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The most direct evidence that the icy Galilean satellite Callisto is able to sustain a significant neutral exosphere dates back to the detection of the CO2 non-LTE emission at 4.3 μm wavelength, measured by the NIMS instrument onboard the NASA Galileo spacecraft [1]. Other exospheric emissions have been observed in the UV spectral range, basically tracing the ionised exospheric component ([2], [3]). The analysis of such emissions in the framework of exospheric models (see e.g. [4], [5]) allowed to establish an overall composition dominated by O2 and H2O, with minor contributions by CO2 and CO. However, direct observations of neutral species other than CO2 are still missing, and their actual abundances, as well as spatial and temporal variability, are poorly constrained.The MAJIS (Moon And Jupiter Imaging Spectrometer, [6]) instrument, on board the ESA JUICE spacecraft, is expected to contribute in this field, by searching for non-LTE emissions falling in its spectral range, from 0.50 to 5.54 μm. In particular, we evaluate the chance of detection of signals at the satellite’s limb emitted by the CO2 complexes at 4.3 μm and 2.3 μm, by the H2O complex at 2.3 μm, by O2 at 1.27 μm, and by the CO bands at 4.7 μm and 2.3 μm. We calculate the populations of molecular levels by using the GRANADA algorithm [7], then the emissions intensities, for reference abundances of the molecular species and for limb-viewing geometry, by taking advantage of the KOPRA algorithm [8].Detection limits for all the abovementioned species are obtained in the approximation of horizontal uniformity of exospheric layers and adopting a vertical scaling compatible with the scale height in [1]. Surface density detection limits around 6.2 .106 cm-3, 6.6 .106 cm-3, 3.4 .109 cm-3, 3.4 .107 cm-3 are found for CO2, H2O, O2, and CO respectively. For both CO2 and H2O, these results indicate a high detection probability during the Callisto flybys planned in the current JUICE trajectory version (crema 5.0, [9]). Detection of O2 could also be possible if appropriate observing strategies are adopted. Detection of CO is instead very challenging, being its expected abundance well below the detection limit. AcknowledgementsThis work is supported by the Italian Space Agency (ASI-INAF grant 2018-25-HH.0). IAA researchers acknowledge financial support from the State Agency for Research of the Spanish MCIU through the Center of Excellence Severo Ochoa" award to the Instituto de Astrofísica de Andalucía (CEX2021-001131-S/fund by MICIN/AEI/10.13039/501100011033).References[1] Carlson,R.W.,1999, Science 283 (5403): 820–21. [2] Kliore,A.J., 2002, Journ.Geophys.Res. doi: 10.1029/2002ja009365. [3] Cunningham,N.J. et al., 2015, Icarus. doi:10.1016/j.icarus.2015.03.021. [4] Vorburger,A., et al., 2015, Icarus. doi:10.1016/j.icarus.2015.07.035. [5] Liang, M., 2005, Journ.Geophys.Res. doi:10.1029/2004je002322. [6] Guerri I., et al., 2018, Proc.of SPIE Vol.10690 106901L-1. doi: 10.1117/12.2312013. [7] Funke,B., et al., 2012, Journ.Quant.Sp.Rad.Tran. doi:10.1016/j.jqsrt.2012.05.001. [8] Stiller,G.P., et al., 2002. Journ.Quant.Sp.Rad.Tran. doi:10.1016/s0022-4073(01)00123-6. [9] ESA SPICE Service, JUICE Operational SPICE Kernel Dataset, doi:10.5270/esa-ybmj68p.

