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\begin{document}

\title{Conductance Model for Extreme Events : Impact of Auroral Conductance on
Space Weather Forecasts}



\author[1,1]{Agnit Mukhopadhyay}%
\author[2,2]{Daniel T Welling}%
\author[3,3]{Michael W. Liemohn}%
\author[3,3]{Aaron J. Ridley}%
\author[4,4]{Shibaji Chakraborty}%
\author[5,5]{Brian J. Anderson}%
\affil[1]{University of Michigan}%
\affil[2]{University of Texas at Arlington}%
\affil[3]{University of Michigan-Ann Arbor}%
\affil[4]{Virginia Tech}%
\affil[5]{John Hopkins Univ.}%


\vspace{-1em}



  
  \date{May 17, 2024}


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\begin{abstract}
Ionospheric conductance is a crucial factor in regulating the closure of
magnetospheric field-aligned currents through the ionosphere as Hall and
Pedersen currents. Despite its importance in predictive investigations
of the magnetosphere - ionosphere coupling, the estimation of
ionospheric conductance in the auroral region is precarious in most
global first-principles based models. This impreciseness in estimating
the auroral conductance impedes both our understanding and predictive
capabilities of the magnetosphere-ionosphere system during extreme space
weather events. In this article, we address this concern, with the
development of an advanced Conductance Model for Extreme Events (CMEE)
that estimates the auroral conductance from field aligned current
values. CMEE has been developed using nonlinear regression over a year's
worth of one-minute resolution output from assimilative maps,
specifically including times of extreme driving of the solar
wind-magnetosphere-ionosphere system. The model also includes provisions
to enhance the conductance in the aurora using additional adjustments to
refine the auroral oval. CMEE has been incorporated within the Ridley
Ionosphere Model (RIM) of the Space Weather Modeling Framework (SWMF)
for usage in space weather simulations. This paper compares performance
of CMEE against the existing conductance model in RIM, through a
validation process for six space weather events. The performance
analysis indicates overall improvement in the ionospheric feedback to
ground-based space weather forecasts. Specifically, the model is able to
improve the prediction of ionospheric currents which impact the
simulated dB/dt and \selectlanguage{greek}Δ\selectlanguage{english}B, resulting in substantial improvements in dB/dt
predictive skill.%
\end{abstract}%



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