TP11
Following decades of limited exploration, Venus is once again in the spotlight of planetary exploration, with an exciting wave of missions set to transform our understanding of this enigmatic world. ESA's EnVision aims to explore Venus, uncovering clues about its geological history and activity, interior structure, atmospheric composition, and long-term climate evolution. Beyond EnVision, other planned space missions (DAVINCI+, VERITAS, Shukrayaan-1, CLOVE), as well as a diverse array of scientific activities, including ground-based observations, laboratory experiments, analogue studies, algorithm development and theoretical modeling are contributing to a comprehensive understanding of Venus, with a growing need for increasingly consistent coupling between processes and physical layers, from the core to the upper atmosphere.
We welcome contributions from all areas of Venus research, including interior processes, surface geology and geomorphology, atmospheric dynamics, laboratory simulations, and past mission data analysis. By bringing together diverse expertise, this session aims to enhance our understanding of Venus' history and current state, while exploring its broader implications for planetary evolution throughout the Solar System and beyond.
Session assets
ESA’s Envision mission is a holistic investigation of Venus’ interior, surface and atmosphere, aimed at improving our understanding of the geodynamic, geological and climatic history and activity of our nearest planetary neighbour. To achieve that, we need a series of complimentary observations at global, regional and local scales, from different instruments and in different modes, and repeated observations for change detection. Envision will carry an integrated instrument suite of spectrometers (VenSpec), a Subsurface Radar Sounder (SRS) and a Synthetic Aperture Radar (VenSAR) that will collect these data. This will be further complemented by gravity and radio occultation observations using the satellite communications system to Earth.
Whilst we would like to image the entire planet at high resolution using the SAR instrument, that is not feasible in the 6-sidereal-day nominal mission life, hence Envision’s imaging strategy is targeted: collecting nested, multi-modal images which will be used to answer its complex science questions. At least 20% of the surface of Venus will be imaged using the SAR at 30 m spatial resolution (twice and at different angles, for generation of stereo topography for at least 18% of the surface) with a smaller fraction imaged a third time (for change detection) or at dual-polarisation, and an even smaller fraction imaged at 10 m resolution for detailed geomorphological analysis. The stereo-derived topography and Envision’s near-global altimetry data will be vital to answer science questions involving Envision’s other instruments and for its holistic science investigations. Considering EnVision’s overall scientific objectives, as well as individual instrument goals, synergies, and limitations, the key question then becomes how we decide which areas should be imaged and in which modes?
The Envision Science Working Team (SWT) formed an ROI Working Group (ROIWG), which was tasked with compiling a list of surface features on Venus, the imaging of which will help address the Envision Science Objectives. The list contains named and located features of interest, of all types (including, but not limited to, tectonic, volcanic, and impact features, and aeolian landforms), which was in turn used to construct Regions of Interest (ROIs), in a semi-automated, semi-objective way. It is anticipated that the imagery collected across the ROIs will capture a representative sample of its geological terrains and key features. These ROIs will thus form the basis of Envision’s SAR and radiometric imaging strategy and planning, as well as the strategy for the subsurface radar high density observations. Here we summarise the process and present an example of Envision’s ROIs (e.g. Figure 1) and how they will be used to optimize the scientific return of the EnVision mission. This target lists will be used by the Envision SWT to construct the mission Science Activity Plan for the Science Measurement Phase. In the future, as the mission advances, this target list will evolve, will be opened to community input, and will remain central to maximizing the value of synergistic, multi-instrument investigations of our sister planet.
Figure 1. Illustration of EnVision’s planned Regions of Interest (ROIs) as published in the Definition Study Report or Red Book (ESA-SCI-DIR-RP-00, European Space Agency, Nov 2023) with a selection of known target features as well as the geological terrains they would intersect, overlain on the global Magellan SAR image mosaic.
How to cite: Mason, P. J. and the Envision Science Working Team: Defining Envision’s Regions of Interest (ROI): from a community-led feature list to a targeted imaging strategy, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-406, https://doi.org/10.5194/epsc2026-406, 2026.
1. Introduction
In this study, we analyse Venus zonal winds derived under the cyclostrophic approximation using the complete temperature sounding datasets from the VeRa [1,2] and VIRTIS [3,4,5] instruments onboard Venus Express. We compare winds retrieved from these complementary temperature sounding techniques, using two wind retrieval methods, and cross-validate the results against cloud-tracked and ground-based wind observations.
2. Mesosphere dynamics
As a slowly rotating planet, Venus mesospheric circulation is largely governed by the cyclostrophic regime, in which the zonal winds can be reconstructed from the temperature field through the thermal wind equation [6]. In addition to the zonal super-rotation, which extends from the surface to the lower mesosphere and reaches maximus speeds near the cloud tops (~70 km), the mesosphere is characterized by a strong variability both on day-to-day as well as longer timescales, and the presence of wave motions that are thought to contribute to the maintenance of the atmospheric circulation [7].
3. Temperature retrievals
The thermal structure of Venus mesosphere was investigated by two complementary experiments on board Venus Express: VIRTIS (Visible and Infrared Thermal Imaging Spectrometer) and VeRa (Radio Science Experiment). The VIRTIS-M dataset spans December 2006 to January 2010 (orbits #23 to #843) and includes nightside observations between 65 and 86 km (100 – 1 mbar). Temperatures were retrieved on 67 pressure levels, with hundreds to thousands of profiles per orbit [4,5].
VeRa provided broader temporal and vertical coverage from July 2006 to January 2014, delivering more than 900 temperature profiles on both day- and nightsides between 45 and 90 km with a vertical resolution of 500 m. In addition, VeRa retrieved vertical pressure profiles [1,2]. Both instruments mainly sampled the Southern Hemisphere, with fewer observations in the Northern Hemisphere due to orbital constraints.
Figure 1 shows the latitude-altitude temperature fields for both datasets. Both experiments reveal a consistent thermal structure, including a pronounced temperature inversion (cold collar) poleward of 60°. Above 75 km (≈20 mbar), temperatures generally increase toward the pole.
Figure 1: (Left) Temperature cross-section obtained combining the whole VIRTIS-M dataset. The data was acquired between 14 May 2006 and 15 August 2008 (orbits 23-843). (Right) Temperature cross-section obtained combining all VeRa observations. The data was acquired between July 2006 and January 2014.
4. Zonal Wind Structure
Zonal thermal winds were derived from VIRTIS and VeRa temperature soundings using the thermal wind equation [8,9]. The retrieved circulation shows: (1) a midlatitude jet between 30° and 60° latitude, peaking at 110-160 m/s near 40 mbar; (2) a rapid decrease in wind speed poleward of 60°; and (3) decreasing wind speeds with altitude above the jet.
Figure 2 shows zonal wind cross-sections derived from the VIRTIS (left) and VeRa (right) temperature fields. Both datasets reveal similar circulation patterns, although VeRa derived jet reaches higher velocities (>160 m/s). As discussed in [9], these differences may result from the different temperature sounding techniques.
Future work includes comparisons with cloud-tracked and ground-based winds, and the application to VeRa data of an alternative retrieval method based on the meridional slope of pressure surfaces, which, unlike the VIRTIS wind retrievals, does not require a lower boundary condition.
Figure 2: Zonal wind cross-sections obtained from: (Left) VIRTIS temperature field, and (Right) VeRa temperature field.
References
[1] Tellmann, S., et al., J. Geophys. Res., 114, E00B36, doi:10.1029/2008JE003204.
[2] Tellmann, S. et al., Icarus, doi:10.1016/j.icarus.2012.08.023
[3] Drossart, P. et al. (2007) PSS, 55:1653–1672
[4] Grassi D. et al. (2008) JGR., 113, 2, E00B09.
[5] Migliorini, A. et al. (2012) Icarus 217, 640–647.
[6] Newman, M. et al. (1984) J. Atmos. Sci., 41, 1901-1913.
[7] Sanchez-Lavega, A. et al. (2017) Space Science Reviews, Volume 212, Issue 3-4, pp. 1541-1616.
[8] Piccialli A. et al. (2008) JGR, 113,2, E00B11.
[9] Piccialli A. et al. (2012) Icarus, 217, 669–681
How to cite: Piccialli, A., Tellmann, S., Grassi, D., Migliorini, A., Piccioni, G., Pätzold, M., Robert, S., and Mahieux, A.: Thermal winds in Venus mesosphere derived from the VIRTIS and VeRa temperature soundings, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-167, https://doi.org/10.5194/epsc2026-167, 2026.
