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Convective vortices (whirlwinds) and dust devils (dust-loaded vortices) are one of the most common phenomena on Mars, observable on a daily basis. They reflect the local thermodynamical structure of the atmosphere and are the driving force of the dust cycle. Additionally, they cause an elastic ground deformation, which is useful for retrieving the subsurface rigidity. Therefore, investigating Martian convective vortices with the right instrumentation can lead to a better understanding of the Martian atmospheric structures as well as the subsurface physical properties. In this study, we quantitatively characterized the convective vortices detected by NASA’s InSight mission (~13,000 events) using both meteorological (e.g., pressure, wind speed, temperature) and seismic data. The evaluated parameters, such as the signal-to-noise ratio, event duration, asymmetricity of pressure drop profiles, and cross-correlation coefficient between seismic and pressure signals, are compiled as a catalog. To demonstrate how our catalog can contribute to scientific investigations, we show two analysis results about (i) asymmetrical features seen in the vortex-related pressure drops and (ii) atmospheric-ground interaction to retrieve the subsurface physical properties.

Aeolian activity, the movement of sand and dust by the wind, is common on Earth and has been observed on other planets [1]. Under the current climatic conditions on Mars, aeolian activity is the primary process of surface modification driven by winds, dust storms and wind vortices. Landed and orbiting cameras show that widespread aeolian activity occurs despite low measured and modelled winds, challenging Earth-based theories [2, 3]. Dust particles enter into long-term suspension forming global dust storms which drastically alter the Martian atmospheric dynamics and present hazards to robotic and human missions.Several models have been proposed on the long-standing conundrum of sediment transport on Mars, however, none of these have been verified on the planet. The outstanding question of what wind shear velocities mobilize sediments on Mars has remained elusive despite multiple spacecrafts carrying wind sensors and studying aeolian activity on finer spatial and temporal scales than can be achieved in orbit. Quantitative examination of aeolian activity under natural Martian surface conditions is imperative in validating transport models.The InSight lander has provided a unique opportunity for monitoring simultaneous coverage of aeolian activity on Mars by combining, for the first time, imaging with atmospheric, seismic and magnetic measurements. Previous studies spanned over just half of the first Martian year, from the end of northern winter to midsummer, and observed minor aeolian activity limited to sporadic grain motion and dust devil tracks [4, 5].In this study, we extend observations of aeolian activity for two Martian years, allowing us to infer the seasonal evolution at the landing site. We report a series of remarkable daytime vortex-induced events with pressure excursions up to 10 Pa, including an investigation of the burst in daytime vortices and emergence of nighttime vortices in northern autumn. Despite our observations reinforcing the quiescent aeolian surface environment at InSight, we observe further evidence and constrain timings of surface track formation, saltation, dust lifting and surface creep of coarser particles both on the surface of Mars and lander elements. Such an investigation was previously impossible due to power constraints allowing only intermittent meteorological measurements in the second year and wind-sensor saturation from energetic close vortex encounters that cause surface changes. Here, we derive estimates of vortex-induced peak wind speeds responsible for grain motion based on strong correlations from the excitation of high-frequency lander resonances sensitive to wind forcing measured continuously by the seismometers [6]. This wealth of data allows us to obtain a unique catalogue of complete wind-induced surface activity at InSight over two Martian years. Our findings provide an insight into the long-standing paradox of aeolian transportation on Mars by quantifying the environmental variables responsible for sand motion which help constrain current threshold and transport models.[1] Hayes (2018) Sci. [2] Kok et al. (2012) RPP [3] Newman et al. (2022) Auth. [4] Charalambous et al. (2021) JGR 126(6) e2020JE006538 [5] Baker et al., (2021) JGR [6] Charalambous et al. (2021) JGR 126(4) e2020JE006514.

Air temperature, ground temperature, pressure, and wind speed and direction data obtained from the APSS (Auxiliary Payload Sensor Suite) and HP3 radiometer (RAD) onboard the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) lander are compared to data from the Mars Regional Atmospheric Modeling System. A full diurnal cycle at four different seasons (Ls 0º, 90º, 180º and 270º) is investigated at the lander location at 4.5° N 135.6° E in Elysium Planitia on Mars (Figure shows comparison results for Ls 180º). This work extends the atmospheric observations perform by [1]. Model results are shown to be in good agreement with observations. The good agreement provides justification for utilizing the model results to investigate the broader meteorological environment of Elysium Planitia in a companion paper. The observed air temperature, pressure and winds are taken at ∼1m above ground, while MRAMS provides those values at the lowest atmospheric model level of ∼14 m. As expected, the MRAMS air temperature values at this height tend to be cooler than the observed in the morning and early afternoon, and then tend to be warmer in the late afternoon and through the night. Also, the difference in height should not have a large impact on wind direction, but modeled wind speeds at ∼14 m are faster than the observed at 1.5 m due to frictional effects. Small discrepancies in ground temperatures could be attribute to a different initialization of thermal inertia, dust and clouds in the model when compared with the data. The diurnal pressure amplitude at Elysium Planitia varies from 2.52% to 4.5% depending on the season. The total amplitude is then considerably smaller compared to Gale crater (up to ∼13%, [2]). [3] attributed the amplification at Gale due to a mesoscale hydrostatic adjustment process in regions of topographic slopes. We also use a Computational Fluid Dynamics (CFD) to study the mechanical disturb of the wind directions due to other instruments onboard the lander and it effect into the wind directions discrepancy between modeling and observations [4]. For low wind speeds (~3.4 m/s), there is an important mechanical contamination in the 330º-30º wind directions range for FM1 and in the 210-330º range for FM2 (Figure bottom left), mostly during nighttime. Figure 1. Observed and modeled diurnal air temperature, ground temperature, pressure, wind speed and wind direction signal at Ls 180. MRAMS are the black dots. InSight data taken within a few sols of the Ls 180 are shown in different colors, which each color representing data from a single sol. CFD results with the mechanical disturb (from the higher value -0- to the lower value -1.2-) of the wind directions due to other instruments onboard the lander for low wind speeds (~3.4 m/s) are shown in the bottom left.

International audience; In the midst of climate change, academic travels - one salient aspect of the carbon footprint of research activities - are at the center of a growing concern. Mitigation options often focus on two dimensions : (i) decreasing the frequency of attendance to conferences and (ii) modal shift in transport. Here, we analyze professional travel in academia from a unique database compiling about 100 000 travels from about 150 research labs across a large array of disciplines and localities in France to detail the structure, patterns and heterogeneity of national and international research travels for research purposes. We estimate the mitigation potential of a series of options encompassing but not limited to institutional options. We show that, if short distance traveling (typically below 1000 km) are largely dominant in number, their relative mitigation potential via modal shift is small (i.e., below 15%). On the other hand, long distance traveling, which is often associated with international collaborations or field work hold a much larger mitigation potential but question the very nature of research activities. We propose ambitious sobriety options to robustly decrease travel-induced GHG emissions in academia and discuss their acceptability in the context of the French public research system.