Aqueous alteration minerals are high-value scientific targets and potential resources for future exploration. In particular, they are key drivers in the selection of contemporary and upcoming landing sites at Mars. Here we report on the “MOCAAS” (Mars Orbital Catalog of Aqueous Alteration Signatures) project, a 10-year endeavor which built a comprehensive high-resolution repository of aqueous minerals on Mars. Our project goals include: 1) providing a statistically meaningful global approach to aqueous minerals, 2) providing regional mineralogical context to better understand specific sites of interest, 3) identifying new high-science merit aqueous alteration mineral deposits, including as prospective landing sites, 4) providing groundwork for upcoming quantification work on the global inventory of volatiles sequestered in such minerals. A corollary are identifying sites which abundant aqueous alteration minerals provide ISRU opportunities for future human exploration. We will present the first global-scale analyses of our detection sample, our benchmark of the methodology on rover landing sites, and discuss limitations, biases and perspectives. We processed a large fraction of the OMEGA/Mars Express and CRISM/MRO datasets [Bibring+04; Murchie+07] which both allow retrieval of Mars surface reflectance in the [1.1-2.65] µm range used in this study. Their processing is described in [Carter+22] and yields aqueous alteration mineral detection (AMD) all over Mars. An AMD is a cluster of (nearly) contiguous pixels which we ascertained to contain similar spectral rationale for one or several aqueous minerals, to the sensibility limit of orbital near-infrared spectroscopy and observation spatial sampling. We combine several approaches that are systematic and semi-automatic as well as more refined manual investigations of individual observations from OMEGA and CRISM. Only confirmed AMDs are retained in the end which spectral content has been visually validated. We then further classify AMDs into 5 spectral-mineral classes: 1) Fe/Mg phyllosilicate clay, 2) Hydrous aluminosilicates and hydrated silica, 3) Poly/Semi-hydrated sulfate salts, 4) Mono-hydrated sulfate salts, and 5) Carbonates. These classes account for degeneracies in the diagnostic spectral features which cannot always be uniquely attributed to a given alteration mineral. Excluding polar latitudes, a large fraction of the Mars surface mineralogy has been surveyed at a sampling down to 200 m/pixel (>62% of the surface) using semi-automatic algorithms, and its near entirety at kilometric resolution. Candidate AMDs were then further investigated in detail at all resolutions. The total fraction of AMDs reported at Mars is ~1%, yet this fraction includes many terrains that exhibit surface dust, poor observational conditions, and are younger than the late Hesperian. Figure 1 provides the global distribution color-coding for spectral mineral classes which is seen to strongly correlate with the oldest, dust-poor terrains of Mars. Figure 1: Distribution of aqueous alteration mineral detections based on the OMEGA and CRISM datasets. Each color codes for the spectral mineral classes (Red: Fe/Mg phyllosilicates; Green-blue: sulfate salts; Orange: carbonates; Cyan: aluminosilicates or hydrated silica). Each color pixel here indicates that alteration minerals are present within a 4x4km² area. Preliminary analyses of the global distribution of aqueous alteration minerals will be presented, investigating distribution as a function of latitude, altitude, unit type and unit age. An example histogram of the distribution of aqueous minerals as a function of unit age is shown in Figure 2. In particular, we report the much more widespread occurrence of several types of aqueous minerals throughout the Noachian highlands of Mars compared to what was previously known. Figure 2: preliminary statistics on the distribution of alteration minerals, as a function of their unit-age from [Tanaka+14]. Our detection capability is then benchmarked by implementing the same mapping procedure but applied to well-studied candidate or current landing sites for rover missions: at Gale crater, Jezero Crater, Mawrth Vallis plateaus and Oxia Planum. For these, we generate local high resolution maps, for which an example is given at Jezero crater below. Figure 3: High resolution aqueous alteration mineral mapping of the surroundings of Mars 2020 in Jezero crater. We will discuss perspectives for both global analyses of aqueous minerals made possible by this catalogue (e.g. [Riu+22]), as well as regarding future studies of newly identified sites of interest for which we will present a sample. In the near-term, the MOCAAS catalogue of aqueous alteration minerals will be made available on the PSUP portal (psup.ias.u-psud.fr) as well as through a dedicated web portal. References: [Bibring+04] J.-P. Bibring et al., ESA Spec. Pub, 2004, https://ui.adsabs.harvard.edu/abs/2004ESASP1240...37B; [Murchie+07] S. Murchie et al., JGR, 2007, 10.1029/2006JE002682 ; [Carter+22] J. Carter et al., Icarus, under revision ; [Tanaka+14] K. Tanaka et al., 2014, http://pubs.er.usgs.gov/publication/sim3292 ; [Riu+22] L. Riu et al., this conference.

