Near-IR Investigation of the Thermal Structure of Venusian Deep Atmosphere

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. [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)

Validation of the IPSL Venus GCM Thermal Structure with Venus Express Data

General circulation models (GCMs) are valuable instruments to understand the most peculiar features in the atmospheres of planets and the mechanisms behind their dynamics. Venus makes no exception and it has been extensively studied thanks to GCMs. Here we validate the current version of the Institut Pierre Simon Laplace (IPSL) Venus GCM, by means of a comparison between the modelled temperature field and that obtained from data by the Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) and the Venus Express Radio Science Experiment (VeRa) onboard Venus Express. The modelled thermal structure displays an overall good agreement with data, and the cold collar is successfully reproduced at latitudes higher than +/−55°, with an extent and a behavior close to the observed ones. Thermal tides developing in the model appear to be consistent in phase and amplitude with data: diurnal tide dominates at altitudes above 102 Pa pressure level and at high-latitudes, while semidiurnal tide dominates between 102 and 104 Pa, from low to mid-latitudes. The main difference revealed by our analysis is located poleward of 50°, where the model is affected by a second temperature inversion arising at 103 Pa. This second inversion, possibly related to the adopted aerosols distribution, is not observed in data

Venus surface temperature derived from VIRTIS on Venus Express in comparison to the Venus Climate Database

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

Long-term Plan to Monitor Venus using Earth-orbiting CubeSats: Chasing the Long-term Variability of Our Nearest Neighbor Planet Venus (CLOVE)

Past Venus studies reported unexpected temporal variations on a global scale in terms of ultraviolet (UV) reflectivity, SO _{2} and H _{2}O gas abundances, cloud top altitudes, and zonal wind speed. These variations are plausibly connected to each other and to global atmospheric circulation, atmospheric chemistry, volcanism, and solar activity cycles. The nature of these reported variations is unknown: are they periodic? What is the driving mechanism? What are the implications for the current climate? To answer these questions, we plan a long-term Venus monitoring campaign. Our plan has been selected by the Institute for Basic Science (IBS), South Korea, and funded for the first 5 years by a research grant (2022-2027). Our international and ambitious project includes long-term monitoring with ground-based telescopes and space-based CubeSats. Ground-based telescopes will perform observations from 320 nm to the near-infrared (NIR). CubeSats in Earth orbit will provide a high temporal resolution and a unique UV wavelength coverage, as is only possible to achieve from space. We will simultaneously retrieve reflectivity, SO _{2} abundance, cloud top altitude, and haze abundance above the clouds to elucidate the mechanism behind their correlations. Our effort will benefit from coordinated observations with the active space missions Akatsuki and BepiColombo. We will perform a feasibility study to assess the use of CubeSats for Venus observations, with the goal of having the first CubeSat ready within 5 years, for a mission that can be extended with other CubeSats for a total of 15 years, covering the time of future Venus missions by NASA and ESA. Long-term monitoring will characterize the temporal variability of the variations, allowing us to reveal their origin and nature

Long-term Monitoring Plan of Venus using Earth-orbiting CubeSats

Venus’s atmosphere shows considerable temporal variations regarding the SO2 gas abundance, zonal wind speeds, and the UV brightness near the cloud’s tops. The main drivers of the reported variations are unclear but may be associated with volcanic activities, impacts of the Solar Cycle, or large-scale atmospheric dynamics. To understand possible mechanisms, a long period of monitoring is necessary, and reliable data calibration is mandatory. We propose a continuous monitoring project, CLOVE (Chasing the Long-term Variability of Our Nearest Neighbor Planet Venus), utilizing a combination of ground- and space-based facilities to overcome the limitations of using a single dataset. Firstly, we plan a low-Earth orbit CubeSat that will monitor Venus at four selected wavelengths to investigate the cloud top vertical structure, the unknown absorber(s), and the SO2 gaseous abundance. We plan our first CLOVE CubeSat to be launched in 2026. With its successful operation, we aim to proceed with the subsequent CubeSats that will continue Venus monitoring, replacing the old Sat with a new one to cover at least 15 years of time to complete one Solar Cycle. Secondly, our ground-based observations have been conducted as a coordinated Venus dayside observation in 2020 and 2023 with the Akatsuki Venus orbiter and the BepiColombo mission during its cruise phase. Future ground-based observations will be coordinated with the CLOVE CubeSat, providing cross-check validation and supplementary data to interpret our analysis

Enabling planetary science across light-years. Ariel Definition Study Report

Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar System. The payload consists of an off-axis Cassegrain telescope (primary mirror 1100 mm x 730 mm ellipse) and two separate instruments (FGS and AIRS) covering simultaneously 0.5-7.8 micron spectral range. The satellite is best placed into an L2 orbit to maximise the thermal stability and the field of regard. The payload module is passively cooled via a series of V-Groove radiators; the detectors for the AIRS are the only items that require active cooling via an active Ne JT cooler. The Ariel payload is developed by a consortium of more than 50 institutes from 16 ESA countries, which include the UK, France, Italy, Belgium, Poland, Spain, Austria, Denmark, Ireland, Portugal, Czech Republic, Hungary, the Netherlands, Sweden, Norway, Estonia, and a NASA contribution

Science goals and new mission concepts for future exploration of Titan's atmosphere geology and habitability: Titan POlar Scout/orbitEr and In situ lake lander and DrONe explorer (POSEIDON)