Despite the little insolation received by the ice giant planets, the stormy activity of their atmospheres is intense. Indeed Neptune has the strongest winds in the solar system, reaching 400 m/s in addition to being retrograde. What is the phenomenum responsible for this activity ? Interestingly, unlike the Earth, the species able to condense in the atmospheres of Uranus and Neptune, methane in particular, are heavier than the ambient air, essentially hydrogen. This property makes convection difficult to start [1,2]. Convection in these atmospheres should therefore be a regime of strong intermittence where convective energy can be stored for a long time before being released in short episodes. Our hypothesis is that this regime is at the origin of intense storms. Then, these storms could drive the intense winds observed on a global scale. To study this hypothesis, we use a "cloud-resolving" model. This model is built from a dynamical core (The Weather Research and Forecasting model), that has been initially developed for terrestrial applications and already adapted for simulations on Mars and Venus [3,4], coupled to independent physical parameterizations such as a radiative transfer. The high resolution of the model grid can allow us to highlight dry but also moist atmospheric convection, by resolving cloud formation and dissipation. We will present our implementation of methane cycle in this model and first moist simulations, and compare them with simple dry simulations, in order to reveal the impact of Methane cycle in tropospheric convection on Neptune. (1) Leconte J., Selsis F., Hersant F., Guillot T. (2017) Condensation-inhibited convection in hydrogen-rich atmospheres. stability against double-diffusive processes and thermal profiles for Jupiter, Saturn, Uranus, and Neptune Astron. Astrophys., 598 (2017), p. A98, 10.1051/0004- 361/201629140 (2) Hueso R, Guillot T, and Sánchez-Lavega A. (2020) Convective storms and atmospheric vertical structure in Uranus and Neptune. Phil. Trans. R. Soc. A 378: 20190476. http://dx.doi.org/10.1098/rsta.2019.0476 (3) Spiga, A., and F. Forget (2009), A new model to simulate the Martian mesoscale and microscale atmospheric circulation: Validation and first results, J. Geophys. Res., 114, E02009, doi:10.1029/2008JE003242. (4) Lefèvre, M., A. Spiga, and S. Lebonnois (2017), Three-dimensional turbulence-resolving modeling of the Venusian cloud layer and induced gravity waves, J. Geophys. Res. Planets, 122, 134–149, doi:10.1002/2016JE005146.

Uranus and Neptune have a tropopause, stratosphere and a thermosphere inexplicably too hot. This problem is called "Energy Crisis" [1,2]. Radio occultation measurements [3,4] and UV stellar and solar measurements [5,6] by Voyager 2 revealed that their stratosphere reach values of 150 K and their thermosphere reach values of 800 K. Globally-averaged temperature observations [7,8] have also shown a warmer stratosphere than expected. Current radiative equilibrium models can’t explain the observed temperatures [9,10], one or several unknown heat sources are necessarily responsible of this warm atmosphere. Thus, the nature of this or these heat sources is still an open question. To evaluate the role of several heat sources, we use the radiative-convective model developed by the Laboratoire de Météorologie Dynamique (LMD), previously used for the atmospheres of gas giant planets [11,12]. The model employs the correlated-k formalism to compute gaseous opacities from CH4, C2H2 and C2H6, opacities from collision-induced absorption (H2-H2, H2-He, H2-CH4, He-CH4 and CH4-CH4) assuming a H2 ortho/para fraction at equilibrium. Our model accounts for the internal heat flux, for multiple scattering and Rayleigh scattering. Cloud and aerosols physical properties (exctinction coefficient, single scattering albedo and asymmetry factor) are computed offline assuming Mie scattering, given a particle size distribution and optical constants. In the radiative-convective model, their optical depth is computed for each layer from several entry parameters: the total optical depth (at a reference wavelength), the boundary pressures (bottom and top of the layer), and an aerosol scale height [13]. Three hypotheses were explored separately to induce sufficient heating to warm the atmosphere. We varied the methane mole fraction profile, added an ad hoc aerosol layer, and imposed thermal conduction from the thermosphere. Values of observed methane molar fraction in the uranian stratosphere being scattered [14], a sensitivity study was carried out by varying the methane homopause altitude and the stratospheric molar fraction. As expected, a high molar fraction makes it possible to heat the stratosphere and to obtain a tropopause altitude similar to observations. Nevertheless, all tests failed to fully heat the tropopause. This is also expected, as much less solar photons in the near infrared reach these levels. Concerning thermal conduction from the thermosphere, the heating allows to obtain a temperature gradient in upper stratosphere similar to nominal temperature profile from [7]. However, simulated temperature profile is still colder (see figure 1). Simulations showed that temperature profile of Uranus was very sensitive to the addition of an optically thin aerosols layer confined to a few levels in the stratosphere. To obtain a sufficiently important stratospheric heating, this layer requires that the absorption spectrum is relatively intense in ultraviolet and thermal infrared. This type of spectrum is similar to tholins, black carbon or a carbon-NH3 mixture [15]. The relatively dark spectrum of this layer also induces greenhouse effect in the tropopause. In the case of Neptune, all hypothesis tested couldn’t warm stratosphere. Therefore, other heat sources are needed to explain observations, such as a dynamical forcing in stratosphere (...) and/or a coupling with thermospheric dynamics and/or auroral heating. Figure 1: Temperature profiles from our simulations and from observations [3,4,16] at the same latitude and solar longitude of Voyager 2 measurements. Blue curve corresponds to a simulation without aerosols, orange curve aerosolsmodel from [17] is added, and for green curve, we add a conduction from thermosphere with aerosols. Methane molar fraction profile from [14] is used on our simulations. Acknowledgements G. Milcareck, S. Guerlet and A. Spiga acknowledge funding from Agence Nationale de la Recherche (ANR) project SOUND, ANR-20-CE49-00009-01. References [1] Marley, M. S. and McKay, C. P. (1999). Icarus, 138.[2] Fletcher, L. N., de Pater, I., Orton, G. S., Hofstadter, M. D., Irwin, P. G. J., Roman, M. T., and Toledo, D. (2020). Space Science Reviews, 216.[3] Lindal, G. F., Lyons, J. R., Sweetnam, D. N., Eshleman, V. R., Hinson, D. P., and Tyler, G. L. (1987). Journal of Geophysics Research, 92.[4] Lindal, G. F. (1992). Astronomical Journal, 103.[5] Herbert, F., Sandel, B. R., Yelle, R. V., Holberg, J. B., Broadfoot, A. L., Shemansky, D. E., Atreya, S. K., and Romani, P. N. (1987). Journal of Geophysical Research, 92.[6] Broadfoot, A. L., Atreya, S. K., Bertaux, J. L., Blamont, J. E., Dessler, A. J., Donahue, T. M., Forrester, W. T., Hall, D. T., Herbert, F., Holberg, J. B., Hunten, D. M., Krasnopolsky, V. A., Linick, S., Lunine, J. I., Mcconnell, J. C., Moos, H. W., Sandel, B. R., Schneider, N. M., Shemansky, D. E., Smith, G. R., Strobel, D. F., and Yelle, R. V. (1989). Science, 246.[7] Orton, G. S., Fletcher, L. N., Moses, J. I., Mainzer, A. K., Hines, D., Hammel, H. B., Martin- Torres, F. J., Burgdorf, M., Merlet, C., and Line, M. R. (2014). Icarus, 243.[8] Fletcher, L. N., de Pater, I., Orton, G. S., Hammel, H. B., Sitko, M. L., and Irwin, P. G. J. (2014). Icarus, 231.[9] Greathouse, T. K., Richter, M., Lacy, J., Moses, J., Orton, G., Encrenaz, T., Hammel, H. B., and Jaffe, D. (2011). Icarus, 214.[10] Li, C., Le, T., Zhang, X., and Yung, Y. L. (2018). Journal of Quantitative Spectroscopy and Radiative Transfer, 217.[11] Guerlet, S., Spiga, A., Sylvestre, M., Indurain, M., Fouchet, T., Leconte, J., Millour, E., Wordsworth, R., Capderou, M., Bézard, B., and Forget, F. (2014). Icarus, 238.[12] Guerlet, S., Spiga, A., Delattre, H., and Fouchet, T. (2020). Icarus, 351.[13] Madeleine, J. B., Forget, F., Millour, E., Navarro, T., and Spiga, A. (2012). Geophysical Research Letters, 39.[14] Lellouch, E., Moreno, R., Orton, G. S., Feuchtgruber, H., Cavalié, T., Moses, J. I., Hartogh, P., Jarchow, C., and Sagawa, H. (2015). Astronomy and Astrophysics, 579.[15] Rizk, B. and Hunten, D. M. (1990). Icarus, 88.[16] Lindal, G. F., Lyons, J. R., Sweetnam, D. N., Eshleman, V. R., Hinson, D. P., and Tyler, G. L. (1990). Geophysical Research Letters, 17.[17] Irwin, P. G. J., Teanby, N. A., Fletcher, L. N., Toledo, D., Orton, G. S., Wong, M. H., Roman, M. T., Perez-Hoyos, S., James, A., and Dobinson, J. (2022). arXiv e-prints.

