predictions; root mean square error values in upward and downward FACs of MAGNIT predictions compared to AMPERE data are smaller than those of CMEE and Ridley Ionosphere Model (RIM) by $\sim$12.7% and $\sim$6.24% before the storm, $\sim$4.52% and $\sim$2.13% better during the main phase, $\sim$1.98% and $\sim$1.27% worse during the second minimum, and better by $\sim$1.84% and $\sim$1.49% by the beginning of the recovery, respectively. In all three model configurations, the dusk and night magnetic local time (MLT) sectors over-predict throughout the storm, while the day and dawn MLT sectors under-predict in response to interplanetary magnetic field (IMF) conditions. In addition to accuracy and bias, similar results and conclusions are drawn from additional metrics, including in the categories of correlation, precision, extremes, and skill, and recommendations are made for the best-performing model configuration in each metric category. Visual data–model comparisons conducted by studying the FAC location and latitude/MLT spread throughout various phases of the storm suggest that the spatial extent of the FACs is captured relatively well in the night-side auroral oval, unlike in the day-side oval. The spread in latitude of the FACs matches that in the previous literature on other model performances. This information on auroral precipitation sources and their weight on FACs, along with metrics from model–data comparisons, can be used to modify MAGNIT settings to optimize SWMF model performance. 

Abstract Solar wind drives magnetospheric dynamics through coupling with the geospace system at the magnetopause. While upstream fluctuations correlate with geomagnetic activity, their impact on the magnetopause energy transfer is an open question. In this study, we examine three‐dimensional global magnetospheric simulations using the Geospace configuration of the Space Weather Modeling Framework. We examine the effects of solar wind fluctuations during a substorm event by running the model with four different driving conditions that vary in fluctuation frequency spectrum. We demonstrate that upstream fluctuations intensify the energy exchange at the magnetopause increasing both energy flux into and out of the system. The increased energy input is reflected in ground magnetic indices. Moreover, the fluctuations impact the magnetopause dynamics by regulating the energy exchange between the polar caps and lobes and energy transport within the magnetotail neutral sheet. 

Abstract The vast size of the Sun’s heliosphere, combined with sparse spacecraft measurements over that large domain, makes numerical modeling a critical tool to predict solar wind conditions where there are no measurements. This study models the solar wind propagation in 2D using the BATSRUS MHD solver to form the MSWIM2D data set of solar wind in the outer heliosphere. Representing the solar wind from 1 to 75 au in the ecliptic plane, a continuous model run from 1995–present has been performed. The results are available for free athttp://csem.engin.umich.edu/mswim2d/. The web interface extracts output at desired locations and times. In addition to solar wind ions, the model includes neutrals coming from the interstellar medium to reproduce the slowing of the solar wind in the outer heliosphere and to extend the utility of the model to larger radial distances. The inclusion of neutral hydrogen is critical to recreating the solar wind accurately outside of ∼4 au. The inner boundary is filled by interpolating and time-shifting in situ observations from L1 and STEREO spacecraft when available. Using multiple spacecraft provides a more accurate boundary condition than a single spacecraft with time shifting alone. Validations of MSWIM2D are performed using MAVEN and New Horizons observations. The results demonstrate the efficacy of this model to propagate the solar wind to large distances and obtain practical, useful solar wind predictions. For example, the rms error of solar wind speed prediction at Mars is only 66 km s⁻¹and at Pluto is a mere 25 km s⁻¹.