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Substorm dynamics in MHD: Statistical validation tests and paths for improvement
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  • John Haiducek,
  • Daniel Welling,
  • Steven Morley,
  • Agnit Mukhopadhyay,
  • Xiangning Chu,
  • Joseph Helmboldt,
  • Joseph Huba,
  • Natalia Ganushkina
John Haiducek
US Naval Research Laboratory

Corresponding Author:john.haiducek@nrl.navy.mil

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Daniel Welling
University of Texas at Arlington
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Steven Morley
Los Alamos National Laboratory
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Agnit Mukhopadhyay
University of Michigan Ann Arbor
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Xiangning Chu
University of California Los Angeles
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Joseph Helmboldt
US Naval Research Laboratory
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Joseph Huba
Syntek Technologies
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Natalia Ganushkina
University of Michigan Ann Arbor
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Abstract

Magnetohydrodynamic (MHD) models have been used for nearly four decades to study the dynamics of magnetospheric substorms. However, until recently no demonstration has been made that MHD models can consistently reproduce substorm onset times in a statistical sense. To test whether MHD can reproduce observed substorm onset times, we developed a procedure for identifying substorm onsets that can be applied both to observational data and to MHD output. Our substorm identification procedure aims to improve upon existing methods of substorm identification by using multiple types of observations to corroborate each identified substorm. Using this procedure, we identified over 100 substorms from the period 1-31 January 2005. Using this list of substorm onset times, we show that the MHD model has weak, but statistically significant skill in predicting substorm onset times. We explore paths to improving the ability of the MHD model to predict substorm dynamics by testing different configurations of the MHD model.