Previous CO2 ice cloud modeling studies [Colaprete et al., 2003, Tobie et al., 2003, Forget et al., 1998, Kuroda et al., 2013, Colaprete et al., 2008] allowed to develop and test ideas on CO2 ice cloud formation; however, the studies were often made in idealized settings and included simplified physics and/or limited model boundaries such as a low model top. Listowski et al. [2014] developed refined CO2 cloud microphysics adapted for the Martian conditions of a near-pure vapor condensing in highly supersaturated conditions [Listowski et al., 2013]. They showed with a one-dimensional model and a temperature structure including tidal and gravity wave effects that an additional source of condensation nuclei (CN) was required in the mesosphere for the formation of observed-like clouds. The model of Listowski et al. [2014] has now been coupled with the LMD Mars GCM (MGCM), jointly developed by several laboratories, including LATMOS, LMD, and IAA. The MGCM is now able to simulate the formation of CO2 ice clouds in the Martian atmosphere taking into account mineral dust particles and water ice crystals as potential condensation nuclei (CN). The first simulations are used for testing the new microphysics and comparing its results to the previous simplified CO2 condensation parameterization. The simulations are compared to the published CO2 ice cloud observations. We are using the most recent version of the MGCM and most of the included processes have been described in Navarro et al. [2014], including water ice cloud microphysics and their radiative effect. The new CO2 ice cloud microphysics follow closely the implementation of water ice cloud microphysics in the MGCM, performed via the so-called modal approach, frequently used in GCMs. This means that the particle size distribution is described assuming a lognormal form for the distribution and its evolution is described through the integral properties (moments) of the distribution. We have performed three simulations, one with the previous, simple parametrization of CO2 condensation, one with the new CO2 cloud microphysics but only including dust particles as CN, and one using both dust and water ice as CN, respectively called PARAM, MPCO2, and MPCO2+H2OCN. The simulations have been run for three Martian years and we take the results from the last simulation year to insure convergence. We use the climatological dust scenario that describes well an average Martian Year without a global dust storm. We use a spatial resolution of 5.6258° longitude x 3.758° latitude, corresponding to a 64 longitude x 48 latitude horizontal grid, and 32 vertical levels. The model top is defined at the pressure level 3x10-3 Pa that corresponds approximately to an altitude of 120 km. The model produces CO2 ice clouds in the polar regions in the troposphere during the winter and in the mesosphere at equatorial altitudes. Figure 1 shows the CO2 ice column density as a function of latitude and solar longitude for the two simulations: MPCO2 and MPCO2+H2OCN with observations from several instruments [Clancy et al., 2007, Montmessin et al., 2006, Määttänen et al., 2010,McConnochie et al., 2010, Scholten et al., 2010, Vincendon et al., 2011, Aoki et al., 2018, Clancy et al., 2019, Jiang et al., 2019, Liuzzi et al., 2021]. The polar clouds are formed in a larger altitude range than in the observations, reaching from the surface up to 40 km altitude. The polar atmosphere is cold and supersaturated in a deeper layer than in the observations, causing the thicker cloud formation that forms earlier and lasts longer. The cause of the colder polar winter troposphere may be the prescribed dust column depth coming from observations: as there are very few observations in the polar night, the column depth has been given a minimum value that might still be too high compared to reality. This larger dust content in the polar night causing a too large radiative cooling may be the reason for the cold temperatures. The snowfall from polar clouds contributes about 10% to the formation of the polar ice caps. Substantial mesospheric clouds only form when the model takes into account CO2 ice nucleation on both water ice crystals and dust grains. The seasonal distribution of the clouds agrees well with observations during most of the mesospheric cloud season, but the pause in cloud formation around the aphelion is more clear-cut than in the observations where cloud formation seems to continue during the whole cloud season, although at a lower frequency during a certain period around the aphelion. The clear pause in cloud formation in the model is due to the rise in mesospheric temperatures that seems to be related to a change in the circulation regime and winds in the mesosphere. The optical thickness of the clouds remains two orders of magnitude below observed values, pointing to a need for an exogenous CN source (meteoritic dust: [Listowski et al., 2014, Plane et al., 2018]). Such a source is being added to the model. Acknowledgements We thank the Agence National de la Recherche for funding (projet MECCOM, ANR18CE310013), the LabEx ESEP, CNES, PNP, and the Spanish Ministerio de Ciencia, Innovación y Universidades, the Agencia Estatal de Investigación and EC FEDER funds under project RTI2018-100920-J-I00, and the State Agency for Research of the Spanish MCIU through the Center of Excellence Severo Ochoa award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). This work was performed using HPC computing resources from GENCI/CINES (Grant 2021A0100110391), and resources at the ESPRI mesocentre of the IPSL institute.

The Saturn DYNAMICO Global Climate Model (GCM) is a high-resolution, multi-annual numerical simulation of Saturn's atmospheric dynamics [1], combining a radiative-convective equilibrium model [2] and a hydrodynamical solver on an icosahedral grid. The model reproduces well the observed behaviour of jets and eddy-momentum transfer to the mean flow. Vortices arise naturally in the model over time but until now they have not been given direct consideration. Here we investigate the long-term statistical distribution and organization of vortices using (1) a manual visual inspection method and (2) automated techniques that utilise machine learning and analytical calculations as a means of validating the first approach. Manual Detection This vortex detection method is similar to previous observational studies of Jupiter and Saturn [3, 4, 5, 6] and shows how the spatial and temporal distributions of the modelled vortices compares to those observed on Saturn [4, 5, 6], as well as studying the formation conditions and long-term temporal evolution of vortex distributions. With seven simulated model years at ½-degree spatial resolution, we constrain well the size and location of vortices, the horizontal wind field components and the magnitude and sign of horizontal vorticity, enabling direct comparison of the manual and automated methodologies. Automated Detection A convolutional neural network is used to reproduce the manual visual detection method across the entire timeseries using the same assumptions and using the results of the manual study as a training set. We also study the Angular Momentum Eddy Detection Algorithm (AMEDA, [7]) designed for the analysis of terrestrial oceanic eddies. The machine learning study is ongoing and the results of the AMEDA algorithm are largely consistent with the manual approach, meaning that this algorithm can be used in future studies of Jupiter and Saturn DYNAMICO GCM outputs. Figure 1: Vortex count over the entire mature model timeline for the manual (black) and AMEDA (red) approaches. Manual technique measures at each seasonal peak, AMEDA measures at each timestep to create a seasonal average for comparison. AMEDA analysis to be extended to earlier years. Figure 2: Vortex east-west size (left), north-south size (centre) and shape (right), in units of 103km, for the manual (top) and AMEDA (bottom) approaches. Figure 3: Overall distribution of vortices for entire timeseries with the manual (left subplot) and AMEDA (right subplot) approaches. In each subplot: (Left) histogram of total vortex count. (Centre) instantaneous zonal wind speed at the vortex centre with the mean zonal wind profile. (Right) vortex average size and vorticity sign. Figure 4: (Top) Maximum tangential velocity at vortex edge as a function of distance from the vortex centre (scatter), derived from the AMEDA approach, alongside the geostrophic balance condition (black straight line), all vortices are subgeostrophic. (Bottom) the ratio of vortex Vmax and the geostrophic condition as a measure of "vortex geostrophy", with respect to latitude, smaller and higher-latitude vortices tend to be clsoer to the geostrophic condition. Acknowledgements Donnelly and the France authors were supported by Agence Nationale de la Recherche (ANR) and the UK authors acknowledge the Science and Technology Facilities Council (STFC, James) and the European Research Council (ERC, Bardet). References [1] Spiga et al. (2020), Icarus, 335, http://dx.doi.org/10.1016/j.icarus.2019.07.011. [2] Guerlet et al. (2014), Icarus, 238, https://doi.org/10.1016/j.icarus.2014.05.010. [3] Li et al. (2004), Icarus, 172, https://doi.org/10.1016/j.icarus.2003.10.015. [4] Vasavada et al. (2006), J. Geophys. Res. Planets, 111, https://doi.org/10.1029/2005JE002563. [5] Trammell et al. (2014), Icarus, 242, https://doi.org/10.1016/j.icarus.2014.07.019. [6] Trammell et al. (2016), J. Geophys. Res. Planets, 121, https://doi.org/10.1002/2016JE005122. [7] Le Vu et al. (2018), J. Atmos. Ocean. Tech., 35, https://doi.org/10.1175/JTECH-D-17-0010.1

