We present the Venus Emissivity Mapper (VEM) onboard NASAs Venus Emissivity, Radio science, InSAR, Topography, And Spectroscopy (VERITAS) and ESAs (EnVision) Venus orbiter missions. The VEM instrument (on EnVision called VenSpec-M), is a multispectral imager for mapping of the Venus surface and its lower atmosphere. This is realized by observation through narrow-band atmospheric windows present in the nearinfrared spectral region around 1 mu m. For the first time, VEM will provide a global Venus coverage of > 70% with a high signal-to-noise ratio on the order of 100 to detect thermal emissions like volcanic activity, surface rock composition, water abundance and cloud formation. Since VEM for VERITAS and VenSpec-M for EnVision are being developed almost simultaneously, the instrument development approach can be made very efficient. By tailoring the science level, interface and environmental requirements of both missions to a joint requirements baseline, a single instrument design can be established. Focusing on the science requirement breakdown, this paper presents the key scientific requirements derived from VERITAS and EnVision and how they translate into verifiable technical instrument requirements. The VEM/VenSpec-M project is in its preliminary design phase. The instrument preliminary design review (PDR) is planned in 2025 for VERITAS and EnVision. Two flight models (FMs) are currently scheduled for delivery to the VERITAS S/C in 2028 and one FM to the EnVision S/C in 2029. First VEM/VenSpec-M data obtained from Venus orbit is expected after launch of the two missions currently scheduled in 2031.

Introduction: Given the extreme conditions in the lower atmosphere of Venus, various in-situ missions faced instrumental failures. As a result, the thermal structure of the deep atmosphere, particularly below 12 km is not well known. In Venus International Reference Atmosphere (VIRA), the thermal structure of the atmosphere below 12 km altitude was constructed by extrapolating the data recorded in the upper atmosphere. Only VeGa-2 lander provided the high-resolution temperature measurements below 12 km altitude. However, these measurements indicated a region of high instability below 7 km altitude. Due to a lack of physical explanation, these measurements were not included in VIRA. Methodology: In this study, we use the previous near-IR observations of Venus nightside to investigate the thermal structure of the deep atmosphere. First, a surface temperature map is generated from the near-IR observations. By correlating this map with surface topography a surface temperature vs altitude profile is generated. Assuming that the surface is in thermal equilibrium with the atmosphere [1], the surface temperature vs altitude profile then provides the thermal structure of the deep atmosphere. In the end, we compare the retrieved thermal structure with the VIRA and VeGa-2 temperature profiles. Data Processing: The near-IR observations from the VIRTIS instrument onboard the Venus Express and the IR1 imager onboard the Akatsuki orbiter are used in our study. The VIRTIS dataset has been already processed by [2] and contains the observations of the southern hemisphere having an altitude range below 4 km. The equatorial and northern highlands on Venus were observed by the IR1 imager. However, the IR1 observations are heavily contaminated by the bright straylight coming from the dayside of Venus. Also, the calibration had an uncertainty of±67%. To make use of the IR1data, we develop a correction procedure that includes (1) starylight correction, (2) limb darkening correction, and (3) cross-calibration using the VIRTIS data. Radiative Transfer: To retrieve the surface temperatures from the near-IR observations, we develop an atmospheric radiative transfer model based on the radiative transfer code from [3]. The atmosphere is constructed by using VIRA profiles. We use the cloud model from [4] and Mie scattering is treated by using the code from [5]. We model the absorption using the line-by-line code from [6] and considering eight major absorbing species. Appropriate spectral line dataset and lineshapes are used. To simulate the effect of topography on Venus, we generate the results in the form of a look-up table in which we vary the starting altitude of the atmosphere from -3 to 13 km altitude with respect to a 6051 km planetary radius. We validate our model based on the results generated by the model described in [7]. Results and Conclusion: The coverage of the VIRTIS and IR1 datasets can be observed from the maps of retrieved surface temperatures shown in Figure 1 and Figure 2. Figure 3 shows the trendlines of mean values of the deviation of surface temperature with respect to VIRA temperature profile against the altitude for both the dataset. The dotted line shows the deviation of the VeGa-2 profile. We find that the VIRTIS and IR1 temperature trendlines show a lapse rate lower than VIRA from 0 to 1.5 km altitude, as previously indicated by [8]. Above this altitude VIRTIS trendline follows the VIRA lapse rate, however, the observations are limited up to an altitude of 3.5 km. Above 2 km altitude, the IR1 temperatures fall even faster than the VeGa-2 profile and achieve a maximum deviation of∼5 K from the VIRA profile between 4-5 km and 7-8 km altitude range. This indicates that the situation could be even more complex than indicated by the VeGa-2 profile. Above 8 km altitude, the IR1 data is less reliable. The reasons behind the differences in the IR1, and VIRA profiles are not clear. Possible reasons could be surface emissivity variations, a near-surface layer of aerosols, or a composition gradient [9]. Thus, we find that both the VIRTIS and IR1 profile do not completely agree with either VIRA or VeGa-2 profile. However, observations from both VIRTIS and IR1 instruments were not ideal for the surface-emission studies. An optimized instrument could provide better coverage and quality of the data which could significantly help near-surface studies. Based on this, we highlight the need for future near-IR observations with an instrument optimized for the surface observing atmospheric windows of Venus. References: [1] Lecacheux, J., Drossart, P., Laques, P., Deladerriére, F., and Colas, F., Planetary and Space Science 41(7), 543–549 (1993). [2] Mueller, N., Helbert, J., Hashimoto, G. L., Tsang, C. C., Erard, S., Piccioni, G., and Drossart, P., Journal of GeophysicalResearch E: Planets 114(5), 1–21 (2009). [3] Wauben, W. M. F., De Haan, J., and Hovenier, J., Astronomy and Astrophysics -Berlin-282(1), 277–277 (1994). [4] Barstow, J. K., Tsang, C. C., Wilson, C. F., Irwin, P. G., Taylor, F. W., McGouldrick, K., Drossart, P., Piccioni, G., andTellmann, S., Icarus 217(2), 542–560 (2012). [5] De Rooij, W. and Stap, Van Der, C., Astronomy and astrophysics (Berlin. Print) 131(2), 237–248 (1984). [6] Stam, D. M., De Haan, J. F., Hovenier, J. W., and Stammes, P., Journal of Quantitative Spectroscopy and RadiativeTransfer 64(2), 131–149 (2000). [7] Tsang, C. C., Irwin, P. G., Taylor, F. W., and Wilson, C. F., Journal of Quantitative Spectroscopy and Radiative Transfer 109(6), 1118–1135 (2008). [8] Meadows, V. S. and Crisp, D., Journal of Geophysical Research: Planets 101(E2), 4595–4622 (1996). [9] Lebonnois, S. and Schubert, G., Nature Geoscience 10(7), 473–477 (2017).