Introduction
The sulfuric acid clouds of Venus located at altitudes of 50–70 km play an important role in the energy budget of Venus. While this cloud layer reflects approximately 80% of the incident solar radiation, it absorbs most of the remaining energy, thereby determining the thermal structure of the whole atmosphere [1]. Sulfur dioxide, the chemical precursor of these clouds, is transported from the lower cloud layer and converted into sulfuric acid through photochemical reactions at the cloud top [2]. Therefore, clarifying the spatial distribution and transport processes of sulfur dioxide is essential for understanding the mechanisms that form and maintain the Venusian clouds. Furthermore, an unidentified UV absorber dominates solar energy absorption in the ultraviolet range and significantly influences dynamical structures, such as superrotation and thermal tides, by varying solar heating rates. There are likely complex feedbacks where atmospheric motions vary the distribution of these materials, which in turn induces changes in absorption and reflectance, modulating the solar energy supply.
These atmospheric motions range hierarchically from planetary-scale waves to local turbulence across various spatio-temporal scales. However, polar-orbiting observations so far have been limited by spatio-temporal continuity, making it difficult to continuously capture short-term fluctuations and global-scale dynamics. In contrast, the Japanese Venus orbiter, Akatsuki, has conducted high-frequency observations of the entire Venusian disk at 2-hour intervals using the Ultraviolet Imager (UVI) from a low-inclination orbit. Our previous research using approximately 15,000 dual-channel image pairs (283 nm and 365 nm) revealed that planetary-scale waves, such as thermal tides and Kelvin waves, excite fluctuations in the distribution of these materials [3]. However, these waves alone primarily induce periodic oscillations. The net transport that effectively carries materials to the cloud top is thought to be driven by the complex combinations of waves, chemical reactions of materials lifted upward, and dynamical processes such as small-scale turbulence and diffusion. In this study, we performed a detailed periodicity analysis and morphological discussions using snapshots to elucidate this material supply mechanism.
Methods
We analyzed over 15,000 pairs of 283- and 365-nm UV images captured by Akatsuki/UVI. These images are Level 3b data products, consisting of radiance maps calibrated on a longitude-latitude grid (0.125-degree resolution). To reduce computational costs and improve the signal-to-noise ratio, the data were spatially binned to a 1-degree resolution. By comparing the observed reflectance distributions at 283 nm and 365 nm with modeled reflectances generated by radiative transfer calculations, we utilized an iterative algorithm to determine the optimal pairs of the sulfur dioxide mixing ratio and the imaginary part of the refractive index of the clouds, a proxy for the unidentified absorber. These retrievals were performed for the entire dataset of 15,000 image pairs.
Results
A longitude-time two-dimensional Lomb-Scargle analysis was conducted on the equatorial distributions of sulfur dioxide and the unidentified absorber (Fig. 1). The results showed that for short-term fluctuations of less than 50 days, a westward-propagating wavenumber-1 structure with a 4-day period was most dominant, likely reflecting vertical atmospheric oscillations associated with equatorial Kelvin waves. Wavenumber-2 components were also identified. On longer timescales of approximately 200 days, signals corresponding to the semi-diurnal thermal tide (58-day period) and eastward-propagating wavenumber-2 components appeared strongly. The signals in the periodogram were not confined to specific peaks but were distributed across a broad frequency band, suggesting that the superposition of various wave components drives effective material transport.
In snapshots taken every two hours, the sulfur dioxide distribution, unlike that of the unidentified absorber, showed dark Y-shape structures [4]. This captures the dynamics where sulfur dioxide upwelling in the equatorial region is photochemically depleted while being transported to mid-to-high latitudes by meridional circulation and latitudinal shear of superrotation, providing evidence for the irreversible supply of sulfur dioxide to the cloud top. Furthermore, we observed the splitting of single concentration regions of sulfur dioxide as they moved with the superrotation (Fig. 2). This phenomenon is difficult to explain by the linear superposition of waves alone, suggesting that such non-linear processes contribute to the net transport of materials.
Finally, we investigated the relationship between the long-term temporal variations of the cloud-tracked zonal wind speed [5] and the abundance of the unidentified absorber, which can influence solar heating rates. The results showed a negative correlation between these two parameters on a decadal scale, while a strong positive correlation was observed on a scale of 2–3 Venusian years. This suggests the existence of a feedback between material distribution and dynamics through radiative heating.
Fig 1. 2D Lomb-Scargle periodograms of equatorial sulfur dioxide and unidentified absorber. The dashed lines indicate the phase velocity of the Kelvin wave.
Fig 2. A sequence of the maps cloud-top sulfur dioxide with 2-hour intervals from 23:01 on April 8, 2018 to 21:01 on April 9. The panel numbers indicate the temporal order.
References
[1] Titov et al., 2007, AGU Geophys. Monogr. Ser., 176, 121-138.
[2] Mills and Allen, 2007, Planet. Space Sci., 55, 1729-1740.
[3] Iwanaka et al., 2025, J. Geophys. Res. Planets, 130, e2024JE008775.
[4] Rossow et al., 1980, J. Geophys. Res., 85, 8107-8128.
[5] Horinouchi et al., 2024, J. Geophys. Res. Planets, 129, e2023JE008221.
How to cite: Iwanaka, T., Imamura, T., Aoki, S., Marcq, E., and Sagawa, H.: How the Venusian Atmospheric Dynamics Shapes Cloud-Top Sulfur Dioxide Derived from Akatsuki/UVI, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-313, https://doi.org/10.5194/epsc2026-313, 2026.
Introduction
On Venus, 85,000 volcanic edifices have been identified (Hahn and Byrne, 2023), and between 40 and 120 per Earth year could be active (Byrne and Krishnamoorthy, 2022; van Zelst, 2022). The question of volcanism is central to determining the long-term and recent evolution of the atmosphere (Gillmann et al., 2022). The climatic impact of volcanic outgassing on Venus is not known, but the sulphuric acid cloud deck, between 47 and 70 km, could be maintained through a supply of SO2 gas (Bullock and Grinspoon, 2001). Volcanic plume destabilising the cloud chemistry is the main hypothesis for the periodical variations of mesospheric SO2 (Esposito, 1984; Marcq et al., 2013). Recent analysis of Magellan images showed geomorphological variations over a few months (Herrick and Hensley, 2023; Sulcanese et al., 2024), and hot spots have been observed by Venus Express, both suggesting possible present volcanic activity (Smrekar et al., 2010; Shalygin et al., 2015). Nevertheless, the characteristics of volcanic plumes on Venus remain unknown (Wilson et al., 2024).
The study of the exotic, hot, sulphur cycle of Venus is a priority of the European, U.S. and international scientific community, with the observations of active volcanism the primary target. The ESA’s EnVision, and two NASA missions, DAVINCI (Garvin et al., 2022) and VERITAS, were all three selected to launch around 2031. It is therefore important to constrain volcanic plume dynamics on Venus.
Lefèvre et al. (2025) adapted a 1D eruption column for Venus, and showed that explosive volcanism would preferably reach 15 km of altitude, and that the super-rotating winds have a substantial impact by plume-bending of reducing the height of plumes. However, discrepancies between 1D and 3D are known for Earth volcanic plumes (Costa et al., 2016), especially for complex features of strong plumes. We propose to adapt a 3D plume model for the Venusian environment to resolve the vertical propagation of strong plume.
Model
The ASHEE solver (Cerminara et al., 2016) is conceived to numerically simulate the dynamics of compressible multiphase flows, focusing on volcanic plumes and dilute pyroclastic density currents, i.e. gas-particle mixtures with multiple gas components and solid particle classes for pyroclasts modelling. The equations solved are the continuity equations for all the phases, the momentum and energy of the mixture, and the equations for the dynamic LES model. The ASHEE was adapted for Venus, and for the first time in 3D, the vertical propagation of volcanic plumes is resolved.
Results
Under extreme vent conditions (mass flow rate, exit temperature and velocity), the 3D plume can reach the clouds (48-70 km), as seen in Fig 1. There are significant discrepancies between the height reached by the plume in 1D versus 3D. The parametrization of entrainment between the plume and ambient air in the 1D is valid for the Earth atmosphere but not valid for the Venus environment. The impact of the wind shear, volatile mass fraction and composition will be assessed. The generation of secondary plumes will be discussed. The volatile flux from the plume into the atmosphere will be presented.
