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\begin{document}

\title{Substorm dynamics in MHD: Statistical validation tests and paths for
improvement}



\author[1]{John Haiducek}%
\author[2]{Daniel Welling}%
\author[3]{Steven Morley}%
\author[4]{Agnit Mukhopadhyay}%
\author[5]{Xiangning Chu}%
\author[1]{Joseph Helmboldt}%
\author[6]{Joseph Huba}%
\author[4]{Natalia Ganushkina}%
\affil[1]{US Naval Research Laboratory}%
\affil[2]{University of Texas at Arlington}%
\affil[3]{Los Alamos National Laboratory}%
\affil[4]{University of Michigan Ann Arbor}%
\affil[5]{University of California Los Angeles}%
\affil[6]{Syntek Technologies}%


\vspace{-1em}



  
  \date{May 17, 2024}


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\begin{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.%
\end{abstract}%



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