In the past decades, numerous hydrated silicates have been detected at the surface of Mars from orbital and in situ characterization. Understanding the hydrated mineralogy of Mars constitutes an important goal to retrace its water history and to evaluate its resource assets in terms of water budget. In addition to providing information on the past aqueous subsurface and surface environments, the aqueous alteration minerals (e.g., secondary phases) have a major exobiological potential and are prospective resources for human exploration and in situ resource utilization (ISRU, [1]). As such they are key drivers in the selection of current and upcoming landing sites for robotic and human missions to Mars. With a more global and quantitative view of the altered mineralogy (as presented in [2]) the modal composition can be accessed and the water content stored in hydrated silicates present at/near the surface can be evaluated. By quantifying the content of each minerals at the hydrated sites, the estimation of the water content stored at the surface within these minerals is then quite straightforward. The global mineralogical maps of [2] were used. They were derived using the full dataset of the OMEGA instrument, where the global abundances of 11 hydrated silicates can be found: Fe-Mg dominated smectite, Al-smectite, AlSiOH, Opal, Mg-carbonates, Chlorite, Fe/Mg-Micas, Serpentine and Fe-hydroxide. A set of non-hydrated minerals is also included in the mixture but is not used to derive the water content as they do not contain OH or H2O. To evaluate the water content of each individual end-member, the potential chemical formula of each end-member was first evaluated and then the weight percent of H2O or OH in the formula was estimated. This methodology is based on [3]. Thus, for each end-member several estimations of the water content are computed. They depend on the selected formula (the exact formula being unknown at Mars) and on the estimated hydration state (being also unknown) of each mineral. Then, the abundance of each end-member in water content is evaluated by multiplying their abundance with their individual water weight percent and by summing at each location (i.e., each pixel of the map) all the resulting water contributions. The resulting global map of water content at a resolution of ~ 1 km per pixel at the equator is shown on Figure 1. The average content of water, based on the content stored in hydrated silicates, is estimated to be slightly above 5 wt%, with some rare occurrences > 20 wt% (examples of such occurrences are shown on Figure 1). These values are in good agreement with previous orbital estimations of the water content at Mars based on other estimations techniques ([4],[5]) that predicted 2-7 wt% on average at the surface. Figure 1 - Global map of water content (wt%) at Mars, as stored in hydrated silicates. The red arrows point at location of 100s km2 were the water content at the surface is consistently > 10 wt%. Three zoomed maps are shown to illustrate specific settings that provide a high-water content at the surface. The orange arrows and circles highlight the large deposits of Marwth Vallis, Nili Fossae and Meridiani Planum. The ongoing studies now aim at a detailed analysis of the water distribution in order to look for new regions with high past aquability (stable liquid water) potential and/or exobiological potential, if such locations exist. The map will be studied locally (see Figure 1) in combination with high resolution images in order to correlate the high-water content with their context and highlight new regions of interest. Incorporation of ground-truth knowledge from Perserverance at Jezero crater is foreseen so as to refine the mineral endmembers, and make abundance comparisons on the larger mineral units which will be sampled. References [1] Abbud-Madrid, A., et al. (2016). Mars Water In-Situ Resource Utilization (ISRU) Planning (M-WIP) Study 90. [2] Riu, et al. (2022). The M3 project: 3 – Global abundance distribution of hydrated silicates at Mars. Icarus 374, 114809. https://doi.org/10.1016/j.icarus.2021.114809 [3] Wernicke, L.J. & Jakosky, B.M. (2021). Martian Hydrated Minerals: A Significant Water Sink. J. Geophys. Res. Planets 126. https://doi.org/10.1029/2019JE006351 [4] Audouard, J., et al. (2014). Water in the Martian regolith from OMEGA/Mars Express: Mars 3 µm absorption and water mobility. J. Geophys. Res. Planets 119, 1969–1989. https://doi.org/10.1002/2014JE004649 [5] Milliken, R.E. et al. (2007). Hydration state of the Martian surface as seen by Mars Express OMEGA: 2. H 2 O content of the surface: HYDRATION STATE OF THE MARTIAN SURFACE. J. Geophys. Res. Planets 112. https://doi.org/10.1029/2006JE002853

