Surface information derived from exospheric measurements at planetary bodies complements surface mapping provided by dedicated imagers, offering critical insights into surface release processes, dynamics of various interactions within the planetary environment, erosion, space weathering, and planetary evolution. This study explores a method for deriving the elemental composition of Mercury’s regolith from in-situ measurements of its neutral exosphere using deep neural networks (DNNs). We present a supervised feed-forward DNN architecture—a network of fully-connected neural layers, the so-called multilayer perceptron (MLP). This network takes exospheric densities and proton precipitation fluxes, derived from a simulated orbital run through Mercury’s exosphere, as inputs and predicts the chemical elements of the surface regolith below. It serves as an estimator for the surface-exosphere interaction and the processes leading to exosphere formation, including micrometeoroid impact vaporization, ion sputtering, photon-stimulated desorption, and thermal desorption. Extensive training and testing campaigns demonstrate the MLP DNN’s ability to accurately predict and reconstruct surface composition maps from simulated exospheric measurements. These results not only affirm the algorithm’s robustness but also illuminate its extensive capabilities in handling complex data sets for the creation of estimators for modeled exospheric generation. Furthermore, the tests reveal substantial potential for further development, suggesting that this method could significantly enhance the analysis of complex surface-exosphere interactions and reduce uncertainties in planetary exospheres models. This work anticipates the analysis of data from the SERENA (Search for Exospheric Refilling and Emitted Natural Abundances) instrument package aboard the BepiColombo Mercury Planetary Orbiter, with its nominal phase starting in 2026.

The electromagnetic coupling between the Galilean satellites at Jupiter and the planetary ionosphere generates an auroral footprint, whose ultimate source is the relative velocity between the moons and the corotating magnetospheric plasma. The footprint can be detected in the infrared L band (3.3-3.6 microns) by the Jovian InfraRed Auroral Mapper (JIRAM) onboard the Juno spacecraft, which can observe the footprint position with high precision. Here, we report the JIRAM data acquired since August 27th 2016 until May 23rd 2022, corresponding to the first 42 orbits of Juno. The dataset is used to compute the average position of the footprint tracks of Io, Europa and Ganymede. The result of the present analysis can help to test the reliability of magnetic field models, to calibrate ground-based observations and to highlight episodes of variability in the footprint positions, which in turn can point out specific conditions of the Jovian magnetospheric environment.

In this work we present the detection of CH4 and H3+ emissions in the atmosphere of Jupiter as two well separated layers, located, respectively, at a tangent altitudes of about 200 km and 500-600 km above the 1-bar level. We studied the vertical distribution of the two species retrieving their Volume Mixing Ratio (VMR) and temperature simultaneously or allowing only one quantity to vary. From this analysis, it is not possible to firmly conclude if the observed H3+ and CH4 features are due to an increase of their VMR or rather to variations of the temperature of the two molecules. However, our retrieval indicates that CH4 is in non-Local Thermal Equilibrium (non-LTE) condition, considering that the retrieved temperature values at about 300 km, where the maximum CH4 concentration lies, is always about 100 K higher than the Galileo measurements. We suggest that vertically propagating waves is the most likely explanation for the observed VMR and temperature variations in the JIRAM (Jovian InfraRed Auroral Mapper) data. Other possible phenomena could explain the observed evidences, for example a dynamical activity driving chemical species from lower layers towards the upper atmosphere, like the advection-diffusion processes responsible for the enhancement observed by Juno/MWR (MicroWave Radiometer), or soft electrons precipitation, although a better modeling is required to confirm these hypothesis. The characterization of CH4 and H3+ species, simultaneously observed by JIRAM, offers the opportunity for better constraining the atmospheric models of Jupiter and understanding the planetary formation.

We present multi-wavelength measurements of the thermal, chemical, and cloud contrasts associated with the visibly dark formations (also known as 5-µm hot spots) and intervening bright plumes on the boundary between Jupiter’s Equatorial Zone (EZ) and North Equatorial Belt (NEB). Observations made by the TEXES 5-20 µm spectrometer at the Gemini North Telescope in March 2017 reveal the upper-tropospheric properties of 12 hot spots, which are directly compared to measurements by Juno using the Microwave Radiometer (MWR), JIRAM at 5 µm, and JunoCam visible images. MWR and thermal-infrared spectroscopic results are consistent near 0.7 bar. Mid-infrared-derived aerosol opacity is consistent with that inferred from visible-albedo and 5-µm opacity maps. Aerosol contrasts, the defining characteristics of the cloudy plumes and aerosol-depleted hot spots, are not a good proxy for microwave brightness. The hot spots are neither uniformly warmer nor ammonia-depleted compared to their surroundings at p<1 bar. At 0.7 bar, the microwave brightness at the edges of hot spots is comparable to other features within the NEB, whereas they are brighter at 1.5 bar, signifying either warm temperatures and/or depleted NH3 at depth. Temperatures and ammonia are spatially variable within the hot spots, so the precise location of the observations matters to their interpretation. Reflective plumes sometimes have enhanced NH3, cold temperatures, and elevated aerosol opacity, but each plume appears different. Neither plumes nor hot spots had microwave signatures in channels sensing p>10 bars, suggesting that the hot-spot/plume wave is a relatively shallow feature.