Titan, the largest satellite of Saturn, is known to host a rich and active meteorology, by all standards more dynamic than previously thought before the Cassini-Huygens mission. One key element of the dynamic Titan's atmosphere is the Planetary Boundary Layer (PBL), defined as the lowermost part of the atmosphere directly influenced by the presence of a surface below it. Turbulence in the PBL is a controlling factor for exchanges of momentum, heat, chemical species and aerosols between surface and atmosphere. Following observations by the Cassini-Huygens mission, a debate has arisen on the vertical extent of the PBL mixing on Titan in daytime conditions. Radio-occultations by Voyager and Cassini, as well as insights from dune spacing, indicate that a mixed layer, following the dry adiabatic lapse rate, extends 2 to 4 km above the surface. Conversely, in situ mid-morning measurements on board the equatorial Huygens descent probe suggests a more complex structure, with a clear-cut mixed layer only found to extend 300 m from the surface of Titan, with slope breaks between 2 and 4 km in the vertical temperature profile being related to PBL processes by some studies but not by others. The turbulent dynamics of Titan's PBL have been studied thus far either by Global Climate Models where mixing dynamics is parameterized rather than resolved, or by idealized Large-Eddy Simulations not coupled to realistic Titan physics and limited to the first hundreds meters above the surface. Here, to broaden the knowledge of Titan PBL processes, we present turbulent-resolving Large Eddy Simulations coupled with a realistic Titan radiative transfer and soil model, extended several kilometers above the surface and ran for the full daytime cycle of Titan environmental conditions. Using those new simulations, we are able to reconcile all existing observations in a single scenario of Titan PBL growth in daytime, from a couple hundreds of meters in mid-morning conditions to a 3 km fully-developed mixing layer in early afternoon conditions. We also explored turbulent statistics for Titan's PBL: sensible heat flux, updraft and downdraft intensity, wind gustiness. We also note the spontaneous occurrence of convective vortices (dustless devils) in our Titan Large-Eddy Simulations. Our new simulations for Titan PBL bears the potential to help rethink Titan weather processes close to the surface -- and their link to the aerosol / volatile cycles. Furthermore, basic knowledge on PBL turbulence on Titan is needed in the perspective of the Dragonfly spacecraft which will be directly flying within Titan's PBL, thereby experiencing its turbulent dynamics and carrying out in situ measurements of this turbulence.

International audience; Meteoroid impacts shape planetary surfaces by forming new craters and alter atmospheric composition. During atmospheric entry and impact on the ground, meteoroids excite transient acoustic and seismic waves. However, new crater formation and the associated impact-induced mechanical waves have yet to be observed jointly beyond Earth. Here we report observations of seismic and acoustic waves from the NASA InSight lander’s seismometer that we link to four meteoroid impact events on Mars observed in spacecraft imagery. We analysed arrival times and polarization of seismic and acoustic waves to estimate impact locations, which were subsequently confirmed by orbital imaging of the associated craters. Crater dimensions and estimates of meteoroid trajectories are consistent with waveform modelling of the recorded seismograms. With identified seismic sources, the seismic waves can be used to constrain the structure of the Martian interior, corroborating previous crustal structure models, and constrain scaling relationships between the distance and amplitude of impact-generated seismic waves on Mars, supporting a link between the seismic moment of impacts and the vertical impactor momentum. Our findings demonstrate the capability of planetary seismology to identify impact-generated seismic sources and constrain both impact processes and planetary interiors.

A recent work (Hernández-Bernal et al., 2021) described the Arsia Mons Elongated Cloud (AMEC), an impressive orographically generated cloud that appears next to the Arsia Mons volcano on Mars during the early morning on a daily basis in southern spring and summer. The most visually striking characteristic of this cloud is its extremely elongated shape.This spectacular cloud is formed by underlying dynamical and microphysical processes that remain to be elucidated. To that end, we run the LMD (Laboratoire de Météorologie Dynamique) MMM (Mars Mesoscale Model; Spiga and Forget, 2009) for Solar Longitude 270º, with a grid resolution of 10km. The model shows that the interaction of fast transient easterly winds with the summit of Arsia Mons results in strong ascending winds on the western slope of the volcano, seasonally and diurnally coincident with the occurrence of the AMEC according to observations. These ascending winds propagate vertically and result in a temperature drop which takes values of down to -30K in the hygropause (around 45 km over the areoid). This results in extreme relative humidity values and condensation, spatially coincident with what Hernández-Bernal et al. (2021) called the head of the AMEC. We expect advection by easterly winds to produce the particular elongated shape of the AMEC, however the advection of condensed particles is not clearly reproduced by the model.This AMEC study demonstrates that coupling the analysis of mesoscale modeling with imagery monitoring on elongated clouds help to better understand the involved processes to form the cloud. We aim to search for similar mechanisms in other visually resemblant clouds, like those reported by Clancy et al. (2006; 2021), and others observed by the Visual Monitoring Camera onboard Mars Express, among other imagers. In the meantime, the AMEC is expected to appear again in early June 2022 and different instruments are already planning observations.References:Hernández‐Bernal, Jorge, et al. "An extremely elongated cloud over Arsia Mons volcano on Mars: I. Life cycle." Journal of Geophysical Research: Planets 126.3 (2021): e2020JE006517. Spiga, Aymeric, and François Forget. "A new model to simulate the Martian mesoscale and microscale atmospheric circulation: Validation and first results." Journal of Geophysical Research: Planets 114.E2 (2009). Clancy, R. Todd, et al. "Valles Marineris cloud trails." Journal of Geophysical Research: Planets 114.E11 (2009). Clancy, R. Todd, et al. "Mars perihelion cloud trails as revealed by MARCI: Mesoscale topographically focused updrafts and gravity wave forcing of high altitude clouds." Icarus 362 (2021): 114411.