Introduction: The composition of lava fields on Venus and their alteration state are poorly constrained. The Venus Emissivity Mapper (VEM) [1, 2] on board NASA’s VERITAS [3] and its twin VenSpec-M on ESA’s EnVision will observe the surface of Venus in the NIR range through five atmospheric windows covered by six spectral bands (0.86 to 1.2 µm). These will enable studying the spectral characteristics of the Venusian surface, as well as lava types and possible alteration processes. To prepare for these missions and deepen our understanding of the emissivity spectral characterization of various volcanic rocks, we developed a field camera system analogous to VEM, named “VEMulator2.0” [4], and have undertaken in-situ measurements during the VERITAS expedition in Iceland, early August 2023. We relate these data to emissivity spectra of field samples acquired in the Venus chamber at the Planetary Spectroscopy Laboratory (PSL) of DLR-Berlin [1].Iceland: The vegetation-free, geologically recent basaltic lava fields of Iceland make this area a prime Venus analog [5, 6]. Selected regions of interest for this campaign are [6]: Askja/Holuhraun in the highlands; Fagradalsfjall on the Reykjanes Peninsula. These ROIs offer a wide variety of surface textures, sand cover, and diverse fumarolic deposits, as well as macro- and micro- fractures. Fagadalsfjall is of particular interest for NIR team because of its very fresh lava flows (2021, 2022, and 2023), the still-cooling lava in the subsurface, and the recent fumarolic alteration products on the surface.In-situ NIR data acquisition: The VEMulator2.0 is an in-house built camera system equipped with an InGaAs detector – similar to the VEM flight model – and a filter wheel with six bandpass filters: 860, 910, 990, 1030, 1100, 1200 nm. A simpler version of this set-up had been successfully used in a field campaign in Vulcano, Italy [7]. In Iceland, data were collected in daytime (reflected sunlight) and at nighttime as emittance of the very hot (~100-480°C) lava flow at the active fissure of Litli-Hrutur.Reflectance data. The main goal here is to understand the NIR spectral response of different basaltic surfaces in the spectral range of VEM. The sites were selected based on their surface texture and mineralogy. The goal was to image varying surface textures as well as contacts between different materials, such as sand cover over the 2014-2015 Holuhraun lava field, fumaroles and their deposits of Holuhhraun and Fagradalsfjall, tephra mantled lava flows near Askja, very fresh surfaces of Fagradalsfjall’s 2021-2023 fields, and near surface alteration due to escaping hot gases (including water vapor), exposed via fractures.The imaged sites were scanned by the LiDAR team to obtain a high-resolution (millimeter-scale) DEM of the ROIs. These data will constrain surface geometry [8, 9]. GPS coordinates of the VEMulator location and the imaged targets have been collected, providing cm-scale precision on the camera-target distance. Two calibration targets were used in each imaged scene: one black surface as blackbody, and a gray disc. Both calibration targets were spectrally analyzed in the PSL laboratory before and after the field campaign, thus have known spectra that will help improving our data calibration processes.Emittance data. The main goal here was to collect in-situ emittance of a fresh lava flow in the NIR spectral range of VEM. We imaged the hot lava surface (approximately 100-480°C) of the active vent of Litli-Hrútur where an eruption terminated two days prior to our arrival to obtain in-situ emittance of the basaltic rock at Venus temperature, after sunset. We used a FLIR thermal camera to find the hot spots, in collaboration with colleagues at the Univ. of Iceland. This allowed direct observation of surface temperature and identification of several cracks where hot gases were escaping from the cooling lava. All these collected data will provide detailed spectral information and a deeper understanding of the surface composition of the studied lava flows.Sample collection. We collected samples from every imaged scenery by VEMulator. A total of ~60 kg of samples was transported to DLR in Berlin for post- processing and analyses using reflectance and emittance methods available there. All the samples are carefully labeled and stored in the sample collection laboratory at DLR-Berlin.Laboratory measurements: Bi-directional and hemispherical reflectance spectra from 0.7-2.63 μm were collected using the Bruker Vertex 80V spectrometer at the PSL in DLR-Berlin. The data will be related to the daytime field data to better understand the NIR spectral response of surface material using the six spectral bands. We will collect emissivity measurements using the Venus chamber at PSL, to correlate with the in-situ nighttime data collected from Litli-Hrutur 2023 lava field. In addition, various Icelandic basalt samples will be analyzed in the Venus chamber with the goal to expand our datasets of emissivity spectra of Venus-analog materials as part of the VEM calibration plan [10].Conclusion and future work: In the VERITAS expedition 2023 in Iceland, we collected in-situ NIR data using a Venus Emissivity Mapper (VEM) emulator (VEMulator2.0), and 60 kg of samples of Venus analog materials. The highlight of this work is the data we collected after sunset from the active fissure of Litli-Hrutur in the range of Venus surface temperature. We are currently analyzing the samples at PSL-DLR Berlin using the reflectance and emittance set-ups to correlate the laboratory data with the field data. This work will increase our understanding of emissivity of rock samples in hot temperature and will contribute in the VEM calibration plan.Acknowledgments: SA, SPG, NM, AD received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149. GC, EM was supported by NASA Planetary Science Division Research Program through the GSFC GIFT ISFM.References: [1] Helbert, J., et al. (2022) SPIE. [2] Helbert et al. (2024) LPSC 55. [3] Smrekar S. (2022) IEEE Aerospace Conf.. [4] Garland S. et al. (2024) EPSC 2024. [5] Nunes et al. (2023) LPSC 54. [6] Nunes et al. (2024) LPSC 55. [7] Adeli et al. (2023) SPIE. [8] Mazarico et al. (2024) LPSC 55. [9] Cascioli et al. (2024) LPSC 55. [10] Alemanno et al. (2023) SPIE.

This work reviews possible signatures and potential detectability of present-day volcanically emitted material in the atmosphere of Venus. We first discuss the expected composition of volcanic gases at present time, addressing how this is related to mantle composition and atmospheric pressure. Sulfur dioxide, often used as a marker of volcanic activity in Earth’s atmosphere, has been observed since late 1970s to exhibit variability at the Venus’ cloud tops at time scales from hours to decades; however, this variability may be associated with solely atmospheric processes. Water vapor is identified as a particularly valuable tracer for volcanic plumes because it can be mapped from orbit at three different tropospheric altitude ranges, and because of its apparent low background variability. We note that volcanic gas plumes could be either enhanced or depleted in water vapor compared to the background atmosphere, depending on magmatic volatile composition. Non-gaseous components of volcanic plumes, such as ash grains and/or cloud aerosol particles, are another investigation target of orbital and in situ measurements. We discuss expectations of in situ and remote measurements of volcanic plumes in the atmosphere with particular focus on the upcoming DAVINCI, EnVision and VERITAS missions, as well as possible future missions.

