Advancing Our Understanding of Martian Proton Aurora Through a Coordinated Multi-Model Comparison Campaign

Loading...
Thumbnail Image
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2023-10
Major/Subject
Mcode
Degree programme
Language
en
Pages
19
Series
Journal of geophysical research: Space physics, Volume 128, issue 10
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 proton aurora observation. All models are able to effectively simulate the general shape of 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 vs. 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.
Description
Funding Information: The MAVEN mission is supported by NASA through the Mars Exploration Program in association with the University of Colorado and NASA's Goddard Space Flight Center. The work of GG and BH was supported by the NASA Grant 80NSSC20K1348. CSW is funded by Austrian Science Fund (FWF) project P35954‐N. EK acknowledges support from the Academy of Finland (Decisions No. 348784 and No. 310444). VS and DB acknowledge the financial support of the Russian Science Foundation, Grant 22‐12‐00364. J‐CG acknowledges support from the PRODEX program of ESA managed with the help of the Belgian Federal Scientific Policy Office (BELSPO). This work utilized the RMACC Summit supercomputer, which is supported by the National Science Foundation (awards ACI‐1532235 and ACI‐1532236), the University of Colorado Boulder, and Colorado State University. The Summit supercomputer is a joint effort of the University of Colorado Boulder and Colorado State University. We would like to thank our collaborators on the MAVEN team, especially Meredith Elrod and Robin Ramstad, for their contributions in understanding the local Mars environment during the time period of interest. We would also like to acknowledge Majd Mayyasi for contributions to IUVS FUV data calibration using interplanetary hydrogen emissions during cruise and in orbit. Finally, we would like to thank the reviewers of this paper for their helpful feedback during the manuscript review process. Funding Information: The MAVEN mission is supported by NASA through the Mars Exploration Program in association with the University of Colorado and NASA's Goddard Space Flight Center. The work of GG and BH was supported by the NASA Grant 80NSSC20K1348. CSW is funded by Austrian Science Fund (FWF) project P35954-N. EK acknowledges support from the Academy of Finland (Decisions No. 348784 and No. 310444). VS and DB acknowledge the financial support of the Russian Science Foundation, Grant 22-12-00364. J-CG acknowledges support from the PRODEX program of ESA managed with the help of the Belgian Federal Scientific Policy Office (BELSPO). This work utilized the RMACC Summit supercomputer, which is supported by the National Science Foundation (awards ACI-1532235 and ACI-1532236), the University of Colorado Boulder, and Colorado State University. The Summit supercomputer is a joint effort of the University of Colorado Boulder and Colorado State University. We would like to thank our collaborators on the MAVEN team, especially Meredith Elrod and Robin Ramstad, for their contributions in understanding the local Mars environment during the time period of interest. We would also like to acknowledge Majd Mayyasi for contributions to IUVS FUV data calibration using interplanetary hydrogen emissions during cruise and in orbit. Finally, we would like to thank the reviewers of this paper for their helpful feedback during the manuscript review process. Publisher Copyright: © 2023. The Authors.
Keywords
aurora, Mars, model, proton aurora, proton/hydrogen precipitation
Other note
Citation
Hughes, A C G, Chaffin, M, Mierkiewicz, E, Deighan, J, Jolitz, R D, Kallio, E, Gronoff, G, Shematovich, V, Bisikalo, D, Halekas, J, Simon Wedlund, C, Schneider, N, Ritter, B, Girazian, Z, Jain, S, Gérard, J C & Hegyi, B 2023, ' Advancing Our Understanding of Martian Proton Aurora Through a Coordinated Multi-Model Comparison Campaign ', Journal of geophysical research: Space physics, vol. 128, no. 10, e2023JA031838 . https://doi.org/10.1029/2023JA031838