The study of Jupiter’s atmosphere, its composition, evolution, distribution, structure, and dynamics around the planet, is of interest to the scientific community. Several missions, space observatories, and ground-based telescopes (even if limited by the telluric bands of water vapor), have studied Jupiter’s atmosphere. Some of them, such as Juno, the Hubble Space Telescope (HST), and the Very Large Telescope (VLT), continue providing information about the vertical structure and distribution of the atmosphere around the planet [1-3]. Although the main chemical composition of Jupiter’s atmosphere has been unraveled, many questions remain open, such as the global abundance of water, or the responsible chemistry for the coloration of the clouds [4]. Besides, a remarkable potential of VIS-NIR spectrometry for characterizing the composition and dynamics of planetary atmospheres has been demonstrated in the last years [5]. The next mission to the Jovian system from the European Space Agency (ESA) is the Jupiter Icy Moons Explorer (JUICE), to be launched in April 2023 with an arrival date on July 2031 [6]. One of the key scientific instruments onboard is the Moons And Jupiter Imaging Spectrometer (MAJIS), which will provide hyperspectral capabilities through two channels: VIS-NIR (0.5μm-2.35μm), and IR (2.25μm-5.54μm) [7]. We would like to perform simulations of different test cases with respect to the viewing geometries of MAJIS and assess its capabilities [8-9] to characterize the vertical structure of the Jovian atmosphere. For this purpose, we upgraded ASIMUT-ALVL, a Radiative Transfer (RT) code developed at BIRA-IASB, that has been extensively used to characterize Mars and Venus atmospheres [10-11]. During the implementation phase of the new Jupiter case in ASIMUT-ALVL, we applied the current knowledge of the physical and chemical characteristics of Jupiter, including the Rayleigh scattering contribution due to dominant atmospheric species, the refractive index of Jupiter’s atmosphere, and the Collision-Induced Absorption (CIA) due to H2-H2 and H2-He molecular systems. The typical temperature profile and atmospheric composition of Jupiter were retrieved from [12], although in our next studies we might use the CH4 abundance from the Volume Mixing Ratio (VMR) profile from [13], which is similar to that from [14]. The required line-lists were implemented from the HITRAN online database with line parameters adequate for an H2 and He dominant atmosphere, following the 2020 version release [15]. The extinction coefficient due to Rayleigh Scattering is obtained based on the calculation of its cross-section from [16], by considering the refractive indexes of H2 and He, obtained from the refractivities measured by [17] and [18], respectively. The atmospheric King correction factor is obtained from an adapted version of the formula of [19], considering the depolarization ratio of H2 as measured by [20]. To model the aerosols and hazes present in the atmosphere, we used the microphysical parameters defined by [21]. We validated the updated performances of ASIMUT-ALVL by individually comparing the main spectroscopic features of Jupiter’s atmosphere in the VIS-NIR range against KOPRA, an RT code originally developed for studying Earth’s atmosphere but later adapted to the atmospheres of Titan, Mars, and Jupiter [22]. We used the same geometry of observation, assuming solar occultations with a tangential altitude between 50km and 360km, a resolution of 0.3cm-1, a Signal-to-Noise Ratio (SNR) of 100, and an orbit around the planet of 5000km high. The mean difference in transmittance obtained between both models is below 3%. The next step was to validate our RT model against observational spectroscopic data, which was obtained from the Visible and Infrared Mapping Spectrometer (VIMS) observations during the Cassini flyby to Jupiter [23]. This imaging spectrometer consists of two channels: VIS (0.35µm-1.07µm) and IR (0.85µm-5.1µm). In this presentation, we will discuss the results we obtained from the complete validation of our RT model, and the perspectives for the future implementation of the performances and viewing geometries of MAJIS/JUICE. Acknowledgements We acknowledge the kind support of Gianrico Filacchione who provided the calibrated data of the VIMS/Cassini observations. This project also acknowledges the funding provided by the Scientific Research Fund (FNRS) through the Aspirant Grant: 34828772 MAJIS detectors and impact on science. References [1] Bolton, S.J., et al., Space Science Reviews, 2017. 