Numerous past observations of Saturn by ground based and space telescopes have monitored the movements of clouds and derived direct measurements of tropospheric wind speeds, giving insights into the tropospheric circulation of the planet. The most remarkable feature is a broad and fast equatorial prograde jet, reaching 400-450 m/s. Saturn's stratospheric dynamics is less well known. At low latitudes, it is characterized by the thermal signature of an equatorial oscillation: the observed thermal structure implies that there is a strong oscillating vertical shear of the zonal winds throughout the stratosphere, however, wind speeds in this region cannot be measured by cloud-tracking techniques and remain unknown.The objective of our study is to measure the stratospheric zonal winds of Saturn and unveil the circulation of this layer by observing it in the submillimeter range with the ALMA interferometer. For this, we observed the spectral lines of HCN at 354 GHz and CO at 345 GHz emitted from the limb of the planet. The pressure level at which we measure the winds is about 0.2 mbar. Thanks to the high spatial and spectral resolution of ALMA observations at 345 GHz, we measured the central frequencies of the emission lines in the whole limb, subtracted the rigid rotation of the planet, and thus derived the Doppler shift due to the atmospheric motions of the probed layer, i.e. the stratospheric winds. The method we used in this study was first developed to observe the stratospheric winds in Jupiter (Cavalié et al. 2021). Saturn's rings have limited our wind observations to latitudes north of 20°S. The zonal winds obtained in the eastern and western limbs are consistent within error bars. We most noticeably detected a very broad eastward jet that spreads from 20°S to 20°N with an average speed of exceeding 250 m/s.

To accurately simulate the climate and the fate of volatiles for thousands to millions of years we must couple physical processes with very different timescale, ranging from clouds microphysics and atmospheric dynamics (represented in the GCM) to the evolution of lakes, glacier accumulation, and subsurface ice evolution. Given the diversity and the complexity of the Martian paleoclimates, we choose to use use an ambitious “asynchronous coupling” between the slow ice and water reservoirs models and the GCM. In practice our innovative Mars evolution model will use a horizontal grid identical to that of the GCM, and include the same representation of the micro-climate on slopes. In our case, we will run the Mars Evolution Model with a timestep of 50 to ~500 years, depending upon the dynamics of the modeled system (smaller timesteps must first be used so that the different volatile reservoirs reach a quasi-equilibrium, then the timestep will depends on the evolution of the forcing, which is slow in the case of obliquity, for instance) . At each timestep, the inputs from the atmosphere (e.g. mean precipitation, sublimation and evaporation, temperatures, dust deposition) will be obtained through a multi-annual run of the Global Climate model using the outcome of the Mars Evolution Model as initial state.First results about evolution of water ice and CO2 ice glacier will be presented.

Our understanding of Venus and Mars climate has been noticeably improved thanks to progress with General Circulation Models (GCM) (e.g., Forget et al. 1999, Lebonnois et al. 2010, Gilli et al. 2021) and increasing measurements, both from space missions and ground-based telescopes. While there are 13 operational missions currently dedicated to Mars, a new era in the exploration of “our sister” planet Venus is coming in the next decades with the selection of 3 missions: DAVINCI and VERITAS by NASA, EnVision by ESA, in addition to the Indian orbiter mission, Shukrayyan-1 (planned for 2025). Nevertheless, our view of the upper layers of those planets (i.e., above approximately 80 km and 60 km on Venus and Mars, respectively) remains incomplete. The observed high variability of those regions (e.g., Gerard et al. 2014, Gonzalez-Galindo et al. 2015) is very challenging to predict by 3D models. Planetary waves (e.g., Kelvin waves) are suggested to play an important role in the variability in the so-called transition region on Venus (between super-rotation and day-to-night circulation) (Navarro et al. 2021) and gravity waves are recognized to produce a significant impact on the thermal tides of Mars (Gilli et al. 2020). In this talk, I will give a brief overview of recent 3D GCM developments done in collaboration with the Institut Pierre-Simon Laplace (IPSL) laboratories in France and the Instituto de Astrofisica de Andalucia (IAA) in Spain, such as the inclusion of a stochastic non-orographic gravity wave parameterization and improvements on the parameterization of non-LTE CO2 heating rates (Martinez et al. 2022, submitted), to provide a more realistic picture of those upper regions of the Venus and Mars atmosphere. References:Forget et al. 1999, JGR, 104, 155-24Lebonnois et al. 2010, JGR-Planets, 115, 6006Gilli et al. 2021, Icarus, Vol. 366, 114432Navarro et al. 2021, Icarus, Vol. 366, 114400Gilli et al. 2020, JGR-Planets, 125-3Gilli et al. 2017, Icarus, Vol.248, 478-498Gerard et al. 2014, Icarus, 236, 92-103Gonzalez-Galindo et al. 2015. JGR-Planets, 120, 2020-2035Martinez et al. 2022, submitted to Icarus Acknowledgments:GG is funded by the Spanish Ministerio de Ciencia, Innovación y Universidades, the Agencia Estatal de Investigación and EC-FEDER funds under project RTI2018-100920-J-I00, and acknowledges 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 (SEV-2017-0709). This research was also supported by Fundação para a Ciência e a Tecnologia (FCT) through the research grants UIDB/04434/2020, UIDP/04434/2020, P-TUGA PTDC/FIS-AST/29942/2017.

In some high latitude craters, intriguing moraines are interpreted to have been deposited by CO2 ice glaciers, essentially frozen from when the local climate was colder (i.e., when Mars obliquity was low) [1]. This scenario has been little studied, but it suggests that the atmosphere could totally collapse into CO2 glaciers, leaving behind a residual atmosphere of only Ar and N2, but 20 times less dense than today [2]. However, these results are based on a radiative equilibrium that does not take into account all the dynamics of the atmosphere. Such periods of low obliquities generally last tens of thousands of years [3], making a complete simulation with a classical Global Circulation Model impossible. We will present the preliminary results of our climate simulations of Mars at low obliquity based on our new tool which is the Planetary Evolution Model developed at the LMD (Fig 1.). This model allows us to simulate the evolution of the climate, based on the LMD GCM, over long-time steps. Particular attention will be paid to the condensation of the atmosphere in the form of CO2 glaciers, and to the composition of the residual atmosphere.Fig 1. Principles of the Planetary Evolution Model References: [1] Kreslavsky and Head, Carbon dioxide glaciers on Mars: Products of recent low obliquity epochs(?). Icarus, 216:111–115, 2011.[2] Kreslavsky and Head. Mars at very low obliquity: Atmospheric collapse and the fate of volatiles. Geophysical Research Letters, 32(L12202), 2005.[3] Laskar, Correia, Gastineau, Joutel, Levrard, Robutel, Long term evolution and chaotic diffusion of the insolation quantities of Mars. Icarus 170, 343–364, 2004.Acknowledgments:This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 835275).

Observations of the South Polar Residual Cap suggest a possible erosion of the cap, leading to an increase of the global mass of the atmosphere. We test this assumption by making the first comparison between Viking 1 and InSight surface pressure data, which were recorded 40 years apart. Such a comparison also allows us to determine changes in the dynamics of the seasonal ice caps between these two periods. To do so, we first had to recalibrate the InSight pressure data because of their unexpected sensitivity to the sensor temperature. Then, we had to design a procedure to compare distant pressure measurements. We propose two surface pressure interpolation methods at the local and global scale to do the comparison. The comparison of Viking and InSight seasonal surface pressure variations does not show changes larger than +-8 Pa in the CO2 cycle. Such conclusions are supported by an analysis of Mars Science Laboratory (MSL) pressure data. Further comparisons with images of the south seasonal cap taken by the Viking 2 orbiter and MARCI camera do not display significant changes in the dynamics of this cap over a 40 year period. Only a possible larger extension of the North Cap after the global storm of MY 34 is observed, but the physical mechanisms behind this anomaly are not well determined. Finally, the first comparison of MSL and InSight pressure data suggests a pressure deficit at Gale crater during southern summer, possibly resulting from a large presence of dust suspended within the crater.