While its primary objectives were to study the interior of Mars and its present day seismic activity, the InSight lander also carried several meteorological sensors (primarily needed to differentiate true seismic signals from those produced by wind or passing vortices, or as part of a heat flow experiment) as well as cameras which could be used to monitor atmospheric and surface changes [1-6]. Although power became increasingly limited due to dust build-up on the lander’s solar panels [7], InSight’s Pressure Sensor measured nearly continuously at up to 20Hz for ~1.25 Mars years, giving the highest frequency pressure dataset yet obtained on Mars [8,9]. The Temperature and Winds for InSight (TWINS) instrument consisted of two booms pointing in opposite directions (such that at least one sensor would measure winds from a given direction with minimal influence from lander hardware). Each boom measured air temperature and winds at 1Hz nearly continuously for over one Mars year [8,10]. The Heat Flow and Physical Properties Package (HP3) regularly measured the diurnal variation of surface temperature [11,12], while aeolian observations revealed that vortices rather than linear wind stress were associated with the majority of particle motion events [10,13]. We will provide an overview of InSight’s meteorological and aeolian datasets, and show how we are using them to validate the predictions of four global and four mesoscale atmospheric models of InSight’s landing site in Elysium Planitia. The models used include Aeolis Research’s multiscale MarsWRF model (run at global and mesoscales) [14,15], the Open University’s global Mars model (in the form of the OpenMars reanalysis dataset, produced via data assimilation) [16], the global Mars version of LMD’s Planetary Climate Model [17], LMD’s mesoscale Mars model [18], and the Belgian version of the MarsWRF global model [19]. This work goes beyond previous pre-landing multi-model intercomparison and prediction efforts [e.g., 14] by assessing the performance of models against data and attempting to understand the reasons for differences, with the dual goals of better understanding the causes of weather phenomena at InSight and of improving Mars atmospheric model predictions of the near-surface environment. This is vital not only for improving future landing site predictions (which are key to planning Entry-Descent-Landing and surface mission operations), including the expected dust clearing from solar panels [7,20], but also for Mars science in general, such as improving the prediction of near-surface wind and dust lifting globally in order to better simulate the martian dust cycle and dust storms [21]. [1] Banfield, D., Rodriguez-Manfredi, J.A., Russell, C.T. et al. InSight Auxiliary Payload Sensor Suite (APSS). Space Sci Rev 215, 4 (2019). https://doi.org/10.1007/s11214-018-0570-x[2]Spiga, A., Banfield, D., Teanby, N.A. et al. Atmospheric Science with InSight. Space Sci Rev 214, 109 (2018). https://doi.org/10.1007/s11214-018-0543-0[3] Murdoch, N., Kenda, B., Kawamura, T. et al. Estimations of the Seismic Pressure Noise on Mars Determined from Large Eddy Simulations and Demonstration of Pressure Decorrelation Techniques for the Insight Mission. Space Sci Rev 211, 457–483 (2017). https://doi.org/10.1007/s11214-017-0343-y[4] Spohn, T., Grott, M., Smrekar, S.E. et al. The Heat Flow and Physical Properties Package (HP3) for the InSight Mission. Space Sci Rev 214, 96 (2018). https://doi.org/10.1007/s11214-018-0531-4[5] Maki, J.N., Golombek, M., Deen, R. et al. The Color Cameras on the InSight Lander. Space Sci Rev 214, 105 (2018). https://doi.org/10.1007/s11214-018-0536-z[6] Golombek, M., Grott, M., Kargl, G. et al. Geology and Physical Properties Investigations by the InSight Lander. Space Sci Rev 214, 84 (2018). https://doi.org/10.1007/s11214-018-0512-7[7] Golombek, M., Hudson, T., Bailey, P. et al. Results from InSight Robotic Arm Activities. Space Sci Rev 219, 20 (2023). https://doi.org/10.1007/s11214-023-00964-0[8] Banfield, D., Spiga, A., Newman, C. et al. The atmosphere of Mars as observed by InSight. Nat. Geosci. 13, 190–198 (2020). https://doi.org/10.1038/s41561-020-0534-0[9] Chatain, A., Spiga, A., Banfield, D., Forget, F., & Murdoch, N. (2021). Seasonal variability of the daytime and nighttime atmospheric turbulence experienced by InSight on Mars. Geophysical Research Letters, 48, e2021GL095453. https://doi.org/10.1029/2021GL095453[10] Baker, M., Newman, C., Charalambous, et al. (2021). Vortex-dominated aeolian activity at InSight's landing site, Part 2: Local meteorology, transport dynamics, and model analysis. Journal of Geophysical Research: Planets, 126, e2020JE006514. https://doi.org/10.1029/2020JE006514[11] Mueller, N. T., Knollenberg, J., Grott, et al. (2020). Calibration of the HP3 radiometer on InSight. Earth and Space Science, 7, e2020EA001086. https://doi.org/10.1029/2020EA001086[12] Spohn, T., Krause, C., Golombeck, M. et al. (2024). Mars Soil Temperature and Thermal Properties from InSight HP^3 Data. ESS Open Archive .https://doi.org/10.22541/essoar.170688827.75469589/v1[13] Charalambous, C., McClean, J. B., Baker, M., et al. (2021). Vortex-dominated aeolian activity at InSight's landing site, Part 1: Multi-instrument observations, analysis, and implications. Journal of Geophysical Research: Planets, 126, e2020JE006757. https://doi.org/10.1029/2020JE006757[14] Newman, C.E., M. de la Torre Juárez, J. Pla-García, et al. (2021). Multi-model Meteorological and Aeolian Predictions for Mars 2020 and the Jezero Crater Region, Space Sci. Rev., 217 (20), https://doi.org/10.1007/s11214-020-00788-2[15] Newman, C.E., Hueso, R., Lemmon, M., et al. (2022). The dynamic atmospheric and aeolian environment of Jezero crater, Mars, Sci Adv., 8 (21), eabn3783, https://doi.org/10.1126/sciadv.abn3783[16] Holmes, J.A., Lewis, S.R., and Patel, M.R. (2020). OpenMARS: A global record of martian weather from 1999 to 2015, Planetary and Space Science (188), 104962, https://doi.org/10.1016/j.pss.2020.104962[17] Lange, L., Forget, F., Banfield, D., et al. (2022). Insight pressure data recalibration, and its application to the study of long-term pressure changes on Mars. Journal of Geophysical Research: Planets, 127, e2022JE007190. https://doi.org/10.1029/2022JE007190[18] Spiga, A., Forget, F., Madeleine, J.-B., et al. (2011). The impact of martian mesoscale winds on surface temperature and on the determination of thermal inertia, Icarus, 212 (2), 504-519, https://doi.org/10.1016/j.icarus.2011.02.001[19] Temel, O., Senel, C.B., Porchetta, S., et al. (2021). Large eddy simulations of the Martian convective boundary layer: Towards developing a new planetary boundary layer scheme, Atmospheric Research, 250, 105381, https://doi.org/10.1016/j.atmosres.2020.105381[20] Lorenz, R. D., Lemmon, M. T., Maki, et al. (2020). Scientific observations with the InSight solar arrays: Dust, clouds, and eclipses on Mars. Earth and Space Science, 7, e2019EA000992. https://doi.org/10.1029/2019EA000992[21] Newman, C.E., Bertrand, T., Battalio, J.M., et al. (2021). Toward More Realistic Simulation and Prediction of Dust Storms on Mars, Bulletin of the AAS, 53 (4), https://doi.org/10.3847/25c2cfeb.726b0b65