Figure 1: Top: contour for ash. Bottom: Vertical profile of the plume radius. The two panels are for a mass flow rate of 109 kg/s, an exit temperature of 1600 K, an exit velocity of 280 m/s and a 5%wt volatile composed of water with the 1D and 3D model.
Volcanic eruptions generate a spectrum of waves in the atmosphere, from infrasound to gravity waves. The characteristics of those waves were never established for Venus and will be shown. The dispersion of the ash solid particle on the radar reflectivity will be discussed.
References
- Bullock, M. A., & Grinspoon, D. H. (2001). Icarus, 150:19–37.
- Byrne, P. K., & Krishnamoorthy, S. (2022). Journal of Geophysical Research: Planets, 127(1):e2021JE007040.
- Cerminara, M., Esposti Ongaro, T., & Berselli, L. C. (2016). Geoscientific Model Development, 9:697–730.
- Costa, A., Suzuki, Y. J., Cerminara, M., et al. (2016). Journal of Volcanology and Geothermal Research, 326:2–25.
- Esposito, L. W. (1984). Science, 223:1072–1074.
- Garvin, J. B., Getty, S. A., Arney, G. N., et al. (2022). The Planetary Science Journal, 3(5):117.
- Gillmann, C., Way, M. J., Avice, G., et al. (2022). Space Science Reviews, 218(7):56.
- Hahn, R. M., & Byrne, P. K. (2023). Journal of Geophysical Research (Planets), 128:e2023JE007753.
- Herrick, R. R., & Hensley, S. (2023). Science, 379:1205–1208.
- Lefèvre, M., Cerminara, M., & Costa, A. (2025). Journal of Geophysical Research: Planets, 130(10):e2025JE009320.
- Marcq, E., Bertaux, J.-L., Montmessin, F., et al. (2013). Nature Geoscience, 6:25–28.
- Shalygin, E. V., Markiewicz, W. J., Basilevsky, A. T., et al. (2015). Geophysical Research Letters, 42:4762–4769.
- Smrekar, S. E., Stofan, E. R., Mueller, N., et al. (2010). Science, 328:605.
- Sulcanese, D., Mitri, G., & Mastrogiuseppe, M. (2024). Nature Astronomy, 8:973–982.
- van Zelst, I. (2022). Journal of Geophysical Research: Planets, 127(12):e2022JE007448.
- Wilson, C. F., Marcq, E., Gillmann, C., et al. (2024). Space Science Reviews, 220:31
How to cite: Lefevre, M. and Cerminara, M.: 4D modelling volcanic plume on Venus, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-75, https://doi.org/10.5194/epsc2026-75, 2026.
Introduction: On Venus, variations in SO2 content in the cloud tops have been suggested as evidence of recent volcanism [1]. The Pioneer orbiter observed a steep decline in SO2 content in the cloud tops between 1978 and 1983 which may have been caused by a recent injection of volcanic SO2 into the mesosphere [2]. [1] found a similar decline in the SO2 content in the Venus Express data between 2006 and 2014, although they suggest that temporal variations are caused by episodic variations in atmospheric mixing of SO2 rich troposphere and SO2 poor mesosphere. [3] found high degrees of temporal and spatial variations in SO, SO2, (SO+SO2) and SO/SO2 ratio across all available datasets. No mechanism was suggested to explain these variations. It is debated whether these variations are caused by either volcanic SO2 influx, by atmospheric processes or by a combination.
Atmospheric SO2 is consumed by weathering of surface rocks, where Ca-bearing minerals react with SO2 to create anhydrite (CaSO4). Atmospheric SO2 may or may not be buffered by interactions with anhydrite and plagioclase [4]. It is therefore unclear whether recent volcanic SO2 degassing is required to maintain the current SO2 abundance in the atmosphere or if it the current SO2 content is in equilibrium with this mineral assemblage [5].
The goal of this study is to experimentally derive SO2 degassing kinematics and their dependence on magma temperature at Venus’ current atmospheric surface pressure (92 bar). This is done by conducting experiments in a gas-mixing furnace at relevant magma temperatures (1250–1400 °C) and two different pressures; a ~0,005 bar vacuum and a 1 bar CO2 atmosphere. From this, the pressure and temperature dependance of degassing kinematics is extrapolated to Venus’s surface conditions.
Methods: SO2-rich starting materials are made in accordance with composition PPG07 from [6]. This a haplobasaltic composition based on the anorthite (CaAl2Si2O8) + diopside (CaMg2Si2O6) eutectic (An36Di64). CaSO4 is added as the volatile component. Boron is added to reduce the system liquidus temperature. The lower temperature at glass synthesis stage mitigates the evaporative loss of SO2 during the synthesis of the starting material, as well as lowering the melting temperature of samples. The mixture is vitrivied in a crucible for a short duration.
This material is ground to a powder. Small amounts of this powder are mixed with polyvinyl alcohol glue to create a viscous slurry. Around 20 mm length of thin (0.1mm) Pt wire is bent around rod for 1–2 rotations to create a loop (r ~ 1.5 mm) with a straight piece of wire extending from the loop. The loop is used to scoop up the slurry. The slurry is dried and hardened with a lighter. The Pt wire attached to a carousel of thicker Pt wire attached to an alumina rod. The rod with samples attached is lowered to the hot spot of the gas-mixing furnace at which point the experiment time starts.
The 1 bar experiments were performed in a CO2 atmosphere by flowing 200 cm3/min CO2 through the furnace with a flow controller in a temperature range of 1250–1400 °C. The vacuum experiments are all done at 1250 °C. Low pressures (~0,005 bar) are achieved by attaching an Alcatel vacuum pump to the furnace.
After the experiment time elapsed, the molten beads are taken out of the furnace and quenched. The dimensions of the resulting glass beads are measured before mounting them in epoxy and analyzing their major oxide composition as well as SO2 content, divided by the original SO2 content (Xt/X0) with an EPMA.
Experiments are done with various experiment times for each combination of P and T. As the loops with starter material reach the hot spot of the furnace, the outside heats up first and starts degassing while the inside is not yet hot enough for diffusion to replenish the outside with SO2. This causes zoning at the beginning of the experiment. As the center of the bead reaches a high enough temperature to start efficient diffusion, the concentration of SO2 throughout the bead equilibrates. From this point, the beads follow a degassing curve (figure 1). This curve is extrapolated to where Xt/X0 = 1. The corresponding time is t0, the apparent lag time, and is subtracted from the experiment time.
Figure 1: Xt/X0 of all beads from experiments done at 1350 °C under a 1 bar CO2 atmosphere. 1 minute experiments are within the lag time (t0) of 3.5 minutes, constrained from the degassing curve.
From the bead dimensions, the SO2 fraction and the experiment time (minus t0), a reaction rate constant K* is calculated using the thermodynamic framework outlined in [7]. Values for K* from all beads with same P and T are averaged. The effect of temperature on K* is constrained by regression through all data at 1 bar. This effect is assumed to be the same at all pressures. The effect of pressure is constrained at 1250 °C.
These effects are extrapolated to predict the reaction rate constants under Venus surface pressure and relevant magma temperatures. These are used to calculate absolute SO2 fluxes evaporating from silicate lavas in different magmatic settings; a putative global resurfacing event, a collection of large lava lakes and a collection of lava flow channels, in order to see constrain what scale of events can provide a volcanic signature from SO2 degassing.
Results: Experiments have been done and analysis is ongoing, results will be presented at the meeting.
Acknowledgements: This study was supported by ERC StG VenusVolAtmos awarded to ESS. We want to thank Maik Trogisch at Münster University for his diligent preparation of our samples.
References: [1] Marcq et al. (2013), Nature Geoscience [2] Esposito (1984), Science [3] Vandaele et al. (2017), Icarus [4] Zolotov (2018), Reviews in Mineralogy and Geochemistry [5] Wilson et al. (2024), Space Science Reviews [6] Pangritz et al. (2022), ACS Earth and Space Chemistry [7] Sossi et al. (2019), GCA
How to cite: Jorritsma, J., Aerts, G., Berndt, J., Klemme, S., and Steenstra, E.: Experimental quantification of the evaporative loss of SO2 from silicate melt: implications for the Venusian sulfur flux, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-456, https://doi.org/10.5194/epsc2026-456, 2026.
