Abigail R. Azari

Cassini's CHarge Energy Mass Spectrometer (CHEMS) instrument collected energetic plasma data from 2004 to 2017, including hundreds of observations of small‐scale nearly dispersionless “local” injection events into the inner magnetosphere. This study assesses whether these interchange‐like injections are a channel‐like structure still connected to the outer region or whether they are typically a small, isolated zone that is disconnected from the source location. We model these events with a simple azimuthal drift code, which evolves the injections forward in time around the equatorial plane of Saturn. The results are compared against Cassini observations if their predicted path intersected the Cassini spacecraft again within 0.25 R _s (Saturn radii). Our analysis of these events determined that out of the 816 events, only 243 injections intersected Cassini's trajectory again. By examining the CHEMS spectrogram data during these expected intersections, we found that a majority (186 injections, 77%) displayed an energy‐dispersion signature that aligned closely with the modeled dispersion pattern, indicating that the injections are of “channel‐like,” or radially extended (several R _S ) morphology. The nominal runs assumed a typical co‐rotation velocity, and while this worked for 93 (50%) of matching events, the other half required a slight adjustment (within 10%). Additionally, 38 events (20%) required a slight adjustment to the magnetic gradient‐curvature drift term. Estimates of this nature advance subsequent calculations of transport of energetic plasma to the inner magnetosphere of Saturn.

Disappearing solar wind events (DSWEs), intervals when the solar wind proton density <1 , represent one extreme of the Mars solar wind interaction. Using data from NASA's Mars Atmosphere and Volatile Evolution (MAVEN) mission from February 2016 to May 2024, 154 orbits across 90 unique days were identified. During these events, the solar wind kinetic energy flux had a median value of ∼0.08 and never exceeded 0.37 , whereas normal times have a median value twice as large (∼0.16 ) and maximum values exceeding 8 . In contrast, electromagnetic energy fluxes and solar ionizing irradiance remained near normal levels. Observations of and density and fluxes from MAVEN's SupraThermal and Thermal Ion Composition (STATIC) instrument were analyzed. During DSWEs, ion density and ion flux distributions are significantly restructured, consistent with expansion of Mars' ionosphere and induced magnetosphere. Ion escape rates are significantly reduced during DSWEs compared to normal solar wind conditions, with falling to ∼75% and to ∼88% of normal values (9.45 and 1.30 ions/s). DSWE ion fluxes binned by solar wind kinetic and solar ionizing irradiance followed the same empirical relations as under normal conditions, whereas DSWE ion fluxes were depleted relative to the background trend for solar wind electromagnetic energy. Thus, the observed decrease in ion escape is likely attributable to the reduced solar wind kinetic energy flux. These results suggest that even under extreme solar wind density reductions, Mars' ion escape remains mostly governed by the same background drivers as during normal times.

Prediction efficiency (PE) is a skill score that compares the data‐model metric of mean square error against the variance of the observations (i.e., using the average of the observed values as the “reference model” in the general skill score formula). This has proven to be highly useful for analysis using “continuous metrics”—those data‐model comparison techniques that employ the exact values of the observations and model results—especially when comparing the new model's performance against an existing model. Another major grouping of data‐model comparisons is “event detection analysis” in which all observational and numerical values are converted into a binary yes‐no categorization of being in or out of “event state.” There is, however, no equivalent skill score to PE within the event detection toolkit. This study proposes two such options, one based on the proportion correct metric and another based on the critical success index metric. Like PE, these new skill scores use the observations as the reference model, which provides complete independence of the reference model from the new model. It is demonstrated, reevaluating two space weather data‐model comparison studies, that these skill scores provide context for model evaluation that is unique to other existing metrics and valuable for the assessment, especially with respect to comparing the new model's performance against an existing model. Reference models in existing skill scores are based in part on the new model's performance against the data, which leads to ambiguous interpretation for intermodel comparison usage.