Introduction:The Venusian atmosphere is a fascinating object of interest to planetary scientists. Obtaining in-situ data from Venus’ atmosphere and surface is however challenging. Radiative transfer (RT) modelling is an essential tool to understand planetary atmospheres. In a nutshell, radiative transfer codes model absorption, emission, and scattering of light by various components present in the atmosphere and surface. Accurate modelling of the atmosphere is also essential for decoding surface information from remote sensing data collected by probes. In the coming decade, several missions to Venus are planned that aim to image Venus thermal emission in the NIR spectral windows [1]. In order to process the data from these missions once they are available, radiative transfer modelling of the Venusian atmosphere is a necessary first step. One important aspect of the model is absorption by gases. Modelled absorption cross-sections are governed by the line list chosen for the model. These line lists are provided for wavelength ranges over which absorption occurs. The high-resolution transmission molecular absorption database (HITRAN) is a frequently used line database in radiative transfer modelling [2]. Several Venus atmospheric studies [3], however, have relied on the database of [4] for CO2 lines, referred to as “Hot CO2” from here on. This database is structurally similar to high-temperature molecular spectroscopic database (HITEMP) [5]. Fortunately, due to advances in exoplanetary sciences, newer line databases have been developed for high temperature atmospheres which are yet to be applied to Venusian atmospheric studies. In this work we compare absorption cross sections generated by using different line databases for relevant species present in the Venusian atmosphere: HITRAN 2020, HITEMP 2010, Hot CO2, and ExoMol [2,4,5,6]. Additional comparisons are made between radiance spectra generated by radiative transfer methods using different line lists with measured spectra in the NIR wavelength range.SPICAV dataset from Venus Express: The NIR wavelength range of 0.8 – 1.2 micron contains spectral windows where Venus’ surface thermal emission radiation is detectable from space, paving the way for surface studies in these bands [4]. Hence, the NIR region of Venus’ spectra is of particular importance. The Spectroscopy for the Investigation of the Characteristics of the Atmosphere of Venus (SPICAV) suite on board Venus Express made observations of Venus’ nightside in the spectral range of 0.65–1.7 um. The data used in our analysis is detailed in [7].Materials and Methods:The following computational tools have been utilized in this work: PYthon for Computational ATmospheric Spectroscopy (Py4CATS) [8] and Planetary Spectrum Generator (PSG) [9]. Both Py4CATS and PSG are equipped to read various line lists to produce radiance spectra from calculated absorption coefficients for a specified atmospheric profile. PSG is an online multi-purpose tool capable of computing radiance and transmission for planets and exoplanets with preconfigured settings. Py4CATS implements several scripts for radiative transfer calculations which can be executed from a Python interpreter or from a console. PSG includes a module capable of modelling scattering in the Venusian clouds while Py4CATS has to be combined with additional tools to do so, e.g. [10].Preliminary results:In the Venusian atmosphere, absorption features are majorly dominated by CO2 and H2O lines. Thus, we start by comparing absorption cross sections for CO2 computed by Py4CATS for the following line databases: HITRAN 2020, HITEMP 2010, and Hot CO2. From figure 1, one can note that HITEMP 2010 has missing lines in the 8500 – 9000 cm-1 wavenumber region and that absorption cross sections produced from HITRAN 2020 are much closer to those of Hot CO2. This work aims to further explore implications on radiative transfer modelling using recently updated line databases such as HITRAN 2020 and ExoMol.Figure 1: Comparison of line databases in NIR region generated using Py4CATS, computed for575 K and 2x106 PaTo decide which database is best suited it is necessary to compare modelled top of atmosphere radiances to observed spectra. We use the PSG to model nadir radiances of the default Venus atmosphere profile and modules (i.e. Lambertian surface with emissivity 0.8, absorption by gases, Rayleigh scattering, multiple scattering at cloud droplets with cloud optical thickness 15). Figure 2 shows that there are noticeable differences in the radiance spectrum generated by the PSG [9] upon using HITRAN 2020 line database and the ExoMol line database.Fig 2: Radiance spectra generated by PSG (HITRAN 2020 and ExoMol) compared to SPICAV IR data.It can be noted from figure 2 that radiances generated using HITRAN 2020 database to have a better agreement with SPICAV data than those generated using ExoMol database. It is likely that further modifications to the line shapes and continuum absorption similar to those that are used in other Venus studies will have to be introduced [3, 11].Conclusions:The HITRAN 2020 line list is closer to the often used ‘’Hot CO2’’ line list than previous versions of HITRAN. Line databases such as ExoMol which are intended for high temperature atmospheres may improve radiative transfer models for Venus, although our initial comparison does not show an improvement over HITRAN. Overall our investigations have shown HITRAN 2020 to be more promising for Venus RT studies than HITEMP 2010 and ExoMol. This work aims to further explore applying these new databases to radiative transfer models and compare generated spectra to measured data.References:[1] Allen D. A. et al. (1984) Nature, 307, 222–224[2] Gordon I. E. et al. (2022) J. Quant. Spectrosc. Radiat. Transfer, 277, 107949[3] Bézard B. et al. (2011) Icarus, 216(1), 173–83[4] Pollack J. B. et al. (1993) Icarus, 103, 1–42[5] Rothman L. S. et al. (2010) J. Quant. Spectrosc. & Radiat. Transfer, 111(12-13), 2139–2150[6] Tennyson J. et al. (2016) J. Mol. Spectrosc., 327, 73 – 94[7] Korablev O. et al. (2006) J. Geophys. Res. 111(E9)[8] Schreier F. et al. (2019) Atmosphere, 10(5), 262[9] Villanueva G. L. et al. (2018) J. Quant. Spectrosc. & Radiat. Transfer, 217, 86 – 104[10] Efremenko D. et al. (2023) Environmental Sciences Proceedings , 29(1), 20[11] Kappel D. et al. (2016) Icarus 265, 42–62

Diurnal and seasonal variations in soil and surface temperature measured with the HP3 thermal probe and radiometer of NASA's InSight Mars mission are reported. At a representative depth of 10-20 cm, an average temperature of 217.5 K was found, varying by 5.3-6.7 K during a sol and by 13.3 K during the seasons. From the damping of the temperature variation with depth and the phase shift, a thermal diffusivity of (3.93 +/- 0.39) x 10 8 m2/s was derived for the upper similar to 10 cm from the diurnal temperature variation and of (3.63 +/- 0.53) x 10 8 m2/s for the similar to 40 cm depth range of the mole from the annual temperature variation. Using published thermal conductivity and inertia values together with the diffusivities, soil densities of 1,470 and 1,730 kg/m3 were derived for these depths. The temperatures allow the deliquescence of thin films of brine, the efflorescence of which may explain the cemented duricrust observed.