Introduction
The Venus Planetary Climate Model (Venus PCM) is a full-physics atmospheric model designed to simulate the thermal structure and circulation of Venus from the surface to the upper atmosphere. The model couples the dynamical core with a radiative transfer scheme that allows the temperature field to be computed self-consistently[1]. The solar radiation module of the Venus PCM was updated using a two-stream scheme from the Generic PCM, allowing a full coupling between solar heating rates, cloud particles and atmospheric composition. The thermal infrared transfer is treated using a Net Exchange Rate matrix formalism[2]. This infrared scheme computes radiative exchanges between atmospheric layers, the surface, and space over the 1.7–250 μm spectral range, allowing radiative heating and cooling rates to be evaluated consistently within the Venus PCM[3]. The opacity calculation includes molecular absorption, cloud opacity, and continuum/CIA contributions, with cloud optical properties commonly based on the Haus cloud model retrieved from Venus Express and Venera observations[4]. For this framework, studying the Venus lower atmosphere is particularly important because uncertainties on opacity and continuum absorption in several windows strongly affect the radiative exchange between the deep atmosphere and the cloud layer.
Control parameters of cloud layer and deeper atmosphere
Particular attention was given to the opacity in the infrared windows between 2 and 10 μm, as well as in the 18-30 μm region, in the far wing of the 15-μm band of CO₂, since these spectral intervals regulate the radiative exchanges between the deep atmosphere, the cloud base, and the overlying cloud layer, and therefore strongly influence the simulated temperature profile from the cloud convective region to the surface. However, after updating the CO₂–CO₂ CIA and CO₂ line-shape treatments[5,6], the modeled opacity in these windows remains insufficient to reproduce the observed thermal structure, leading to excessive radiative cooling and underestimated temperatures in the lower atmosphere.
Temperature structure in the cloud
The temperature at the cloud base mostly depends on the amount of solar energy absorbed in the middle cloud and below, as this energy is balanced by thermal emission mostly to space in the 10-30 μm spectral region at the top of the convective layer (interface between upper and middle cloud, as shown in the Figure 1).
Figure 1. This figure compares the spectral contributions of different opacity sources at the level 1x104 pa and 250k (nearly the top pf the convective layer), including the 2016 reference dataset, the updated HR2024 dataset, individual gas absorptions, cloud extinction, and CIA/continuum terms. Gas lines dominate the strong absorption regions, while clouds and continuum absorption provide smoother background opacity. The shading color on the background represents the narrowbands used in the radiative transfer modules.
Figure 2. Net infrared flux per narrowband (positive upward),which illustrates the energy exchange from layer to layer in every narrowbands. Left plot: corresponding to the Figure1 SO2 curve (green line) Right plot: Figure 1 SO2 former curve (pink line)
To evaluate the sensitivity of radiative transfer in the 18-30 μm spectral window, we performed a series of sensitivity experiments in which the SO₂ abundance, cloud optical thickness, and H₂O mixing ratio were adjusted within observationally constrained ranges. These tests were designed to isolate the relative influence of key opacity sources on the thermal structure of the Venus atmosphere, with particular emphasis on the potential temperature response within the cloud layer and near the cloud base.
Figure 3. Potential temperature of different SO2 concentration cases
Stability in the stable layer below the cloud
With the obtained shape of the opacity in the 2-10 micron spectral region, energy exchanges between lower layers and the cloud base are too efficient in the stable layer (30-50 km), leading to under-estimated temperatures in the deep atmosphere. To further investigate the origin of this excessive radiative coupling, we tested the sensitivity of the model to the H₂O–CO₂ continuum absorption and to different vertical distributions of H₂O volume mixing ratio below the clouds. The results indicate that H₂O plays a major role in controlling the radiative stability of the deep atmosphere. In particular, doubling the H₂O continuum reduces the transparency of the 5–10 μm window and increases the potential temperature under the cloud base by approximately 30K. Similarly, increasing the H₂O abundance in the sub-cloud region modifies the net infrared flux and weakens the excessive energy exchange between the deep atmosphere and the cloud layer. These experiments suggest that even moderate changes in H₂O opacity can produce a significant response in the thermal structure below the clouds.
The influence of other relevant sources of opacity and comparison with latest reasearch have been explored: HCl and CO2 dimer CIA in 3-4 micron window, CO in 2.3 micron window[7][8]. These three spectral regions are key to control the radiative exchanges between the deep atmosphere and the cloud base and therefore represent critical targets for improving the representation of lower-atmosphere stability in the model.
References
[1] Garate-Lopez, I., & Lebonnois, S. (2018). Icarus, 314, 1-11, doi : 10.1016/j.icarus.2018.05.011
[2] Eymet, V.,et al. (2009). Journal of Geophysical Research: Planets, 114(E11), doi : 10.1029/2008JE003276
[3] Lebonnois, S.,et al. (2015). Journal of Geophysical Research: Planets, 120(6), 1186-1200, doi : 10.1002/2015JE004794
[4] Haus R, Kappel D, Arnold G.(2015). Planetary and Space Science, 117:262-294. doi:10.1016/j.pss.2015.06.024
[5] Tran, H et al. (2011). Journal of Quantitative Spectroscopy and Radiative Transfer, 112(6), 925-936, doi : 10.1016/j.jqsrt.2010.11.021
[6] Tran, H et al. (2024). Icarus 422, 116265, doi: 10.1016/j.icarus.2024.116265
[7] Takahashi et al. (2023). Journal of the Meteorological Society of Japan 101, 39–66, doi: 10.2151/jmsj.2023-003.
[8] Takahashi et al. (2024). Journal of the Meteorological Society of Japan, 102, 469–483, doi: 10.2151/jmsj.2024-025.
How to cite: Han, P., Lebonnois, S., Kang, H., and Lee, Y. J.: Radiative control of Venus atmosphere temperature structure, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-806, https://doi.org/10.5194/epsc2026-806, 2026.
Introduction
Despite similarities between Earth and Venus in size and bulk composition, Venus is currently one of the most enigmatic planets in the Solar System, with its surface shrouded by a dense CO2-rich atmosphere. Obtaining data from Venus’ lower atmosphere below the planetary boundary layer (PBL) has been a challenge. In the coming decade, several missions to Venus are planned (e.g. [1]) that aim to image Venus nightside thermal emission in the NIR spectral windows [2] from orbit and in addition to future descent probes (e.g. [3]) that will measure lower atmospheric properties including species abundance, temperature, pressure, and wind speed. Until such data becomes available in the next decade, we have to rely on Atmosphere Radiative Transfer Modelling (ARTM) and existing measurements to expand our understanding and prepare for future data processing.
Venus’ high pressure and temperature conditions require us to consider absorption line broadening effects. Since these effects are poorly understood for such environments, they are usually accounted for by implementing a modified molecular absorption line profile (CO2 and H2O). An additional continuum opacity is often required to match observations (NIR ARTM) which we assume is due to collision induced bands and far wing contributions of allowed CO2 transitions, seemingly varying with square of number density (e.g., [4-8]). Calculation of such a term depends on the temperature – pressure relationship used in the ARTM. The temperature structure of the lower atmosphere is contested – the failure of thermal sensors on Pioneer Venus probes resulted in no details of the PBL making their way to the Venus International Reference Atmosphere (VIRA [9]) which is widely used in the community as a standard temperature- pressure profile. Contrary to this, the VeGa-2 [10] descent probe’s higher resolved observations are often considered impractical as they point to a temperature lapse rate exceeding the adiabatic lapse rate. However, Lebonnois and Schubert (2017) have shown that such a structure is plausible through a vertical gradient of N2, resulting in an almost pure CO2 atmosphere close to the surface [11].
In this work we apply our ARTM to different temperature-pressure profiles (VIRA and VeGa-2) and study their effect on the of continuum opacity required to match the model with data from Venus Express.
SPICAV dataset from Venus Express:
The Spectroscopy for the Investigation of the Characteristics of the Atmosphere of Venus (SPICAV) suite on board Venus Express (VEX) made spectrally relatively high-resolution observations of Venus’ nightside in the spectral range of 0.65–1.7 µm. The synthetic radiance generated by our ARTM is compared to SPICAV IR night-side observations on VEX orbit 34 [12] and additional processing by [13].
Radiative Transfer Model
Our ARTM is a combination of several open-source tools – Helios-k [14] to compute line by line absorption cross sections ofCO2 using HITEMP 2025 [15] with a sub-Lorentzian line shape identical to [16], the HITEMP 2010 database for H2O with a super-Lorentzian lineshape, Python for Computational ATmospheric Spectroscopy (Py4CATS) [17] to calculate Rayleigh contributions according to [18], and DISORT [19] implementation [20] to solve the radiative transfer equation. Our cloud model follows that detailed in [21]. Continuum coefficients are free parameters and are adjusted until modeled radiance matches that of the SPICAV observation.