213(1): p. 5-37.[2] Nichols, J.D., et al., Geophysical Research Letters, 2017. 44(15): p. 7643-7652.[3] Antuñano, A., et al., The Astronomical Journal, 2019. 158(3): p. 130 (28).[4] MAJIS Team, JUICE Definition Study Report, 2014.[5] Langevin, Y., et al., Lunar and Planetary Science Conference, 2014. No. 1777: p. 2493.[6] Grasset, O., et al., Planetary and Space Science, Vol. 78, pp. 1-21, 2013.[7] Piccioni, G. et al., International Workshop on Metrology for AeroSpace, IEEE, 2019. pp. 318-323.[8] ESA, Consolidated Report on Mission Analysis (CReMA), Tech. Rep. 5.0b23.1. https://www.cosmos.esa.int/web/spice/spice-for-juice[9] Cisneros-González, M. E. et al., Space Telescopes and Instrumentation in Proc. SPIE 2020, 11443, 114431L.[10] Vandaele, A.C., et al., Planetary and Space Science, 2015. 119: p. 233-249.[11] Vandaele, A.C., et al., Optics Express, 2013. 21(18): p. 21148-21161.[12] Moses, J.I., et al., Journal of Geophysical Research: Planets, 2005. 110(E8).[13] Sánchez-López, et al., Astronomy & Astrophysics, 2022. Forthcoming article (ArXiv:2203.10086).[14] Seiff, A., et al., Journal of Geophysical Research: Planets, 1998. 103(E10): 22857-22889.[15] Gordon, I.E., et al., Journal of Quantitative Spectroscopy and Radiative Transfer, 2022. 277: p. 107949.[16] Sneep, M., et al., Journal of Quantitative Spectroscopy and Radiative Transfer, 2005. 92(3): p. 293-310.[17] Peck, E.R. et al., Journal of the Optical Society of America, 1977. 67(11): p. 1550-1554.[18] Mansfield, C.R., et al., Journal of the Optical Society of America, 1969. 59(2): p. 199-204.[19] Tomasi, C., et al., Applied optics, 2005. 44(16): p. 3320-3341.[20] Parthasarathy, S., Indian Journal of Physics, 1951. 25: p. 21-24.[21] López-Puertas, M., et al., The Astronomical Journal, 2018. 156.4: 169.[22] Stiller, G.P., et al., Optical Remote Sensing of the Atmosphere and Clouds, SPIE 2000, 3501.[23] Brown, R.H., et al., Icarus, 2003. 164(2): p. 461-470.

Icy bodies are the most numerous and diverse bodies in the Solar System, but only a few have been visited yet by space probes. Some of these icy bodies, mostly giant planet satellites like Callisto, are called ocean worlds as they likely host most of the liquid water of our Solar System within sub-glacial oceans [Sotin & Tobie 2004]. The presence of liquid water under the icy crusts of these bodies raises questions relative to exobiology. In the coming years and decades, these ocean worlds will be the focus of major planetary science missions, firstly with JUICE (ESA, launch scheduled in April 2023) and Europa Clipper (NASA, launch scheduled in October 2024) which will be targeting the Galilean moons, then with still conceptual missions as we speak such as (i) Uranus Orbiter and Probe and (ii) Enceladus Orbilander. Despite not being the prime target of any of these missions, Callisto will be investigated by JUICE and Europa Clipper through multiple flybys. One way to get information about Callisto’s sub-glacial ocean is to look at the moon’s surface, which may highlight markers of past or current activity and could lift the veil on its chemical composition. Spectroscopy is a powerful technique for such study, especially in the near-infrared domain where spectral signatures of H2O-ices, silicates, salts are detectable. Consequently, in preparation for future infrared spectroscopic data, and specifically those of the infrared imaging spectrometer MAJIS of the JUICE mission, a ground-based campaign was led with an instrument sharing some similar and also complementary characteristics: SINFONI (SINgle Faint Object Near-infrared Investigation), which was mounted on the UT4 of the VLT at ESO. Here we present the results derived from the analysis and the modeling of four full-disk observations acquired with this instrument. SINFONI combines an integral field spectrometer