International audience; The NASA InSight lander has recorded many pressure drops attributed to convective vortices during its first full year of data collection. However, although dust-carrying vortices (dust devils) are a common phenomenon on Mars, they have not been observed in InSight images. On Earth, magnetic signals associated with some dust devils have been reported. Data from the InSight Fluxgate Magnetometer (IFG) provide the first opportunity for similar investigations on Mars. Here, we evaluate whether magnetic signals are associated with daytime vortices. We incorporate observations of environmental conditions, measurements of ground tilt from seismic data, and data from the lander's solar panels, and consider the potential for dust-laden vortices to generate observable magnetic field signals. We find that 7.7% of pressure drop events greater than 1 Pa show a resolvable magnetic field signal at the time of the pressure drops. The resolvable magnetic signals, typically seen on the horizontal field components, are less than 1 nT in amplitude, and have no clear correlation with local time, duration, or pressure drop magnitude. During nine pressure drop events we found smoothly varying magnetic signals of at least 0.3 nT on any one component. To investigate the origin of these magnetic signals we evaluated three possible sources: solar array currents (SAC), ground and lander tilt, and triboelectric effects of lofted dust. We find that SAC and tilt could contribute a change in the magnetic field but cannot solely explain the observed signals. The observed changes in field strength could theoretically be produced via triboelectric effects, but only in the case of exceptionally large dust devils that pass close to the lander. The lack of imaged dust devils and the small number of observed magnetic signatures despite numerous measured pressure drops is consistent with at most a small proportion of dust laden convective vortices at InSight and associated predicted triboelectric effects.

NASA's InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission has operated a sophisticated suite of seismology and geophysics instruments on the surface of Mars since its arrival in 2018. On 18 February 2021, we attempted to detect the seismic and acoustic waves produced by the entry, descent and landing of the Perseverance rover using the sensors onboard the InSight lander. Similar observations have been made on Earth using data from both crewed(1,2) and uncrewed(3,4) spacecraft, and on the Moon during the Apollo eras(5), but never before on Mars or another planet. This was the only seismic event to occur on Mars since InSight began operations that had an a priori known and independently constrained timing and location. It therefore had the potential to be used as a calibration for other marsquakes recorded by InSight. Here we report that no signal from Perseverance's entry, descent and landing is identifiable in the InSight data. Nonetheless, measurements made during the landing window enable us to place constraints on the distance-amplitude relationships used to predict the amplitude of seismic waves produced by planetary impacts and place in situ constraints on Martian impact seismic efficiency (the fraction of the impactor kinetic energy converted into seismic energy)., Nature Astronomy, 6 (1), ISSN:2397-3366

In this study, we perform a detailed spectral analysis of the turbulent energy cascade using the in-situ observations by NASA's InSight lander on Mars. A recent study on the daytime Martian boundary layer using the InSight observations showed that the conventional Kolmogorov energy cascade of inertial sub-range fails to predict the spectral density of pressure. Here we extend this by investigating diurnal and seasonal variations in the spectral density of pressure, as the indicator of the Martian atmospheric turbulence. We show distinct spectral behaviours for the daytime and nighttime conditions. Moreover, we report the important effects of regional dust storms, gravity waves, bore and solitary waves on the turbulent energy cascade. Our results show that the presence of a dust storm and gravity wave activity can enhance the turbulence of the nighttime boundary layer of Mars despite the extreme stably stratified conditions compared to the terrestrial case.

Magnetic fields provide a window into a planet’s interior structure and evolution, including its atmospheric and space environments. Satellites at Mars have measured crustal magnetic fields indicating an ancient dynamo. These crustal fields interact with the solar wind to generate transient fields and electric currents in Mars’s upper atmosphere. Surface magnetic field data play a key role in understanding these effects and the dynamo. Here we report measurements of magnetic field strength and direction at the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) landing site on Mars. We find that the field is ten times stronger than predicted by satellite-based models. We infer magnetized rocks beneath the surface, within ~150 km of the landing site, consistent with a past dynamo with Earth-like strength. Geological mapping and InSight seismic data suggest that much or all of the magnetization sources are carried in basement rocks, which are at least 3.9 billion years old and are overlain by between 200 m and ~10 km of lava flows and modified ancient terrain. Daily variations in the magnetic field indicate contributions from ionospheric currents at 120 km to 180 km altitude. Higher-frequency variations are also observed; their origin is unknown, but they probably propagate from even higher altitudes to the surface. We propose that the time-varying fields can be used to investigate the electrical conductivity structure of the martian interior. The magnetic field measured by the InSight lander on Mars varies daily and is ten times stronger than expected. The field is inferred to originate from components of basement rocks magnetized by an ancient dynamo of Earth-like strength.

The InSight mission, featuring continuous high-frequency high-sensitivity pressure measurements, is in ideal position to study the active atmospheric turbulence of Mars. Data acquired during 1.25 Martian year allows us to study the seasonal evolution of turbulence and its diurnal cycle. We investigate vortices (abrupt pressure drops), local turbulence (frequency range 0.01-2 Hz) and non-local turbulence often caused by convection cells and plumes (frequency range 0.002-0.01 Hz). Contrary to non-local turbulence, local turbulence is strongly sensitive at all local times and seasons to the ambient wind. We report many remarkable events with the arrival of northern autumn at the InSight landing site: a spectacular burst of daytime vortices, the appearance of nighttime vortices, and the development of nighttime local turbulence as intense as its daytime counterpart. Nighttime turbulence at this dusty season appears as a result of the combination of a stronger low-level jet, producing shear-driven turbulence, and a weaker stability., 15 pages, 5 figures, accepted version of the manuscript published in GRL

The seismic noise recorded by the Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) seismometer (Seismic Experiment for Interior Structure [SEIS]) has a strong daily quasi-periodicity and numerous transient microevents, associated mostly with an active Martian environment with wind bursts, pressure drops, in addition to thermally induced lander and instrument cracks. That noise is far from the Earth’s microseismic noise. Quantifying the importance of nonstochasticity and identifying these microevents is mandatory for improving continuous data quality and noise analysis techniques, including autocorrelation. Cataloging these events has so far been made with specific algorithms and operator’s visual inspection. We investigate here the continuous data with an unsupervised deep-learning approach built on a deep scattering network. This leads to the successful detection and clustering of these microevents as well as better determination of daily cycles associated with changes in the intensity and color of the background noise. We first provide a description of our approach, and then present the learned clusters followed by a study of their origin and associated physical phenomena. We show that the clustering is robust over several Martian days, showing distinct types of glitches that repeat at a rate of several tens per sol with stable time differences. We show that the clustering and detection efficiency for pressure drops and glitches is comparable to or better than manual or targeted detection techniques proposed to date, noticeably with an unsupervised approach. Finally, we discuss the origin of other clusters found, especially glitch sequences with stable time offsets that might generate artifacts in autocorrelation analyses. We conclude with presenting the potential of unsupervised learning for long-term space mission operations, in particular, for geophysical and environmental observatories.