Preliminary results
The figure below shows modeled Venus’ night-side radiances for near nadir geometry using VIRA and VeGa-2 temperature profiles. The continuum opacities have been fitted at each spectral window (consistent with future spectrometers observing in NIR) and the particle density of the lowest cloud layer [21] has been scaled by a suitable factor in order to reproduce radiances found in the SPICAV IR dataset. The assumed emissivity is consistent with that of a basalt sample measured in the laboratory [22].
Figure 1: Venus’ night-side NIR radiances produced by our ARTM compared with SPICAV radiances for VIRA and VeGa-2 temperature profiles, assuming isoprofiles of gas abundances. Shaded ranges indicate wavelengths corresponding to planned future observations.
Our current ARTM produces a good fit to the SPICAV spectrum for both assumptions of temperature structures. We note that the continuum opacity required to fit the model is significantly lowerin the VeGa-2 case (notice the logarithmic representation in Fig. 1). As part of this work, we aim to implement varying CO2 abundances as hypothesized by [11] and investigate the continuum coefficient necessary to fit the data.
The order of magnitude difference in derived continuum at 1.31 µm between the VIRA and VeGa-2 profiles suggests that it would be possible to confirm the existence of a VeGa-2 like lapse rate globally with instruments on the Venus missions in development, if both the surface emissivity and the CO2 opacity were constrained with sufficient accuracy.
Bibliography
[1] Smrekar S. + (2022) IEEE Aerospace Conference (AERO) pp. 1-20
[2] Allen D. A. + (1984) Nature, 307, 222–224
[3] Garvin J. B. + (2022) PSJ, 3(5), 117
[4] Pollack J. B. + (1993) Icarus, 103, 1–42
[5] Bézard B. + (2011) Icarus, 216(1), 173–83
[6] Arney G. + (2014) Journal of Geophys. Res.: Planets, 119 (8), 1860-1891
[7] Fedorova A. + (2014) Planetary and Space Science, 113-115, 66-77
[8] Mueller N. T. + (2020) Icarus, 335, 113400
[9] Seiff A. + (1985) Advances in Space Research, 5(11):3–58
[10] Seiff A. + (1987) Advances in Space Research, 7(12), 323–328
[11] Lebonnois S. and Schubert, G. (2017) Nature Geoscience, 10(7):473–477
[12] Korablev O. + (2006) J. Geophys. Res. 111(E9)
[13] Kappel D. + (2016) EGU General Assembly Vol. 18, EGU2016-7578-1
[14] Grimm J. S. and Heng, K. (2015) ApJ 808 182
[15] Hargreaves R. J + (2025) J. Quant. Spectrosc. Radiat. Transfer 333
[16] Bezard B. + (2009) Journal of Geophysical Research 114
[17] Schreier F. + (2019) Atmosphere, 10(5), 262
[18] Sneep M. & Ubachs W. (2005) Journal of Quantitative Spectroscopy and Radiative Transfer, 92(3), 293–310
[19] Stamnes K.+ (1988) Applied Optics, 27(12), 2502-2509
[20] Buras R. + (2011) Journal of Quantitative Spectroscopy & Radiative Transfer, 112(12), 2028–2034
[21] Haus R. + (2013) Planetary and Space Science, 89, 77-101
[22] Helbert, J. + (2021). Science Advances, 7(3).
How to cite: Das, A., Müller, N., Kappel, D., Rauer, H., Plesa, A.-C., Alemanno, G., and Grenfell, J. L.: Impact of Venus lower atmosphere temperature profile on derived atmospheric continuum in the near infrared, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-1124, https://doi.org/10.5194/epsc2026-1124, 2026.
Introduction
Unlike the other terrestrial bodies in the Solar System, Venus is shrouded in a thick, multi-layered cloud at an altitude ranging from 48 to 70 kilometers[1]. These clouds consist of droplets of liquid SO₂ (70–95% by mass) and H₂O, divided into three modes with radii of approximately 0.3, 1, and 2 micrometers, respectively[2].
The lack of in situ observations (only one in-situ profil of the cloud droplets characteristics[2]) means we have to actively try to model these clouds to understand them. The models developed so far are primarily 1D[3-7], and the few 2D and 3D models are restricted to simplified equilibrium schemes[8-11]. Here, we present the first 3D simulation of Venus's clouds using the Venus PCM[12-13], a global climate that includes chemistry, radiative transfer and dynamics, coupled with the microphysical scheme MAD-VenLA[14-16]. We use this opportunity to make comparison with Akatsuki UV observations.
Method
We coupled the MAD-VenLA model, developed by Guilbon[14], Määttänen[15] and Streel[16], with the Venus PCM. MAD-VenLA is a modal model that describes two particle modes with a lognormal shape and fixed standard deviation. It includes a homogeneous nucleation scheme[17], a simplified parametrization of heterogeneous nucleation, and Brownian coagulation, condensation, and evaporation[14-15]. Additionally, MAD-VenLA incorporates mode merging[18], which allows particles to be transferred from one mode to another. In its latest version, a sedimentation scheme has also been added[16].
Results
We will present the first 3D comparisons between and observations from previous missions.
For example, an ongoing study[19] of the Japanese Akatsuki mission's ultraviolet (UV) observations revealed different reflectivity patterns between sulfur dioxide (SO₂) at 283 nm and the unknown UV absorber at 365 nm at low latitudes. The averaged minimum reflectivity at 365 nm occurred ~2 hours earlier in local time than at 283 nm. Our simulations using the Venus PCM (Fig. 1) reveal the presence of a droplet layer situated in the afternoon at low latitude at 70 km, which could mask the unknown UV absorber below and alter the afternoon albedo, explaining the observations made. These droplets are the result of homogeneous nucleation episodes, which are allowed by the chemistry and vertical transport.
This highlights the need for 3D simulations in order to understand such processes.
Figure 1: Horizontral map of the integrated number of droplets from the top of the atmosphere to a specific altitude (resp. 80,75,70 and 65 km) after 2 venusian days.
References
- P. Mills, L. W. Esposito, Y. L. Yung, Geophys. Monogr. Ser. 176, 73–100 (2007).
- R. G. Knollenberg, D. M. Hunten, J. Geophys. Res. 85, 8039–8058 (1980).
- P. James, O. B. Toon, G. Schubert, Icarus. 129, 147–171 (1997).
- Imamura, G. L. Hashimoto, J. Geophys. Res. 103, 31349–31366 (1998).
- Yamamoto, M. Takahashi, J. Geophys. Res. 111, 2006JE002688 (2006).
- McGouldrick, E. L. Barth, Planet. Sci. J. 4, 50 (2023).
- Karyu et al., Planet. Sci. J. 5, 57 (2024).
- Lee, S. R. Lewis, P. L. Read, Icarus. 206, 662–668 (2010).
- Ando, M. Takagi, N. Sugimoto, H. Sagawa, Y. Matsuda, Journal of Geophysical Research: Planets, in press, doi:10.1029/2019JE006208.
- Karyu et al., Journal of Geophysical Research: Planets, in press, doi:10.1029/2022JE007595.
- Stolzenbach, F. Lefèvre, S. Lebonnois, A. Määttänen, Icarus. 395, 115447 (2023).
- Lebonnois, N. Sugimoto, G. Gilli, Icarus. 278, 38–51 (2016).
- Gilli et al., Icarus. 281, 55–72 (2017).
- Guilbon, thesis, Université Paris Saclay (COmUE) (2018).
- Määttänen, S. Guilbon, J. Burgalat, F. Montmessin, Advances in Space Research. 71,1116–1136 (2023).
- Streel, thesis, Sorbonne-Université (2025).
- Määttänen et al., JGR Atmospheres. 123, 1269–1296 (2018).
- Whitby, F. Stratmann, M. Wilck, Journal of Aerosol Science. 33, 623–645 (2002).
- R. L. S. E. Aliste Castillo et al., BACO-25 conference abstract (2025).
How to cite: Streel, N., Määttänen, A., Lefèvre, F., Stolzenbach, A., Aliste Castillo, R. L. S. E., and Lee, Y. J.: 3D Venus Cloud Modelling: the Venus Planetary Climate Model coupled with a microphysical model, first comparisons, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-306, https://doi.org/10.5194/epsc2026-306, 2026.