Crustal plateaus are large, high elevation physiographic features on Venus associated with the strongly deformed tessera terrains. They present positive, low magnitude gravity anomalies, and they are stratigraphically the oldest surfaces on the planet [1]. Previous investigations of the gravity and topography signatures of the plateaus have shown that these regions are consistent with shallow support via crustal thickening [2, 3]. In addition, surface emissivity data obtained by Venus Express have shown that the plateaus are associated with low emissivity anomalies, which could be indicative of a felsic composition [4]. Given these observational data sets that are summarized in Figure 1 for Alpha Regio, crustal plateaus could be analogues to the continents on Earth, which would have major implications for our understanding of the tectonic and geodynamic processes that operated throughout Venus’ evolution. Therefore, a careful investigation of the origin and evolution of these features is one of the main objectives of the future missions to Venus. The goal of this study is to quantify how much the future gravity datasets, in particular obtained by the VERITAS mission, will help us constrain the interior structure of plateaus. We focus on crustal density estimations, since the density would give essential information about the potential felsic composition of the crustal plateaus. Here, we build on the research and methods of Maia & Wieczorek [3], but we adopt a different inversion approach and focus only on surface loads. To this end, we use a two-layer (mantle, crust+load) lithospheric flexural model. In our inversion, the admittance, a measure of the response of the gravity field to variations in topography, is the physical quantity that is compared between model and observations. The admittance is then spatially and spectrally localized using the windowing functions developed by Wieczorek & Simons [5], to focus the analysis on the plateau regions of interest (here, Alpha Regio and Ovda Regio). A Bayesian inversion to retrieve the parameters of crustal plateaus (i.e., crustal thickness Tc, elastic thickness Te, crustal density ρc) is carried out using the Dynesty package [6] that implements a Nested Sampling algorithm. Results using current low resolution gravity data show some improvements on the uncertainties of crustal and elastic thickness in comparison to [3] (Figure 2). In particular, our inversions were able to retrieve a lower bound of about 5 km for the elastic thickness of Ovda Regio. However, as expected, the plateau’s crustal density remains unconstrained within the explored range (2400-3000 kg/m3). The slight variability of the results for different window sizes is caused by uncorrelated gravity anomalies not related to the crustal plateau.These resolution limitations will be soon overcome, thanks to the improvements expected with the VERITAS and EnVision missions, to be launched in the early 2030s to study Venus. In particular, thanks to its quasi-circular orbit, VERITAS will obtain a gravity model with degree strength globally larger than degree 160 and over degree 200 in some regions [7]. Thus, the second focus of this study is to provide a first impression of the extent to which this new dataset will improve our knowledge about the interior structure of the crustal plateaus.For the simulated gravity dataset, we use flexural models up to spherical harmonic degree 180, for which we consider 6 different variations of the parameters of interest (Tc=20 km, Te=15/30 km, ρc=2650/2800/2950 kg/m3). In a second step, simulated noise is added, and the synthetic data is then mixed with the currently measured gravity field with a sigmoid (logistic function). By changing parameters of this function, such as the steepness of the curve (k) and the degree at which the growth occurs (x0), the mixing can be controlled. This new simulated gravity dataset is used together with our inversion process to study the impact of the higher degree gravity field on our results and test our ability to retrieve the parameters of the crustal plateaus (Tc, Te, ρc).We observe that, by including more synthetic data compared to the measured gravity field, our inversion is able to retrieve the parameters of the crustal plateaus within 10% of the true value known from the synthetic models (see results in Figure 3 for Alpha Regio). We show that the uncertainties of the crustal plateau parameters substantially decrease when the maximum degree of the gravity field that is used in our inversions increases. Our results demonstrate that such an approach would be able to distinguish between a high density, basaltic crust and a low density more felsic crust.Future developments will investigate different sources of noise that can be added to the admittance, such as geologic signals not related to flexural support. A natural next step is to apply this analysis to different crustal plateaus to determine the potential of retrieving crustal density estimates at various locations on Venus. Finally, we will perform additional sensitivity tests for our inversion approach to assess its robustness to various additional input parameters. References:[1] Ivanov M.A. & Head J.W. (2011) Planet. Space Sci., 59; [2] Grimm R.E. (1994) Icarus, 112 ; [3] Maia J.S. & Wieczorek M.A. (2022) JGR Planets, 127; [4] Gilmore M.S. et al. (2015) Icarus, 254; [5] Wieczorek M.A. & Simons F.J. (2007) JFAA, 13; [6] Speagle J.S. (2020) MNRAS, 493; [7] Cascioli G. et al. (2024) 55th LPSC.

