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Advancing Our Understanding of Martian Proton Aurora through a Coordinated Multi-Model Comparison Campaign
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  • Andrea C. G. Hughes,
  • Michael Scott Chaffin,
  • Edwin J. Mierkiewicz,
  • Justin Deighan,
  • Rebecca Jolitz,
  • Esa Kallio,
  • Guillaume Gronoff,
  • Valery I. Shematovich,
  • Dmitry Bisikalo,
  • Cyril L. Simon Wedlund,
  • Jasper S. Halekas,
  • Nicholas M. Schneider,
  • Birgit Ritter,
  • Zachary Girazian,
  • Sonal Jain,
  • Jean-Claude M. C. Gérard,
  • Bradley Michael Hegyi
Andrea C. G. Hughes
NASA Goddard Space Flight Center / Howard University

Corresponding Author:[email protected]

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Michael Scott Chaffin
LASP
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Edwin J. Mierkiewicz
Embry-Riddle Aeronautical University
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Justin Deighan
LASP
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Rebecca Jolitz
Laboratory of Atmospheric and Space Physics
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Esa Kallio
Aalto University, School of Electrical Engineering
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Guillaume Gronoff
Nasa Langley Research Center
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Valery I. Shematovich
Institute of Astronomy of the Russian Academy of Sciences
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Dmitry Bisikalo
Institute of Astronomy of the Russian Academy of Sciences
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Cyril L. Simon Wedlund
Space Research Institute, OEAW
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Jasper S. Halekas
University of Iowa
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Nicholas M. Schneider
University of Colorado Boulder
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Birgit Ritter
Royal Observatory of Belgium
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Zachary Girazian
The University of Iowa
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Sonal Jain
LASP
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Jean-Claude M. C. Gérard
Université de Liège
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Bradley Michael Hegyi
NASA Langley Research Center
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Abstract

Proton aurora are the most commonly observed yet least studied type of aurora at Mars. In order to better understand the physics and driving processes of Martian proton aurora, we undertake a multi-model comparison campaign. We compare results from four different proton/hydrogen precipitation models with unique abilities to represent Martian proton aurora: Jolitz model (3-D Monte Carlo), Kallio model (3-D Monte Carlo), Bisikalo/Shematovich et al. model (1-D kinetic Monte Carlo), and Gronoff et al. model (1-D kinetic). This campaign is divided into two steps: an inter-model comparison and a data-model comparison. The inter-model comparison entails modeling five different representative cases using similar constraints in order to better understand the capabilities and limitations of each of the models. Through this step we find that the two primary variables affecting proton aurora are the incident solar wind particle flux and velocity. In the data-model comparison, we assess the robustness of each model based on its ability to reproduce a MAVEN/IUVS proton aurora observation. All models are able to effectively simulate the data. Variations in modeled intensity and peak altitude can be attributed to differences in model capabilities/solving techniques and input assumptions (e.g., cross sections, 3-D versus 1-D solvers, and implementation of the relevant physics and processes). The good match between the observations and multiple models gives a measure of confidence that the appropriate physical processes and their associated parameters have been correctly identified, and provides insight into the key physics that should be incorporated in future models.
18 Jul 2023Submitted to ESS Open Archive
23 Jul 2023Published in ESS Open Archive