Introduction: Venus’s surface composition remains fundamentally unknown, and it is a missing piece about the planet’s evolution. Venus’s permanent cloud cover prevents remote sensing of the surface in visible wavelengths. Nonetheless, surface thermal emission from Venus’s nightside becomes detectable in the CO2 atmospheric windows, notably at 1.02, 1.11, and 1.18 µm [1 – 3]. Atmospheric gaseous absorption/emission attenuates this surface emission, but the surface component dominates the 1.02 and 1.11 µm windows, accounting for 95% and 60% of the total observation, respectively, and 40% in the stronger 1.18 µm window [1]. Surface observations can only be performed on the nightside because reflected direct sunlight from Venus’s dayside dampens the surface contribution [4]. Using IRTF/SpeX observations of the nightside of Venus, we analyse the contribution from the surface emission to investigate potential trends in surface emissivity and surface composition.
Previous ground-based observations: Low-to-moderate resolution spectral image cubes of Venus’s nightside were obtained using the Anglo-Australian Telescope’s infrared imaging spectrometer IRIS to resolve surface thermal emission [1]. Data were affected by limited longitudinal coverage, instrumental issues in treating scattered light, and daytime observations, which partially limited the interpretation of windows shortward of 1.18 µm due to scattered sunlight by Earth’s atmosphere. However, [1] demonstrated that it is possible to create synthetic radiance maps by using the correct topographic elevation and observing angle.
Method: The SpeX instrument acquired Venus observations in the period from 2001 to 2025. The observed nightside radiation is corrected for stray light from Venus’s dayside, thermal emission from the lower atmosphere of Venus, sky background, wavelength calibration, telluric absorption, limb darkening, intrinsic variability in cloud opacity, cloud reflection and atmospheric absorption/emission [1, 5 – 7] and surface temperature [8]. The horizontally uniform thermal structure means that topography controls emission. By using an adiabatic lapse rate, thermal emission can be corrected using NASA/Magellan topography [1, 4, 6, 7, 9 – 11]. The atmospheric contribution can be successfully estimated using dedicated radiative transfer codes, e.g., SMART, which has been extensively used by [1, 5, 12]. By scanning the SpeX slit multiple times across Venus’s disk, we obtained the necessary spatial coverage to map the surface with a spatial resolution ranging from 250 to 400 km (under conservative seeing of 1 arcsec). Geometric correction is applied to retrieve latitude and longitude coordinates for each pixel within the disk and to reconstruct an accurate representation of the Venus disk as seen in each CO2 atmospheric window. We present here a subset of this SpeX dataset obtained for Venus, using a series of observing geometries. The dataset uses the high-throughput low-resolution PRISM mode of the IRTF/SpeX instrument, covering wavelengths from 0.8 to 2.5 µm, with a 60 arcsec slit (as seen in Figure 1), with a nominal resolving power of R ~200 (or R~140 at 1.18 µm).
Comparison with laboratory emissivity data: Measurements of Venus analogue materials have been performed at the Planetary Spectroscopy Laboratory (DLR, Germany) under Venus-like surface conditions [13]. Spectral shifts are dominated by temperature, while pressure and grain size have negligible impacts [14]. Mafic (basalts) and felsic (granitic) rocks have very distinct emissivity values under Venus-like conditions (see Figure 2). Mafic rocks have much higher emissivity than felsic counterparts across Venus’s CO2 atmospheric windows. The emissivity difference between these two families is larger than the ±4% uncertainties due to instrumental and atmospheric effects (shaded in Figure 2), making them distinguishable in ground-based observations [5, 15]. These works establish that it is possible to relate Venus’s surface thermal emission to mineralogy.
Results: Analysis of the IRTF/SpeX data shows that, even under daytime conditions, the 1.02 and 1.11 µm windows are observable (see Figure 1), enabling radiative transfer corrections. These require the aforementioned corrections before they can be translated into radiance maps according to the method in [1]. The resolving power is sufficient to disentangle the contributions from mafic and felsic rocks, while the spatial resolution is sufficient to resolve the highlands signal from that of the plains, allowing us to explore large-scale trends in surface composition. These will be explored by comparing radiance maps from the different CO2 atmospheric windows.
Fig. 1. Observing data from Venus IRTF/SpeX (60 arcsec slit) daytime spectra with Venus’s CO2 atmospheric windows in red. Other atmospheric effects are shown in the figure. The image is obtained by subtracting two positions of the slit acquisition over Venus’s disk.
Fig. 2. Synthetic emissivity [14] under Venus-like conditions for mafic (blues) and felsic (reds) minerals. The black lines depict Venus’s CO2 atmospheric windows. Data kindly provided by DLR (private communication).
References: [1] Meadows, V. S. & Crisp, D. (1996). J Geophys Res Planets 101, E2, 4595; [2] Allen, D. A. & Crawford, J. W. (1984). Nature 307, 222; [3] Pollack, J. B., et al. (1993). Icarus 103, 1; [4] Helbert, J., et al. (2008). Geophys Res Lett 35, 11; [5] Hashimoto, G. L. & Sugita, S. (2003). J Geophys Res Planets108, E9, 5109; [6] Mueller, N., et al. (2008). Geophys Res Planets 113, E00B17; [7] Kappel, D., et al. (2016). Icarus 265, 42-62; [8] Seiff, A., et al. (1985). Adv. Space Res 5, 11, 3-58; [9] Hashimoto, G. L. (2008). Geophys Res Planets 113, E00B24; [10] Smrekar, S. E., et al. (2010). Science 328, 605; [11] Basilevsky, A. T., et al. (2012). Icarus 217, 434; [12] Arney, G., et al. (2014). J. Geophys Res Planets 119, 8, 1860-1891; [13] Helbert, J., et al. (2017). In Venus Modeling Workshop 2022, 8023; [14] Helbert, J., et al. (2021). Sci Adv 7; [15] Treiman, A. H., et al. (2021). Planet Sci J 2, 2, 43.
Funding: DQ acknowledges this work to be supported by FCT - Fundação para a Ciência e Tecnologia, I.P. by project reference and DOI identifier 10.54499/2023.05220.BD
How to cite: Quirino, D., Machado, P., Young, E. F., Bullock, M., Dias, J., Brasil, F., Duarte, J. C., and Green, J. M.: Surface emissivity from the CO2 atmospheric windows at Venus using the NASA Infrared Telescope Facility (IRTF) SpeX spectrograph, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-1069, https://doi.org/10.5194/epsc2026-1069, 2026.
The Magellan radar space mission [1] produced the largest, highest-resolution, most accurate survey of the surface of Venus to date. During the first cycle of the mission, its unique latitude-varying radar observation geometry allowed for the revisit of morphologically-equivalent terrains with a wide array of incidence angles, both in synthetic aperture radar (SAR) mode and in altimetry mode [2,3,4,5]. With the appropriate constraints and processing steps, this enables the reconstruction of the full scattering behaviour (a scattering curve) of distinct rock units [6] across approx. 0-50 degrees of local incidence, offering a unique opportunity to measure the mean radiometric signature of different terrain formations on Venus and, for the first time, map and characterise wavelength-scale surface roughness across the entire planet. Additionally, the derived scattering curves represent the reference scenarios that will enable radiometric comparison of Magellan SAR images with SAR data from upcoming Venus orbiters, even if the acquisition geometry between sensors for a specific target differs significantly [7,8].
To perform this study, we have built a comprehensive method that blends SAR and altimetry backscatter, postprocessed Magellan topography, Magellan radiometry, and geological data from Venus; the method incorporates a physically-constrained stochastic model of uncertainty for each individual backscatter measurement, and provides the framework for scattering models and constraints to appropriately fit the data. Our scattering curve results have been extensively tested against different cycle 1 and cycle 2 SAR and altimetry data to investigate the heterogeneity and/or isotropy of the measured surfaces, and to internally validate the radiometric consistency (absolute and relative) of the observed backscatter estimates.
In this work, we present insights into our findings regarding surface roughness properties for each terrain formation. We discuss the geological interpretation of the results, linking the scale of the retrieved mean roughness with the most-likely surface modification processes. In particular, we demonstrate the separability of the scattering characteristics of rift zones and Tessera terrain from the several plain units across the planet. Additionally, we globally constrain the predicted backscatter values for the forthcoming SAR missions to Venus. This is a critical step towards robust mission-to-mission SAR image intercomparison, enabling inter-mission SAR change detection from a radiometric perspective [9,10], and a key input to consolidate the on-going radar design, operation and data processing for these missions.