In the frame of the preparation of the EnVision mission, going back to existing datasets is essential. In this investigation, the 1.17 µm band both of interest for VenSpec-M and VenSpec-H is analysed from a statistical point of view based on the calibrated dataset provided in Mueller et al. (2020) [1]. The radiative transfer model, ASIMUT-ALVL [2], is then validated against these averaged observations.VenSpec-H is part of the VenSpec suite [3], also including an IR mapper and a UV spectrometer [4]. The suite science objectives are to search for temporal variations in surface temperatures and tropospheric concentrations of volcanically emitted gases, indicative of volcanic eruptions; and to study surface-atmosphere interactions. Maintenance of the clouds requires a constant input of H2O and SO2. A large eruption would locally alter the composition by increasing abundances of H2O, SO2, and CO and possibly decreasing the D/H ratio. Observations of changes in lower atmospheric SO2, CO, and H2O vapour levels, cloud level H2SO4 droplet concentration, and mesospheric SO2, are therefore required to link specific volcanic events with past and ongoing observations of the variable and dynamic mesosphere, to understand both the importance of volatiles in volcanic activity on Venus and their effect on cloud maintenance and dynamics. VenSpec-H’s main scientific objectives are (1) to better constrain the composition of the atmosphere both below and above the clouds to relate changes in the composition to changes on the surface or geological processes such as volcanism; (2) to investigate short and long-term trends in the composition to better grasp the climate evolution on Venus.VenSpec-H is designed to measure H2O, HDO, CO, OCS, and SO2 on both the night and day side to contribute to this investigation. VenSpec-H is a nadir-pointing, high-resolution (R~8000) infrared spectrometer that will perform observations in different spectral windows between 1 and 2.5 µm. Spectra in these bands will be recorded sequentially with the help of a filter wheel and will allow the sounding of different layers in the Venusian atmosphere: close to the surface (1.17 µm), 15-30 km (1.7 µm), 30-40 km (2.4 µm) and above the clouds (1.38 & 2.4 µm). Two additional polarization filters will be used during dayside observations to better characterize the clouds’ properties.VIRTIS was an instrument with three different channels, mapping visible (M-VIS), mapping infrared (M-IR) and high-resolution infrared (H). It flew onboard Venus Express from 2006 to 2014 and delivered major science results [5-7].We consider the M-IR channel which was a line scanning imaging spectrometer observing in the near infrared from approximately 1 μm to 5 μm. Having acquired about 5000 data cubes, VIRTIS-M-IR stopped measuring science data in October 2008 when its cryocooler failed.This investigation is based on calibrated data covering the spectral range from 1020 nm to 1400 nm (bands 0 to 39) with a spectral sampling of 9.5 nm and published in 2020. This dataset has been calibrated to include the 1 to 1.4 µm with Even-Odd correction and sun straylight subtraction [1]. It was also spectrally calibrated based on Cardesin Moinelo et al., 2010 [8].A statistical analysis of the VIRTIS-M-IR dataset was performed, considering account millions of spectra, In the frame of the scientific preparation of EnVision, we focused on the 1.17 µm band which is common to VenSpec-H and VenSpec-M. Averaged spectra were calculated by considering latitudinal and temporal binning. Outliers were identified for further analysis.The BIRA-IASB radiative transfer code, ASIMUT-ALVL [2], has been used as a forward modeling tool in this spectral range to make sure all contributions were properly understood. The radiances of the nightside atmosphere of Venus originate from the thermal emission of the surface and atmosphere. The impacts of the molecular species (line-by-line and collision induced absorption) and of the aerosols were analyzed separately to, in fine, reproduce the VIRTIS-M-IR calibrated observations.This investigation has been led to characterise the radiance levels that VenSpec-H will likely observe when measuring the variations of the minor species in Venus’ troposphere. In this presentation, we will discuss the data analysis and its impact on the expected performances of our future instrument. References[1] N.T. Mueller et al., “Multispectral surface emissivity from VIRTIS on Venus Express”, Icarus, 335 (2020) 113400.[2] A.C. Vandaele, M. Kruglanski and M. De Mazière, “Modeling and retrieval of atmospheric spectra using ASIMUT”, Proc. of the First 'Atmospheric Science Conference', ESRIN, Frascati, Italy, 2006.[3] J. Helbert et al., “The VenSpec suite on the ESA EnVision mission to Venus”, Proc. SPIE 11128, Infrared Remote Sensing and Instrumentation XXVII, (2019) 1112804.[4] E. Marcq et al., “Instrumental requirements for the study of Venus’ cloud top using the UV imaging spectrometer VeSUV”, Advances in Space Research, 68 (2021) 275-291.[5] Piccioni, G. et al., “South-polar features on Venus similar to those near the north pole”, Nature, 450 (7170) (2007) 637-640.[6] Drossart, P. et al., “A dynamic upper atmosphere of Venus as revealed by VIRTIS on Venus Express”, Nature, 450 (7170) (2007) 641-645.[7] E. Marcq et al., “Minor species in Venus’ night side troposphere as observed by VIRTIS-H/Venus Express”, Icarus, 405 (2023) 115714.[8] A. Cardesin Moinelo, et al., “Calibration of hyperspectral imaging data: VIRTIS-M Onboard Venus Express “ IEEE Transactions on Geoscience and Remote Sensing, 48(11) (2010) 3941-3950.