In response to ESA’s “Voyage 2050” announcement of opportunity, we propose an ambitious L-class mission to explore one of the most exciting bodies in the Solar System, Saturn’s largest moon Titan. Titan, a “world with two oceans”, is an organic-rich body with interior-surface-atmosphere interactions that are comparable in complexity to the Earth. Titan is also one of the few places in the Solar System with habitability potential. Titan’s remarkable nature was only partly revealed by the Cassini-Huygens mission and still holds mysteries requiring a complete exploration using a variety of vehicles and instruments. The proposed mission concept POSEIDON (Titan POlar Scout/orbitEr and In situ lake lander DrONe explorer) would perform joint orbital and in situ investigations of Titan. It is designed to build on and exceed the scope and scientific/technological accomplishments of Cassini-Huygens, exploring Titan in ways that were not previously possible, in particular through full close-up and in situ coverage over long periods of time. In the proposed mission architecture, POSEIDON consists of two major elements: a spacecraft with a large set of instruments that would orbit Titan, preferably in a low-eccentricity polar orbit, and a suite of in situ investigation components, i.e. a lake lander, a “heavy” drone (possibly amphibious) and/or a fleet of mini-drones, dedicated to the exploration of the polar regions. The ideal arrival time at Titan would be slightly before the next northern Spring equinox (2039), as equinoxes are the most active periods to monitor still largely unknown atmospheric and surface seasonal changes. The exploration of Titan’s northern latitudes with an orbiter and in situ element(s) would be highly complementary in terms of timing (with possible mission timing overlap), locations, and science goals with the upcoming NASA New Frontiers Dragonfly mission that will provide in situ exploration of Titan’s equatorial regions, in the mid-2030s

Super-rotating the venusian atmosphere

Analysis of spacecraft observations deciphers the source of fast atmospheric rotation</jats:p

Planetary-Scale Wave Activity in Venus Cloud Layer Simulated by the Venus PCM

International audienceThe Venus atmosphere Superrotation (SR) is successfully simulated with the high-resolution (1.25° × 1.25° in longitude and latitude) runs of the Venus Planetary Climate Model (PCM). The results show a clear spectrum and structure of atmospheric waves, primarily with periods of 5.65 and 8.5 days. The simulation reproduces long-term quasi-periodic oscillation of the zonal wind and primary planetary-scale wave seen in observations. These oscillations occur with a period of 163-222 days, although their existence is still debated in observations. The Rossby waves show similarity in wave characteristics and angular momentum (AM) transport due to Rossby-Kelvin instability by comparing the 5.65-day wave in Venus PCM with the 5.8-day wave simulated by AFES-Venus, another Venus General Circulation Model. Similarities are also evident between the 8.5-day wave in Venus PCM and the 7-day wave obtained in AFES-Venus. The long-term variations in the AM budget indicate that the 5.65-day wave is the dominant factor of the oscillation on the SR, and the 8.5-day wave plays a secondary role. When the 5.65-day wave grows, its AM and heat transport are enhanced and accelerate (decelerate) the lower-cloud equatorial jet (cloud-top mid-latitude jets). Meanwhile, the 8.5-day wave weakens, reducing its deceleration effect on the lower-cloud equator. This further suppresses the meridional gradient of the background wind and weakens instability, leading to the decay of the 5.65-day wave. And vice versa when the 5.65-day wave decays

Wave activity in and below Venusian clouds with the IPSL Venus GCM

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Recent analyses mostly based on Akatsuki datasets brought many observational informations about the planetary-scale waves (Imai et al., 2019; Kajiwara et al., 2021) and thermal tides (&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;Scarica et al., 2019, &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;Akiba et al., 2021) at the top of the Venusian cloud layer. &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;Further analysis &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;of these data&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; has enabled to build a view of the angular momentum balance at the cloud top, as a component of our understanding of superrotation (Horinouchi et al., 2020). &amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;To help interpret and understand these wave activities and their impact on the angular momentum budget both in and below the cloud layer, the Venus Global Climate Model (GCM) we are developing at Institut Pierre-Simon Laplace (IPSL) is used in its latest configuration. Similarly to what was done with earlier configurations (Lebonnois et al., 2016), waves are extracted from the simulations to analyze (i) the thermal tide components, (ii) the dominant planetary-scale waves present in the cloud layer, Kelvin- and Rossby-type waves with periods close to 4-6 Earth days, and (iii) wave activity occurring in the deep atmosphere, below the cloud, corresponding to large-scale inertio-gravity waves. These different waves will be compared to observations to assess how the IPSL Venus GCM reproduces observational constraints. Angular momentum budget as evaluated in the GCM simulations will be discussed, with emphasis &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;on&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; the cloud top region.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;References:&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Akiba M. et al. (2021), JGR Planets 126, doi:10.1029/2020JE006808&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Horinouchi T. et al. (2020), Science 368, 405&amp;amp;#8211;409, doi:10.1126/science.aaz4439&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Imai M. et al. (2019), JGR Planets 124, doi:10.1029/2019JE006065&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Kajiwara N. et al. (2021), JGR Planets 126, doi:10.1029/2021JE007047&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Lebonnois S et al. (2016), Icarus 278, 38-51, doi:10.1016/j.icarus.2016.06.004&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Scarica P. et al. (2019), Atmosphere 10, 584, doi:10.3390/atmos10100584&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;</jats:p