operating with different gratings with an adaptive optics module [Eisenhauer et al. 2003]. Our four observations were performed using the H+K grating, ranging from 1.46 µm to 2.41 µm, with a spectral resolution R = 1.500, but each spectrum acquired was automatically resampled in order to get a spectral sampling of 5 x 10-4 µm. The campaign took place from January 2015 from March 2016, and the observations were acquired near the opposition to optimize the angular resolution with Callisto’s angular diameter close to 1.5 arcsec. As SINFONI’s field of view is 0.8 x 0.8 arcsec2 divided into 64 x 64 pixels, one observation actually corresponds to a mosaic of ten overlapping acquisitions, as described in a paper about Ganymede using the exact same technique [Ligier et al. 2019]. All in all, after removing the high solar incident angle pixels we could not recover after applying photometric corrections (basically all pixels above latitude 60°, north and south), our dataset covers approximately 70% of Callisto’s entire surface with a spectral and spatial sampling (~40 km/pix) which allow to detect and map the spectral absorptions that may exist in this wavelength range of the Callisto’s spectrum. Spatial resolution is in par with that of the partial Callisto mosaic from the NIMS imaging spectrometer of the NASA Galileo probe. The first results obtained concerns the physical properties of the moon’s surface directly derived from the reduction process and the photometric corrections; one obtains satisfactory results using the qualitative photometric model of Oren-Nayar, which is a generalization of the Lambertian model with the surface roughness (σ) as only additional parameter [Oren & Nayar 1994]. In the case of our study, the best results were obtained with ranging between 17° and 19° whatever the observation. These values are much lower than the values in the 30° – 45° range provided by previous studies [Buratti 1991, Domingue & Verbiscer 1997], however these values were obtained through the modeling of the solar phase curve via the Hapke model [Hapke 1984, Hapke 1986] using a combination of telescopic observations and Voyager data; the major differences between the approaches make the respective results hard to compare (our data are < 10° emergence angle). Our second result concerns the global shape and spectral signatures in the surface spectra: overall, they are much flatter and more distorted than those of Europa and Ganymede, especially the quite large 2-µm H2O-ice band. To the exception of crystalline ice absorptions at ~1.50 µm, ~1.57 µm, ~1.65 µm and the 2-µm band, Callisto does not show other clear signatures (figure 1). However, very subtle signature(s), like the one at ~2.21 µm (figure 1), might actually be observed and are being investigated to confirm the detection(s). If confirmed it could suggest the presence of hydrated materials like salts or silicates. We will address this point during the meeting. Figure 1: Comparison between Ganymede’s (blue) and Callisto’s (red) mean spectrum of the entire dataset. And lastly our third main result comes from spectral modeling, where both linear and non-linear unmixing were performed. Unlike previous studies on Ganymede and Europa [Ligier et al. 2019, Ligier et al. 2016], the linear model shows that all of Callisto’s spectra are satisfactorily modeled without needing any hydrated salt and that the only two constituents would be (i) a darkening agent, with abundances always exceeding 80% even for the iciest spectra, and (ii) multiple grain sizes of the crystalline form of H2O-ice, with an average abundance of 7% and exhibiting a strong latitudinal gradient for the smallest grains typical of the influence of the Jovian magnetospheric environment (figure 2). Such a low concentration overall of H2O-ice challenged us about the legitimacy of the linear unmixing approach, so we decided to run the Shkuratov non-linear unmixing model [Shkuratov et al. 1999]. Tests are ongoing but very preliminary results show that the overall concentration of the crystalline ice should be much higher than the 7% coming from the linear model and hence much more representative of what should be the surface composition of an icy satellite. By the time of the meeting, we will be able to present the final results of the study. Figure 2: Distribution of the smallest grains of crystalline ice.