Titan's northern high latitudes host many large hydrocarbon lakes. Like water lakes on Earth, Titan's lakes are constantly subject to evaporation. This process strongly affects the atmospheric methane abundance, the atmospheric temperature, the lake mixed layer temperature, and the local wind circulation. In this work we use a 2D atmospheric mesoscale model coupled to a slab lake model to investigate the effect of solar and infrared radiation on the exchange of energy and methane between Titan's lakes and atmosphere. The magnitude of solar radiation reaching the surface of Titan through its thick atmosphere is only a few W/m2. However, we find that this small energy input is important and is comparable in absolute magnitude to the latent and sensible heat fluxes, as suggested in the prior study by S. Rafkin and A. Soto (Icarus, 2020). The implementation of a gray radiative scheme in the model confirms the importance of radiation when studying lakes at the surface of Titan. Solar and infrared radiation change the energy balance of the system leading to an enhancement of the methane evaporation rate, an increase of the equilibrium lake temperature almost completely determined by its environment (humidity, insolation, and background wind), and a strengthening of the local sea breeze, which undergoes diurnal variations. The sea breeze efficiently transports methane vapor horizontally, from the lake to the land, and vertically due to rising motion along the sea breeze front and due to radiation-induced turbulence over the land., Accepted in The Planetary Science Journal (08/2022)

The Venus Climate Database (VCD) is based on the outputs of our state-of-the-art Venus Global Climate Model (GCM) [1-3]. This tool, in the footsteps and spirit of its Martian equivalent, the Mars Climate Database (MCD) [4], is intended to be useful for engineers and scientists wanting to compare with their models, analyze observations or plan future missions. This project is funded by the European Space Agency, in the frame of preliminary studies for the EnVision mission to Venus. Overview of the Venus Climate Database The VCD provides mean values and statistics of the main meteorological variables (atmospheric temperature, density, pressure and winds) as well as atmospheric composition and related physical fields. It extends from the surface up to and including the thermosphere (~250km). The database contains high resolution temporal outputs (using 24 hourly bins) enabling a good representation of the diurnal evolution of quantities over a climatological Venusian day. Figure 1: Illustrative example of diurnal variations of the exospheric temperature retrieved from the VCD, compared to PV-ONMS temperature retrievals. VCD outputs In addition the main meteorological fields (atmospheric temperature, temperature, density, pressure and winds), the following outputs are available from the VCD: Altitudes with respect to the planet center, the reference sphere or above the surface Topography Astronomical quantities such as Venus Solar Longitude and distance to the Sun at any input Earth date Surface temperature (K) and pressure (Pa) Venusian hourly and day to day variability (RMS) of main meteorological fields Short Wave and Long Wave fluxes at any altitude Atmospheric scale height, mean molar mass, speed of sound, reduced gas constant, heat capacity, specific heat ratios and vicosity Volume mixing ratios and columns of CO2, CO, O2, O, H, H2, H2O, SO2, SO, OCS, O3, HCl, N2 and He An estimation of vertically integrated O2 nightglow VIRA (Venus International Reference Atmosphere) temperature, density and pressure at the same location VCD scenarios As the goal of the VCD is to provide information about the state of the Venusian atmosphere, various realistic settings have been used to run a series of baseline GCM simulations, namely: Simulations using various Extreme UltraViolet (EUV) input from the Sun, as this forcing influences significantly the thermosphere (~120km and above). In practice three cases (solar minimum, average and maximum) using fixed E10.7 forcings are provided. The user also has the possibility to obtain outputs corresponding to a chosen E10.7, which may either be specified as a set value or that corresponding to an actual Earth date. In these cases interpolation from the encompassing EUV scenarios is used to estimate the state of the system. To realistically bracket the state of the atmosphere below the thermosphere, which may vary with long-term changes (over time scales of many Venusian days) of the UV cloud albedo [5], along with the baseline case, two supplementary scenarios where that albedo is under and over-estimated are also provided. Figure 2: Illustrative example of temperature profiles retrieved from the VCD using the various EUV scenarios. VCD main features In addition to the aforementioned VCD scenarios, the following features are available: A “high resolution mode” : although the GCM simulations have been run at the resolution of a few degrees in longitude and latitude (3.75° x 1.875°), using some post-processing and a high resolution topography map (at 23 pixels/degree) to adjust the local pressure (and density). Access to the Venusian intra-hour variability (RMS) of main meteorological variables, as well as the Venusian day-to-day variability thereof, as estimated from the multiple Venus days of GCM simulations. The possibility to add perturbations to the climatological fields as: Small-scale perturbations, representative of gravity waves (which are unresolved in the GCM, but accounted for via adequate parametrizations [3]. Large-scale perturbations, representative of actual weather systems present in the GCM simulations. Figure 3: Illustrative example of wind profiles retrieved from the VCD, compared to Pioneer Venus Night probe observations Figure 4: Illustrative example of a climatological temperature profile, along with a perturbed one (using the small-scale perturbation scheme) and VIRA reference values. VCD maccess modes and availability At the time of writing this abstract, we are finalizing a prototype. We plan to release a first version of the VCD in September 2021. Based on our experience with the MCD, the VCD will be distributed as: A main Fortran subroutine that users can interface and directly call from their own software. Interfaces to call this gateway routine using other programming languages (e.g. C, Python, IDL, Matlab, …) will also be available. A web interface, based on the MCD one (at http://www-mars.lmd.jussieu.fr), for quick looks will be set up and maintained on http://www-venus.lmd.jussieu.fr Bibliography [1] S. Lebonnois et al. Wave analysis in the atmosphere of Venus below 100 km altitude, simulated by the LMD Venus GCM, Icarus, 278:38-51, 2016. [2] G. Gilli et al. Thermal structure of the upper atmosphere of Venus simulated by a ground-to-thermosphere GCM, Icarus, 281:55-72, 2017. [3] I. Garate-Lopez and S. Lebonnois. Latitudinal variation of clouds’ structure responsible for Venus’ cold collar, Icarus, 314:1-11, 2018. [4] The Mars Climate Database http://www-mars.lmd.jussieu.fr [5] Y. J. Lee et al., Long-term variations of Venus’ 365-nm albedo observed by Venus Express, Akatsuki, MESSENGER, and Hubble Space Telescope, Astron. J., 158:126, 2019.

Measurements from the InSight lander radiometer acquired after landing are used to characterize the thermophysical properties of the Martian soil in Homestead hollow. This data set is unique as it stems from a high measurement cadence fixed platform studying a simple well-characterized surface, and it benefits from the environmental characterization provided by other instruments. We focus on observations acquired before the arrival of a regional dust storm (near Sol 50), on the furthest observed patch of soil (i.e., ∼3.5 m away from the edge of the lander deck) where temperatures are least impacted by the presence of the lander and where the soil has been least disrupted during landing. Diurnal temperature cycles are fit using a homogenous soil configuration with a thermal inertia of 183 ± 25 J m

Since 30 years, an equatorial oscillation of the temperature structure with a quasi-period of 4 years has been discovered in the atmosphere of Jupiter (Orton et al. 1991, Leovy et al. 1991). This phenomenon results in a complex vertical and horizontal structure of prograde and retrograde jets. However, the wind structure of the stratosphere in the equatorial zone of Jupiter has not been measured directly. It has only been inferred in the tropical region from the thermal wind balance using temperatures measured in the jovian stratosphere and the cloud-top wind speeds measured as a initial condition (e.g. Flasar et al. 2004). But temperatures are not constrained between the upper troposphere and the middle stratosphere from observations, limiting thus the accuracy of the thermal wind balance. In this study, we derive self-consistently for the first time the structure of the tropical winds by utilizing wind and temperature observations all performed in the stratosphere. The wind speeds were obtained by Cavalié et al. (2021) at 1 mbar in Jupiter's stratosphere in both the equatorial and tropical regions in March 2017 with ALMA. The stratospheric thermal field was measured a few days before from the equator to the mid-latitudes with Gemini/TEXES (Giles et al. 2020). For the derivation of the wind, we use both the thermal wind equation (Pedlosky 1979) and the equatorial thermal wind equation (Marcus et al. 2019). In this paper, we will present and discuss our results.

