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  • Dataset Containing Global Modeling Results Comparing Magnetopause Distances and CPCP

    work
    Creator:
    Agnit Mukhopadhyay
    Description:
    Conducting quantitative metrics-based performance analysis of first-principles-based global magnetosphere models is an essential step in understanding their capabilities and limitations, and providing scope for improvements in order to enhance their space weather prediction capabilities for a range of solar conditions. In this study, a detailed comparison of the performance of three global magnetohydrodynamic (MHD) models in predicting the Earth’s magnetopause location and ionospheric cross polar cap potential (CPCP) has been presented. Using the Community Coordinated Modeling Center’s Run-on-Request system and extensive database on results from various magnetospheric scenarios simulated for a variety of solar wind conditions, the aforementioned model predictions have been compared for magnetopause standoff distance estimations obtained from six empirical models, and with cross polar cap potential estimations obtained from the Assimmilative Mapping of Ionospheric Electrodynamics (AMIE) Model and the Super Dual Auroral Radar Network (SuperDARN) observations. We have considered a range of events spanning different space weather activity to analyze the performance of these models. Using a fit performance metric analysis for each event, we have quantified the models’ reproducibility of magnetopause standoff distances and CPCP against empirically-predicted observations, and identified salient features that govern the performance characteristics of the modeled magnetospheric and ionospheric quantities.
    Citation to related publication:
    Mukhopadhyay, A., Jia, X., Welling, D. T., & Liemohn, M. W. (2021). Global Magnetohydrodynamic Simulations: Performance Quantification of Magnetopause Distances and Convection Potential Predictions. Frontiers in Astronomy and Space Sciences, 8.  https://doi.org/10.3389/fspas.2021.637197
    Discipline:
    Engineering and Science