We investigate Martian electron aurora utilizing 130.4 nm auroral observations from the Emirates Mars Ultraviolet Spectrograph and IMF clock angle measurements and estimates from MAVEN. Analysis reveals that more than 5 R aurora occurrence in a given region can vary by up to a factor of seven with IMF orientation, generally highest for southward IMF and lowest for westward IMF, with higher auroral occurrence post‐dusk, decreasing toward and past midnight before increasing again toward dawn. A broad diversity of IMF and local time dependence of aurora occurrence is observed across Mars' crustal magnetic fields. The polarity of a given crustal field determines whether its field lines preferentially magnetically connect to dayside ionospheric or nightside magnetotail electron sources in the post‐dusk or pre‐dawn sectors. We thus establish a “source preference metric”, that is, the excess likelihood of aurora when likely magnetically connected to the nightside versus dayside. A wide range of source preferences are observed across the crustal field features, with some showing higher occurrence for night sources, day sources, or neither, often differently when in the post‐dusk or pre‐dawn sectors. A generally stronger nightside source preference is found for radially inward crustal fields in the predawn sector, and for weaker outward crustal fields in the post‐dusk sector. These results highlight the complex and dynamic nature of Mars' magnetic topology in controlling auroral electron access. Future studies integrating in situ electron measurements with synoptic and limb auroral imaging will further constrain the relative contributions of dayside and magnetotail electron populations to Mars' auroral processes.

The interaction between Jupiter's magnetosphere and the solar wind is not well‐constrained: while internal energetic plasma processes are thought to dominate plasma circulation, the solar wind nonetheless exerts significant control over the shape and scale of the whole structure. To better constrain this interaction, we derive new functional forms for Jupiter's magnetopause and bow shock using data from the Ulysses , Galileo , Cassini , and Juno missions and calibrated solar wind estimates from the Multi‐Model Ensemble System for the Heliosphere (MMESH). We design an empirical Bayesian model to estimate the locations of the boundaries using a Markov‐chain Monte Carlo (MCMC) algorithm, expanding our model to sample all times, not only boundary crossing events. The boundary surfaces which best describe the data are thus estimated without the need for a full, physics‐based magnetohydrodynamic (MHD) treatment of the Jovian magnetosphere and the additional assumptions required for such. The new magnetopause model exhibits significant polar flattening and dawn‐dusk asymmetry, and includes a narrowing of the magnetotail when compared to previous models. The new bow shock model is largely axisymmetric. Both boundary models describe surfaces which lie closer to Jupiter than previous models, which has important implications for the modern picture of Jupiter's dynamic magnetosphere and the expected science results of current and upcoming Jupiter‐bound spacecraft. Applying these models to Juno 's trajectory, we estimate that the spacecraft should be expected to spend of each orbit in the magnetosheath and of each orbit in the solar wind starting from Perijove 64 (PJ64, 21 July 2021).

The induced magnetosphere of Mars is highly dynamic, driven by both the upstream solar wind and the planet’s crustal magnetic fields. This variability can occur on timescales much shorter than a single spacecraft orbit, making it difficult to distinguish between spatial and temporal variations in the induced magnetosphere. In this study, we utilize simultaneous multipoint observations from the Mars Atmosphere and Volatile EvolutioN (MAVEN) and Tianwen-1 missions to investigate how the induced magnetosphere responds to dynamic changes in the solar wind. We report a magnetic reconnection event observed by MAVEN in the Martian magnetotail, occurring a few minutes after an interplanetary magnetic field (IMF) rotation observed by Tianwen-1 in the upstream solar wind. This reconnection event is characterized by clear Hall magnetic field signatures and high-speed ion jets, indicating the presence of a diffusion region. Our analysis of the change in the magnetic field morphology suggests that this reconnection was likely triggered by this IMF rotation, occurring during the resulting reconfiguration of the induced magnetosphere. This multipoint study demonstrates the important role of dynamic upstream solar wind conditions, particularly IMF rotations, in driving the plasma processes in the Martian magnetotail, contributing to our understanding of solar wind energy and momentum transfer and their roles in ion escape in Mars’s hybrid magnetosphere.