Saturn's cloud-top zonal winds have been measured since the Voyager days. Contrary to Jupiter, the jets are mostly prograde and with a noticeable broad super-rotating jet between 35°S and 35°N with peak velocities reaching ~450 m/s between 10°S and 10°N (e.g. Sanchez-Lavega et al. 2000). The Cassini mission revealed, during its Grand Finale, that these winds extend as deep as 8000 km below the clouds (Galanti et al. 2019). Above the tropopause, in the stratosphere, there has been no direct determination of the zonal winds, although thermal wind balance calculations have shown the signature of Saturn's semi-annual oscillation (SAO) in the tropical zone (Fouchet et al. 2008, Guerlet et al. 2011, 2018). These derivations lack an initial condition, in terms of wind speeds, located in the sensitivity zone of the temperature measurements. It thus remains unknown if the SAO jets alternate in direction as a function of altitude. In addition, more and more sophisticated general circulation models are being developed to constrain the dynamics of Saturn's stratosphere (Friedson & Moses 2012, Spiga et al. 2020, Bardet et al. 2021). These models now crucially need observational constraints. We used the Atacama Large Millimeter/submillimeter Array (ALMA) to map Saturn's stratospheric zonal winds. We derive the zonal winds as a function of latitude from the Doppler shifts induced by the winds on the spatially and spectrally resolved spectral lines. In this paper, we will present and discuss our results.

The surface pressure measurements recorded by InSight seem to be the best in terms of precision and stability for comparison with Viking data and to rule on a possible secular climate change. However, the comparison of the measurements between the two consecutive mission years reveals an offset imposed by the sensor temperature. We propose here a correction of this effect by exploiting the MSL REMS data acquired at the same time. The corrected data then follow perfectly the pressure models based on the pressure recorded by MSL during MY 34 and 35 interpolated with the help of the LMD GCM. Further investigations studying the possible difference between Viking 1 and InSight seasonal variations will be presented during the conference. Introduction Remote observations of interannual variations in polar cap coverage suggest that the south polar residual cap (SPRC) might be eroding [1,2,3]. Such a change in the SPRC would raise the surface pressure every year. Previous comparisons of surface pressures recorded by Viking 1 with Phoenix data [4] or MSL REMS measurements [5] report a possible increase of pressure at the surface of Mars within 30 years. However, the conclusions were unsure due to the uncertainty of the data for Phoenix, and the sensitivity of the hydrostatic adjustment imposed by the climbing of MSL on the complex Gale crater topography. In 2018, the InSight lander brought an accurate pressure sensor at Elysium Planitia. The uncertainty due to the long-term instrumental drift and the accuracy of the sensor is negligible compared to the requirement of accuracy to detect this secular climate change [4]. We thus propose to detect any change of CO2 mass in the atmosphere or a change in the seasonality of the polar cap with an accurate comparison between the seasonal pressure variations recorded by Viking 1 and InSight. Thermal Sensitivity of the Pressure SensorA direct comparison between pressure measurements made during the first and second years of the InSight mission shows a strong difference, thus questioning the reliability of the measurements (Figure 1). Considering the large difference between the measured pressure over the two years, and the correlation of some pressure decreases with some drops of the sensor temperature, we believe that the measurements are affected by a possible thermal offset due to a gradient of temperature within the sensor. Figure 1. (a) Uncorrected diurnal-averaged surface pressure recorded by InSight during the first and second years of the mission. (b) Diurnal-averaged pressure sensor temperature. Red dashed lines indicate the correlation between drops in the pressure measurements and drops in the sensor temperature records. Recalibration of the Pressure dataWe propose here an empirical calibration to correct this sensor thermal effect. To remove any meteorological effects (thermal tides, baroclinic waves), the measured pressure P is averaged over 10-sols to give < P >10sols. As reported in [6] who used MSL data, it seems that the pressure recorded at the beginning of the mission (Ls < 70°, MY = 35) could be slightly lower than the pressure recorded at the end of the mission (Ls < 70°, MY = 36), possibly as a result of the MY34 global dust storm. To quantify this difference, we interpolated the MSL REMS data available on the PDS with careful altitude corrections. Neglecting the difference of scale height between MY35 and MY36, one may have: Where: with E the thermal-induced offset on pressure data described previously. Assuming that E can be written as a polynomial function of the sensor temperature, and introducing (2) and (1) yield to a minimization problem that needs to be constrained to avoid any non-physical solution. Figure 1 presents an unexpected increase of uncorrected pressure at Ls~63°, and then a drop, both certainly resulting from a rise of temperature at T = 270K, followed by a decrease of temperature at T = 275K. Based on this observation, we simply assumed that: E(T = 0°C) = 0. With this constraint, the optimization problem can be solved and a first temporary correction is: Applying this correction to InSight measurements following Eq. (2) leads to the results presented in Figure 2. Figure 2. (a) Uncorrected diurnal-averaged surface pressure recorded by InSight during the first and second years of the mission. (b) Diurnal averaged pressure after sensor temperature correction following Eq. (2). Comparison of the Corrected Pressure and MSL MeasurementsTo assess the quality of this correction, we interpolate the MSL Measurements from MY35 et MY34 (assuming that MY34 behaves like MY36 for Ls < 70°) to predict the surface pressure at the InSight landing site. MSL measurements are interpolated to the InSight landing site using the hydrostatic correction presented in [7]. Dynamical effects from MSL to InSight landing site are corrected using GCM runs with MY34 and MY35 as input dust scenarios. The comparison is presented in Figure 3 and reveals a good match between the model and the result obtained after correction. Figure 3. Surface pressure as predicted from the interpolation of MSL REMS measurements, after hydrostatic and dynamic correction (dashed curves) and observations from InSight after thermal correction (crosses). Observations are diurnally-averaged whereas predictions are 10-sols averaged. Comparison of InSight and Viking 1 Surface Pressure The comparison between Viking 1 and InSight data after hydrostatic, dynamical, and temperature-induced offset will be presented during the talk. Interpretations and conclusions on a possible secular climate change will be drawn. References [1] Malin et al., 2001, Science294(5549), 2146–2148 [2] Thomas et al., 2009, Icarus203, 352–375 [3] Blackburn et al., 2010, Space Sci.58, 780–791 [4] Haberle and Kahre, 2010, Mars Int. J. Mars Sci. Explor5., 68–75 [5] Haberle et al., 2014, J. Geophys. Res., Planets119,440–453 [6] de la Torre Juarez et al., 2019, AGU fall meeting abstracts, Vol. 2019, p. P51C-02 [7] Forget et al., 2007, Planets112(E11), 8

International audience; We report the aeolian changes observed in situ by NASA's InSight lander during the first 400 sols of operations: Granule creep, saltation, dust removal, and the formation of dark surface tracks. Aeolian changes are infrequent and sporadic. However, on sols, when they do occur, they consistently appear between noon to 3 p.m., and are associated with the passage of convective vortices during periods of high vortex activity. Aeolian changes are more frequent at elevated locations, such as the top surfaces of rocks and lander footpads. InSight observed these changes using, for the first time, simultaneous insitu and orbital imaging and high-frequency meteorological, seismological, and magnetic measurements. Seismometer measurements of ground acceleration constrain the timing and trajectory of convective vortex encounters, linking surface changes to source vortices. Magnetometer measurements show perturbations in magnetic field strength during the passage of convective vortices consistent with chargedparticle motion. Detachment of sand-scale particles occurs when high background winds and vortexinduced turbulence provide a peak surface friction wind speed above the classic saltation fluid threshold. However, detachment of dust-and granule-scale particles also occurred when the surface friction wind speed remained below this threshold. This may be explained by local enhancement of the surface roughness and other effects described here and further studied in Part 2 (Baker et al., 2021). The lack of saltation and bright dust-coated surfaces at the InSight landing site implies surface stability and the onset of particle motion may be suppressed by dust "cushioning." This differentiates the InSight landing site from other areas on Mars that exhibit more aeolian activity. Plain Language Summary Aeolian activity, the movement of dust and sand by the wind, is common on Earth and has been observed on other planets, including Mars. A new Mars lander, InSight, has for the first time monitored aeolian changes by combining imaging with weather, seismic and CHARALAMBOUS ET AL.