We present a comprehensive study of the nightside discrete electron aurora phenomenon on Mars, utilizing observations from EMUS onboard EMM. The oxygen emission at 130.4 nm is by far the brightest FUV auroral emission line observed at Mars. We identify auroral pixels in OI 130.4 nm disk observations, with higher sensitivity than previously possible. Our statistical analysis reveals regional, SZA, local time, and seasonal dependencies of auroral occurrence. Higher occurrence of aurora is observed in regions of open magnetic topology and vertical crustal magnetic fields. Aurora occurs more frequently closer to the terminator and is more likely on the dusk versus dawn sides of the night hemisphere. A pronounced auroral feature appears close to midnight local times in the southern hemisphere, consistent with the “spot” of energetic electron fluxes previously identified in the MGS data. The auroral spot is more frequent after midnight than before. Additionally, some regions on Mars are “aurora voids” where essentially no aurora occurs. The non-crustal field aurora exhibits a seasonal dependence, with major enhancements around Ls 235° (near perihelion) and Ls 30°. This is in line with the seasonal variability in ionospheric TEC observed by Mars Express, which is in turn related to the variability of solar irradiance and thermospheric density. Aurora occurrence also shows an increase with the rise of Solar Cycle 25. These observations not only shed light on where and when Martian aurora occurs, but also add to our understanding of Mars’ magnetic environment and its interaction with the heliospheric environment.

Andrea C. G. Hughes

and 16 more

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.

Eryn Cangi

and 4 more

Eryn Cangi

and 2 more

Franck Montmessin

and 9 more