Mercury's small magnetosphere is embedded in the dynamic and intense solar wind environment characteristic of the inner heliosphere. Both the magnitude and orientation of the interplanetary magnetic field (IMF) significantly influence the solar wind‐magnetospheric interaction at Mercury, driving phenomena such as magnetic reconnection. The MErcury Surface, Space Environment, Geochemistry and Ranging (MESSENGER) spacecraft provided in‐situ magnetic field measurements of the solar wind, the magnetosheath, and the magnetosphere along each orbit. However, it is a challenge to directly assess the IMF's impact on Mercury's plasma environment due to the temporal separation between observations within the solar wind and the magnetosphere, especially in the absence of an upstream monitor. Here, we present a feedforward neural network (FNN) trained on a subset of magnetosheath observations to estimate the strength and orientation of the IMF upstream of the bow shock. Utilizing magnetosheath magnetic field, cylindrical spatial coordinates, and heliocentric distance measurements, the FNN predicts upstream IMF conditions with an score of 0.70 and mean averaged error of 5.3 nT, thereby greatly decreasing the temporal separation between IMF estimates and magnetospheric measurements throughout the MESSENGER mission. This approach yields IMF estimates for all magnetosheath data measured by MESSENGER, providing a useful tool for future investigations of the IMF impact on Mercury's magnetosphere. This method will be integrable with the dual‐spacecraft BepiColombo magnetosheath measurements, providing useful estimates of upstream IMF conditions particularly during the extended periods in which neither spacecraft sample the solar wind. Our results demonstrate the utility of machine learning techniques on advancing space science research.

Single spacecraft missions do not measure the pristine solar wind continuously because of the spacecrafts' orbital trajectory. The infrequent spatiotemporal cadence of measurement fundamentally limits conclusions about solar wind‐magnetosphere coupling throughout the solar system. At Mars, such single spacecraft missions result in limitations for assessing the solar wind's role in causing lower altitude observations, such as auroral dynamics or atmospheric loss. In this work, we detail the development of a virtual solar wind monitor from the Mars Atmosphere and Volatile Evolution (MAVEN) mission; a single spacecraft. This virtual solar wind monitor provides a continuous estimate of the solar wind upstream from Mars with uncertainties. We specifically employ Gaussian process regression to estimate the upstream solar wind and uncertainty estimations that scale with the data sparsity of our real observations. This proxy enables continuous solar wind estimation at Mars with representative uncertainties for the majority of the time since late 2014. We conclude by discussing suggested uses of this virtual solar wind monitor for statistical studies of the Mars space environment and heliosphere.

We examine the newly discovered phenomena of sinuous aurora on the nightside of Mars, using images of 130.4 and 135.6 nm oxygen emission measured by the Emirates Mars Mission EMUS ultraviolet spectrograph, and upstream measurements from the MAVEN and Mars Express spacecraft. They are detected in ∼3% of observations, totaling 73 clear detections. These emissions are narrow, elongated (1,000–6,000 km), cross Mars' UV terminator, and are oriented generally toward the anti‐solar point, clustering into north, south, east, and west‐oriented groups. Diverse morphologies are observed, though some spatial features, such as broad curves, may in some cases be due to temporal aliasing of aurora motion as each image is built up over 15–20 min. Sinuous aurora form away from Mars' strongest crustal magnetic fields and can be interrupted by moderate crustal fields. Sinuous aurora occurrence increases strongly with solar wind pressure, though brightness shows only a weak positive dependence on pressure. Interplanetary magnetic field (IMF) clock angle affects their occurrence and orientation: sinuous aurora show a broad range of orientations centered on the solar wind convection electric field (E_conv) direction and forming in the +E_conv hemisphere, although with moderate clockwise and counterclockwise average “twists” for westward and eastward IMF, respectively. From these features we infer a link between sinuous aurora and electron energization in Mars' magnetotail current sheet, where field geometry on the +E_conv side of the sheet is more organized and symmetric. Determination of specific triggering conditions for sinuous aurora requires further investigation.