Figure 1. Example summary of diffuse scattering results from Magellan SAR backscatter data of Bell Formation (lava flow) units and Tessera terrain.
[1]. Saunders, R. S., et al. "Magellan mission summary." Journal of Geophysical Research: Planets 97.E8 (1992): 13067-13090.
[2]. Ford, John P. Guide to Magellan image interpretation. National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1993.
[3]. Campbell, Bruce A. Use and presentation of Magellan quantitative data in Venus mapping. No. 95-519. US Geological Survey,, 1995.
[4]. Ford, Peter G., and Gordon H. Pettengill. "Venus topography and kilometer‐scale slopes." Journal of Geophysical Research: Planets 97.E8 (1992): 13103-13114.
[5]. Tyler, G. Leonard, et al. "Scattering properties of the Venusian surface: Preliminary results from Magellan." Journal of Geophysical Research: Planets 97.E8 (1992): 13115-13139.
[6]. Ivanov, Mikhail A., and James W. Head. "Global geological map of Venus." Planetary and Space Science 59.13 (2011): 1559-1600.
[7]. Gallardo i Peres, G., P. J. Mason, and R. Ghail. "An End-To-End Inter-Mission Change Detection Algorithm: Between Magellan and Future VenSAR and VISAR Radar Imagery on Venus." 55th Lunar and Planetary Science Conference. Vol. 3040. 2024.
[8]. Gallardo i Peres, Gerard, et al. "A generalized beta prime distribution as the ratio probability density function for change detection between two SAR intensity images with different number of looks." IEEE Transactions on Geoscience and Remote Sensing 62 (2024): 1-14.
[9]. Gallardo i Peres, G., 2022. A proposed change detection method in the framework of the VERITAS & EnVision radar missions to Venus. MSc Thesis. Denmark Technical University.
[10]. Campbell, Bruce A., and Scott Hensley. "Detecting surface change on Venus from Magellan and VERITAS radar images." Icarus 407 (2024): 115773.
How to cite: Gallardo i Peres, G., Mason, P., Ghail, R., Wilson, C., Straume-Lindner, A. G., Granados, A., and Roca i Aparici, M.: Radar Scattering of Venus Terrains: Characterising Surface Roughness in Preparation for the Decade of Venus, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-691, https://doi.org/10.5194/epsc2026-691, 2026.
Introduction
Tessera terrains represent the oldest preserved units on the Venusian surface, covering approximately 8% of the planet [1]. The largest tessera occurrences correspond to crustal plateaus, which are elevated, quasi-circular regions with steep edges and flat tops [2]. Geophysical observations, including small gravity anomalies, low gravity-to-topography ratios, and shallow apparent compensation depths (ADC), suggest that these plateaus are supported by a thickened crust [3]. However, topographic elevations vary across regions; for instance, Ovda Regio exceeds 4 km above the planetary datum, while Alpha Regio rises to ~2 km [4]. Tessera terrain is defined by complex structural patterns, resulting in high radar brightness due to surface roughness [5]. The most penetrative fabric consists of ribbons, which are sets of long, narrow grabens typically spaced 1-5 km apart [6,7]. Deciphering ribbon evolution is essential for understanding the first recorded tectonic deformations of the Venusian lithosphere. This study presents a structural analysis of the morphology of individual ribbon-bounding faults and uses the results to estimate regional extensional strain caused by ribbons across Ovda and Alpha Regio.
Morphological Constraints on Fault Geometry
This study surveyed 130 normal fault scarps across eight tessera regions using NASA Magellan SAR data from Cycle 1 imagery. Analyzing apparent scarp width against radar incidence angle revealed a critical inflection point where scarp widths reach a minimum within an incidence angle range of 33º to 36º. This inflection point is significant because theoretical radar geometry indicates that it can be explained by the transition from radar layover, where the topographic slope is greater than the incidence angle, to radar foreshortening, where the slope is less than the incidence angle [8]. This provides a robust constraint indicating that the current slope of ribbon scarps globally lies within the range of 33º to 36º. This finding was independently validated using Cycle 1 and 3 images to measure radar distortions on 29 scarps in Ovda Regio, yielding fault scarp slopes of 33.9º ± 1.4º via radar parallax. These values are consistent with the 36.4º ± 1.2º slopes reported for normal faults developed on Venusian volcanic plains [9]. We also estimated a representative average height for these ribbon-bounding faults of 396.2 m, representing the graben depth. Assuming a standard fault dip of ~60º the calculated average horizontal extension, or heave, is approximately 228.7 m per fault. Because these consistently shallow slopes (roughly 35°) are much lower than the 60º dip expected for fresh Andersonian normal faults, they provide clear evidence of extensive post-formation scarp degradation.
Ribbon Regional Strain and Geodynamic Implications
Ovda Regio and Alpha Regio were subdivided into a 200x200 km grid where strain calculations were performed. Within each cell, we targeted the zones with highest density of normal faults to estimate the maximum tectonic extension accommodated by ribbons. We used the representative average fault throw and heave derived from our structural analysis, assuming pure dip-slip kinematics and initial fault dip of 60º. Total extension was computed along transects perpendicular to each fault set and, in regions where two distinct graben orientations intersected, calculating the cumulative strain from both sets. These regional strain values were visualized using deformation ellipses, where the size and color intensity represent the magnitude of stretching (Fig. 1). This regional structural analysis revealed fundamentally different extensional regimes. Ovda Regio exhibits a highly heterogeneous structural pattern with radial and concentric ribbon sets, characterized by strong spatial variability and central elevated regions largely devoid of extensional structures. In contrast, the smaller Alpha Regio displays a pervasive fabric of mutually orthogonal ribbons accommodating more homogeneous extension across the entire plateau.
Figure 1: Finite strain distribution across (a) Ovda Regio and (b) Alpha Regio. The orientation of the major axis indicates the principal direction of strain, while ellipse size and color intensity scale with the magnitude of the stretching value (s). (c) Normalized frequency distribution of the areal stretch (s) for Ovda Regio (red bars) and Alpha Regio (blue bars). Overlapping areas are shown in purple. The x-axis represents the magnitude of the stretch (s), and the y-axis represents the normalized frequency of occurrence within the study areas.
We have compared the areal stretch with crustal thickness at each point of the grid (Fig. 2). The data revealed high dispersion, particularly in Ovda Regio, where the greater scatter reflects a heterogeneous transition from areas with no extension to highly stretched zones. Alpha Regio displays a more homogeneous strain pattern, possibly reflecting more uniform lithospheric properties associated with a small crustal plateau. Various tectonic and magmatic processes that contribute to crustal thickening or thinning explains this scattered distribution, which precludes a simple statistical correlation between these parameters. This study establishes ribbons as quantitative markers of the divergent tectonic evolution of Venusian crustal plateaus by using fault-scale geometries to quantify plateau-scale strain.
Figure 2: Correlation between crustal thickness (Tc) and areal stretch (s) calculated for each 200x200 km grid cell. Red circles represent Ovda Regio and blue circles represent Alpha Regio. Tc values are based on the global gravity-topography inversion model from (a) [10] and (b) [11].
Bibliography
[1] Ivanov, M.A., Head, J.W. (1996). JGR, 101, 14861-14908.
[2] Hansen, V.L., Banks, B.K., Ghent, R.R., (1999). Geology 27, 1071-1074.
[3] Grimm, R.E. (1994). Icarus, 112, 89-103.
[4] Bindschadler, D.L., Schubert, G., Kaula, W.M. (1992). JGR, 97, 13495-13532.
[5] Barsukov, V.L., et al. (1986). JGR, 91, D378-D398.
[6] Hansen, V.L., Willis, J.J. (1996). Icarus, 123, 296-312.
[7] Hansen, V.L., Willis, J.J. (1998). Icarus, 132, 321-343.
[8] Connors, C. (1995). JGR, 100, 14361-14381.
[9] Connors, C.D., Suppe, J. (2001). JGR, 106, 3237-3260.
[10] Maia, J., Wieczorek, M.A. (2022). JGR: Planets, 127, e2021JE007028.
[11] Jiménez-Díaz, A., et al. (2015). Icarus, 260, 215-231.
How to cite: Álvarez-Lozano, J., Romeo, I., Jiménez-Díaz, A., Uzkeda, H., Byrne, P. K., and Ruiz, J.: Quantifying Tectonic Extension in Venusian Tesserae: From Fault Scarp Geometry to Regional Strain Analysis, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-48, https://doi.org/10.5194/epsc2026-48, 2026.