The temperature and dynamics of the planetary boundary layer (PBL), i.e. the atmosphere closest to the surface, are important to many aspects of Venus science. The characteristics of the PBL are critical for the exchange of angular momentum between atmosphere and solid planet possibly affecting the planets spin rate (Mueller et al. 2012, Navarro et al. 2018, Margot et al. 2020). Stability of surface minerals is temperature dependent and a related temperature albedo feedback has been proposed to stabilize the Venus climate (Hashimoto and Abe 2005). Some gravity science investigations are enabled by thermal tides, which include the PBL (Cascioli et al. 2021). The dielectric behavior of minerals is temperature dependent and apparent changes of radar emissivity with surface elevation have been interpreted in terms of mineralogy (Brossier et al. 2021). Even more relevant for the remote sensing of surface mineralogy is that for determination of surface emissivity in the near infrared the surface temperature has to be known very well (Kappel et al. 2015).The PBL is not well resolved by in-situ data. The temperature gathered during the descent of the many Venera missions does not have a very high sampling frequency and has high uncertainty so that the PBL is not discernable (Seiff et al. 1985). The temperature sensors of the four Pioneer Venus descent probes all failed above the PBL at about 12 km about mean planetary radius, so that no details of the PBL are included in the Venus International Reference Atmosphere (Seiff et al. 1985). The last descent probe VeGa 2 observed at a higher frequency and better uncertainty but the results between 1 and 6 km were considered implausible, because the observed temperature lapse rate exceeded the calculated adiabatic lapse, i.e. the stratification should have been unstable.The PBL is not easily accessible to remotes sensing. There are however indirect constraints on the PBL temperature from observations of surface thermal emission through the spectral windows near 1 µm. The Venus Express mission provided with the VIRTIS instrument an extensive data set of thermal emission, that is however mostly limited to the southern hemisphere which does not have highlands reaching far into the layer where VeGa2 found an apparently superadiabatic lapse rate. Mueller et al. 2020 processed the data to a mosaic (Fig. 1) and derived emissivity, again assuming surface temperature corresponding to the VIRA profile. The resulting emissivity is very well correlated with topography in the range from -2 to +2 km relative to the mean planetary radius (MPR) of 6052 km, which is geologically not plausible. The alternative interpretation is again a deviation from the temperature profile assumed in the model instead of a variable emissivity. The model of Mueller et al. 2020 was not used to explore the effect of deviations from the temperature profile but it is possible to estimate the effect. In absence of atmospheric emission, which is approximately true for the 1020 nm window [Meadows and Crisp 1996], the top-of-atmosphere radiance is proportional to the blackbody function at surface temperature. The relative difference between the observed and model TOA radiance can therefore be expressed as the corresponding temperature difference to the model (Fig. 2).Figure 3 shows the result as function of planetary radius for two regions, Lavinia Planitia and Themis Regio, that were often observed by VIRTIS and were selected because they show large temperature differences at the same elevation and lie on the same latitude band. The differences to the VIRA profile are up to -5K and increase to the lowlands, indicating a lower lapse rate than VIRA. At above 6053 km there is a hint that the lapse rate could reverse and follow the apparently super-adiabatic lapse rate observed by VeGa2, but this is ambiguous. This high location is a single corona and relatively low emissivity would be a geologically plausible alternative explanation [Stofan et al. 2016]. To study the VeGa2 profile, observations at higher elevations are necessary, e.g. those made by Akatsuki IR 1 [Kulkarni et al. 2021] or Parker Solar Probe WISPR [Lustig Yaeger et al. 2023].The difference in temperature between the two regions is surprising because studies to derive emissivity assumed that the surface temperature was only a function of elevation since heat redistribution by convection is very effective e.g. (Hashimoto et al. 2008). Comparison to the Venus Climate Database, which models the PBL and its interaction with topography (Lebonnois et al. 2018) shows clear similarities (Fig. 4). The midnight surface temperature below 1 km above MPR has a lower lapse rate than VIRA and the Lavinia Planitia basin is warmer than the flanks of the Themis Regio volcanic rise at the same surface elevation. This temperature difference persists over the Venus day in the model. Our working hypothesis is that the relatively constant slope winds of Venus in combination with the different cooling rates of atmosphere and surface at night redistribute heat and thus create these surface temperature differences.Overall, the differences to VIRA observed by VIRTIS are about two times larger than those in the model. One possibility could be that the approximation for surface temperature exaggerates temperature contrast. This seems unlikely but we will check this using a radiative transfer model. Another possibility is that the difference can be explained by the low resolution of the GCM (~400 km) and the correspondingly more muted topography. In any case, near infrared imaging provides data that can be compared to modeled surface temperatures of GCMs and thus provide indirect evidence on the planetary boundary layer. Upcoming missions will image these wavelengths with a much-improved signal to noise ratio which may additionally provide surface temperature change rates at night.Mueller,+(2012).doi:10.1016/j.icarus.2011.09.026; Navarro,+(2018).doi:10.1038/s41561-018-0157-x; Margot,+(2021).doi:10.1038/s41550-021-01339-7; Hashimoto,+(2005).doi:10.1016/j.pss.2005.01.005; Cascioli,+(2021)doi:10.3847/PSJ/ac26c0; Brossier,+(2021).doi:10.1029/2020JE006722; Kappel,+(2015).doi:10.1016/j.pss.2015.01.014; Seiff,+(1985).doi:10.1016/0273-1177(85)90197-8; Mueller,+(2020).doi:10.1016/j.icarus.2019.113400; Meadows,+(1996).doi:10.1029/95JE03567; Stofan,+(2016).doi:10.1016/j.icarus.2016.01.034; Kulkarni,+(2021).doi:10.5194/epsc2021-730; Lustig-Yaeger,+(2023).doi:10.3847/PSJ/ad0042; Hashimoto,+(2008).doi:10.1029/2008JE003134; Lebonnois,+(2018).doi:10.1016/j.icarus.2018.06.006

<p>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.                                                         </p><p><img src="" alt="" /></p><p>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.</p><p> </p>

Surface mineralogy records the primary composition, climate history and the geochemical cycling between the surface and atmosphere. We have not yet directly measured mineralogy on the Venus surface in situ, but a variety of independent investigations yield a basic understanding of surface composition and weathering reactions in the present era where rocks react under a supercritical atmosphere dominated by CO 2 , N 2 and SO 2 at ∼460 °C and 92 bars. The primary composition of the volcanic plains that cover ∼80% of the surface is inferred to be basaltic, as measured by the 7 Venera and Vega landers and consistent with morphology. These landers also recorded elevated SO 3 values, low rock densities and spectral signatures of hematite consistent with chemical weathering under an oxidizing environment. Thermodynamic modeling and laboratory experiments under present day atmospheric conditions predict and demonstrate reactions where Fe, Ca, Na in rocks react primarily with S species to form sulfates, sulfides and oxides. Variations in surface emissivity at ∼1 μm detected by the VIRTIS instrument on the Venus Express orbiter are spatially correlated to geologic terrains. Laboratory measurements of the near-infrared (NIR) emissivity of geologic materials at Venus surface temperatures confirms theoretical predictions that 1 μm emissivity is directly related to Fe 2+ content in minerals. These data reveal regions of high emissivity that may indicate unweathered and recently erupted basalts and low emissivity associated with tessera terrain that may indicate felsic materials formed during a more clement era. Magellan radar emissivity also constrain mineralogy as this parameter is inversely related to the type and volume of high dielectric minerals, likely to have formed due to surface/atmosphere reactions. The observation of both viscous and low viscosity volcanic flows in Magellan images may also be related to composition. The global NIR emissivity and high-resolution radar and topography collected by the VERITAS, EnVision and DAVINCI missions will provide a revolutionary advancement of these methods and our understanding of Venus mineralogy. Critically, these datasets must be supported with both laboratory experiments to constrain the style and rate weathering reactions and laboratory measurements of their NIR emissivity and radar characteristics at Venus conditions.

Photogeologic principles can be used to suggest possible sequences of events that result in the present planetary surface. The most common method of evaluating the absolute age of a planetary surface remotely is to count the number of impact craters that have occurred after the surface formed, with the assumption that the craters occur in a spatially random fashion over time. Using additional assumptions, craters that have been partially modified by later geologic activity can be used to assess the time frames for an interpreted sequence of events. The total number of craters on Venus is low and the spatial distribution taken by itself is nearly indistinguishable from random. The overall implication is that the Venusian surface is much closer to Earth in its youthfulness than the other, smaller inner solar system bodies. There are differing interpretations of the extent to which volcanism and tectonics have modified the craters and of the regional and global sequences of geologic events. Consequently, a spectrum of global resurfacing views has emerged. These range from a planet that has evolved to have limited current volcanism and tectonics concentrated in a few zones to a planet with Earth-like levels of activity occurring everywhere at similar rates but in different ways. Analyses of the geologic record have provided observations that are challenging to reconcile with either of the endmember views. The interpretation of a global evolution with time in the nature of geologic activity relies on assumptions that have been challenged, but there are other observations of areally extensive short-lived features such as canali that are challenging to reconcile with a view of different regions evolving independently. Future data, especially high-resolution imaging and topography, can provide the details to resolve some of the issues. These different global-evolution viewpoints must tie to assessments of present-day volcanic and tectonic activity levels that can be made with the data from upcoming missions.

Abstract The heat flow and physical properties package measured soil thermal conductivity at the landing site in the 0.03–0.37 m depth range. Six measurements spanning solar longitudes from 8.0° to 210.0° were made and atmospheric pressure at the site was simultaneously measured using InSight's Pressure Sensor. We find that soil thermal conductivity strongly correlates with atmospheric pressure. This trend is compatible with predictions of the pressure dependence of thermal conductivity for unconsolidated soils under martian atmospheric conditions, indicating that heat transport through the pore filling gas is a major contributor to the total heat transport. Therefore, any cementation or induration of the soil sampled by the experiments must be minimal and soil surrounding the mole at depths below the duricrust is likely unconsolidated. Thermal conductivity data presented here are the first direct evidence that the atmosphere interacts with the top most meter of material on Mars.

The SEIS seismometer deployed at the surface of Mars in the framework of the NASA-InSight mission has been continuously recording the ground motion at Elysium Planitia for more than one martian year. In this work, we investigate the seasonal variation of the near surface properties using both background vibrations and a particular class of high-frequency seismic events. We present measurements of relative velocity changes over one martian year and show that they can be modeled by a thermoelastic response of the Martian regolith. Several families of high-frequency seismic multiplets have been observed at various periods of the martian year. These events exhibit repeatable waveforms with an emergent character and a coda that is likely composed of scattered waves. Taking advantage of these properties, we use coda waves interferometry to measure relative travel-time changes as a function of the date of occurrence of the quakes. While in some families a stretching of the coda waveform is clearly observed, in other families we observe either no variation or a clear contraction of the waveform. Measurements of velocity changes from the analysis of background vibrations above 5Hz are consistent with the results from coda wave interferometry. We identify a frequency band structure in the power spectral density, that can be tracked over hundreds of days. This band structure is the equivalent in the frequency domain of an autocorrelogram and can be efficiently used to measure relative travel-time changes as a function of frequency. The observed velocity changes can be adequately modeled by the thermoelastic response of the regolith to the time-dependent incident solar flux at the seasonal scale. In particular, the model captures the time delay between the surface temperature variations and the velocity changes in the sub-surface. Our observations could serve as a basis for a joint inversion of the seismic and thermal properties in the first meters below InSIght.

The InSight lander rests on a regolith‐covered, Hesperian to Early Amazonian lava plain in Elysium Planitia within a ∼27‐m‐diameter, degraded impact crater called Homestead hollow. The km to cm‐scale stratigraphy beneath the lander is relevant to the mission's geophysical investigations. Geologic mapping and crater statistics indicate that ∼170 m of mostly Hesperian to Early Amazonian basaltic lavas are underlain by Noachian to Early Hesperian (∼3.6 Ga) materials of possible sedimentary origin. Up to ∼140 m of this volcanic resurfacing occurred in the Early Amazonian at 1.7 Ga, accounting for removal of craters ≤700 m in diameter. Seismic data however, suggest a clastic horizon that interrupts the volcanic sequence between depths of ∼30 and ∼75 m. Meter‐scale stratigraphy beneath the lander is constrained by local and regional regolith thickness estimates that indicate up to 10–30 m of coarse‐grained, brecciated regolith that fines upwards to a ∼3 m thick loosely‐consolidated, sand‐dominated unit. The maximum depth of Homestead hollow, at ∼3 m, indicates that the crater is entirely embedded in regolith. The hollow is filled by sand‐size eolian sediments, with contributions from sand to cobble‐size slope debris, and sand to cobble‐size ejecta. Lander‐based observations indicate that the fill at Homestead hollow contains a cohesive layer down to ∼10–20 cm depth that is visible in lander rocket‐excavated pits and the HP3 mole hole. The surface of the landing site is capped by a ∼1 to 2 cm‐thick loosely granular, sand‐sized layer with a microns‐thick surficial dust horizon.

SUMMARY The SEIS (Seismic Experiment for Interior Structure) seismometer deployed at the surface of Mars in the framework of the NASA-InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission has been continuously recording the ground motion at Elysium Planitia for more than one martian year. In this work, we investigate the seasonal variation of the near-surface properties using both background vibrations and a particular class of high-frequency seismic events. We present measurements of relative velocity changes over one martian year and show that they can be modelled by a thermoelastic response of the Martian regolith. Several families of high-frequency seismic multiplets have been observed at various periods of the martian year. These events exhibit complex, repeatable waveforms with an emergent character and a coda that is likely composed of scattered waves. Taking advantage of these properties, we use coda wave interferometry (CWI) to measure relative traveltime changes as a function of the date of occurrence of the quakes. While in some families a stretching of the coda waveform is clearly observed, in other families we observe either no variation or a clear contraction of the waveform. These various behaviors correspond to different conditions of illumination at the InSight landing site, depending on the season. Measurements of velocity changes from the analysis of background vibrations above 5 Hz are consistent with the results from CWI. We identify a frequency band structure in the power spectral density (PSD) that can be tracked over hundreds of days. This band structure is the equivalent in the frequency domain of an autocorrelogram and can be efficiently used to measure relative traveltime changes as a function of frequency. We explain how the PSD analysis allows us to circumvent the contamination of the measurements by the Lander mode excitation which is inevitable in the time domain. The observed velocity changes can be adequately modelled by the thermoelastic response of the regolith to the time-dependent incident solar flux at the seasonal scale. In particular, the model captures the time delay between the surface temperature variations and the velocity changes in the subsurface. Our observations could serve as a basis for a joint inversion of the seismic and thermal properties in the first 20 m below InSight.

We use the surface temperature response to Phobos transits as observed by a radiometer on board of the InSight lander to constrain the thermal properties of the uppermost layer of regolith. Modeled...

The heat flow and physical properties package (HP3) of the InSight Mars mission is an instrument package designed to determine the martian planetary heat flow. To this end, the package was designed to emplace sensors into the martian subsurface and measure the thermal conductivity as well as the geothermal gradient in the 0-5 m depth range. After emplacing the probe to a tip depth of 0.37 m, a first reliable measurement of the average soil thermal conductivity in the 0.03-0.37 m depth range was performed. Using the HP3 mole as a modified line heat source, we determined a soil thermal conductivity of 0.039 +/- 0.002 W m(-1) K-1, consistent with the results of orbital and in-situ thermal inertia estimates. This low thermal conductivity implies that 85%-95% of all particles are smaller than 104-173 mu m and suggests that soil cementation is minimal, contrary to the considerable degree of cementation suggested by image data. Rather, cementing agents like salts could be distributed in the form of grain coatings instead. Soil densities compatible with the measurements are 1211-113+149 kg m(-3), indicating soil porosities of 63-9+4%.