ESA's EnVision mission will deliver some of the first new high-resolution radar maps of Venus since Magellan, with the VenSAR instrument operating in HH/HV dual-polarisation S-band at 30 m and 10 m resolutions [1]. Venus' surface is dominated by volcanic terrain [3], so understanding what the new missions may 'see' requires analysis of radar signatures at barren, volcanic terrains on Earth. The Askja volcanic system in Iceland is well-suited to isolating surface-roughness effects on radar backscatter [2]: basaltic composition, minimal topography and vegetation cover, and accessibility for ground-truth validation [6,7]. We address whether radar can be used to differentiate, provide age constraint, and characterise the emplacement and modification of volcanic surfaces, and whether these signatures are preserved at VenSAR specifications.
Seven lava flow age units erupted from the Askja volcano, ranging in age from the 1961 Vikrahraun to >7,000 BP, were characterised using fully polarimetric Synthetic Aperture Radar (SAR) data acquired using the DLR’s F-SAR system for NASA JPL and the VERITAS team in August 2023 [4,5]. These datasets include X-band (3.1 cm), S-band (9.2 cm), and L-band (22.6 cm) at 2 m spatial resolution. Flow units have been mapped using S-band HH radar imagery, stratigraphic relationships, and field data; absolute ages are from the ÍSOR digital geological database [9] and Sæmundsson et al. [10,11] (Figure 1).
Figure 1. Geological map of the Askja volcanic system showing the seven flow units examined in this study [9-11].
Across the Askja flow sequence, mean S-band HH γ0 decreases systematically with flow age. The 1961 Vikrahraun flow has a mean γ0 of -7.0 dB; the >7,000 BP Shield Lavas reach -14.0 dB (Figure 3). This backscatter decrease is driven by post-emplacement weathering, smoothing, and mantling (Figure 2). The 5th percentile of the per-pixel distribution drops 8.7 dB across the age sequence; the 95th percentile drops only 4.6 dB. Weathering therefore smooths the smoothest regions preferentially. Backscatter also decreases with increasing incidence angle (10-15 dB decrease from 10° to 80°), consistent with typical radar scattering behaviour from rough surfaces.
Figure 2. Three end-members of the Askja chronosequence (1961 Vikrahraun, 2900-4500 BP, and >6100 BP) shown as paired Sentinel-2 optical (left) and F-SAR S-band γ0 HH at 2 m (right).
Figure 3. S-band HH γ0 versus flow age at three resolutions: F-SAR 2 m (blue), VenSAR 10 m (orange), VenSAR 30 m (red). Power-law fits with 95% Monte Carlo confidence intervals; inset gives dynamic range and retention per cell.
Wavelength comparison reveals progressive increase in age-discrimination dynamic range with wavelength. X-band, available only at VV polarisation, shows the smallest dynamic range (5.64 dB). S-band HH gives 6.07 dB versus 9.59 dB at L-band HH (8.49 vs 11.60 dB at HV). Polarimetric analysis differentiates surface scattering mechanisms and flow morphologies. Smooth pāhoehoe and mantled surfaces produce high HH and HH/HV ratios, reflecting predominantly single-bounce surface scattering. Rough a'ā flows produce high HV backscatter and large volume-scattering decomposition components: the clinker layer of angular rubble clasts acts as a randomly oriented scattering volume, generating multiple-bounce returns that decompose as volume power.
Differentiation between pāhoehoe and a'ā facies within a single flow appears in the decomposition, not in the raw intensity. Following the facies-separability protocol of Tolometti et al. [12], dual-pol Mascolo-Cloude m·v [8] matches or slightly exceeds quad-pol Freeman-Durden P_v [13] in discriminating Event 2 a'ā from pāhoehoe within Vikrahraun 1961 (Figure 4). Polarimetric facies discrimination is most powerful on young, well-preserved flow surfaces.
Figure 4. Dual-pol decomposition [8] (R = ms, G = mv, B = ms/mv) of Vikrahraun 1961 at 2 m, 10 m, and 30 m. Coloured polygons mark a'ā and pāhoehoe facies, classified following Blasizzo et al. [14]. Per-flow facies separability following Tolometti et al. [12]: MC m·v: O = 0.84, H = 2.6×10⁴; FD P_v: O = 0.89, H = 2.0×10⁴.
To address whether these signatures will be mappable in images captured by VenSAR, the 2 m F-SAR S- and L-band covariance was degraded via a slant-range pipeline: incoherent multilook, Gaussian filtering to the target resolution, Gamma speckle at the specified looks (16 at 30 m, 8 at 10 m), and exponentially-distributed thermal noise at the -20 dB NESZ specification. S-band HH retains 79% of the age-discrimination dynamic range at VenSAR 30 m (1.30 dB loss out of 6.07 dB) and 86% at 10 m (0.87 dB loss); regression slope flattens by 16% and 13% respectively. The HV channel is NESZ-limited: only 49% retention at 30 m and 51% at 10 m, with cross-pol signal on flows older than c.5,000 BP sitting within a few dB of the -20 dB floor. The 10 m mode does not rescue HV because NESZ is per-pixel rather than ensemble-averaged. The same asymmetry holds at L-band (74% HH, 44% HV retention at 30 m), indicating the mechanism is wavelength-robust. Quad-pol and dual-pol products at 30 m agree to within ±0.015 dB on per-flow γ0 statistics; VenSAR's HH/HV mode therefore preserves both the age-discrimination signal and the within-flow facies differentiation accessible to fully polarimetric F-SAR.
Age-backscatter correlations provide a quantitative dating framework, while polarimetric analysis enables morphological and textural discrimination. For VenSAR specifically, HH at 30 m and 10 m is optimal for age discrimination across the 60–7,000-year range, while HV is optimal for morphology discrimination.
References: [1] EnVision Red Book, ESA-SCI-DIR-RP-003, 2023; [2] Adeli et al., 2023; [3] Brossier et al., 2020; [4] Horn et al., 2017; [5] Keller et al., 2024; [6] Mason et al., 2024; [7] Raguso et al., 2025; [8] Mascolo, Cloude & Lopez-Sanchez, 2021, IEEE TGRS; [9] ÍSOR, 2024, Digital Geological Database of Iceland; [10] Sæmundsson et al., 2012, Geol. Map N. Volcanic Zone (N. Part), 1:100,000, ÍSOR; [11] Sæmundsson et al., 2015, Geol. Map N. Volcanic Zone (S. Part), 1:100,000, ÍSOR; [12] Tolometti et al., 2022, JGR Planets 127(6); [13] Freeman & Durden, 1998, IEEE TGRS 36(3); [14] Blasizzo et al., 2022, Earth Planets Space 74:168.
How to cite: Davidova, N., Gallardo i Peres, G., Ghail, R., Moreira, A., Jaeger, M., Benedikter, A., and Mason, P.: Scattering Properties of Lava Flows: Insights from Askja, Iceland, in support of EnVision mission science development, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-918, https://doi.org/10.5194/epsc2026-918, 2026.
Introduction and motivation
The surface of Venus, our closest yet strikingly different planetary neighbor, has not been observed from orbit for 30+ years, since the Magellan mission, whose radar operated at 2.4 GHz (12.6 cm wavelength). This long observational gap will soon end thanks to the selection, in 2021, of two new radar missions : NASA’s VERITAS mission with VISAR (7.9 GHz, 3.8 cm) and ESA’s Envision mission with VenSAR/EuroSAR (3.2 GHz, 9.5 cm).
VenSAR/EuroSAR, contrary to VISAR, includes a passive radiometry mode designed to measure the microwave thermal emission from the surface of Venus. In its radiometry mode, as a baseline, it will operate in a nadir or near-nadir viewing geometry but opportunistic off-nadir horizontal and vertical (H&V) polarized measurements will be performed in specific regions of interest (RoIs).
Among these RoIs are several regions, primarily located at high elevations, that exhibit anomalously low emissivity in Magellan observations. These values have been interpreted as evidence for extremely high dielectric permittivity (up to ~80) [e.g., 1,2] linked to the presence of very unusual minerals (e.g., ferroelectric substances [e.g., 3,4]), due to the cold trapping of exotic volatile species, or yet unidentified weathering reactions. Alternatively, low emissivity may result from strong small-scale roughness or from a low-loss substrate of moderate permittivity where volume scattering dominates [1]. Off-nadir polarized radiometry from EnVision will help discriminate between these scenarios by constraining effective permittivity and separating volume scattering from roughness effects.
In this work, we analyze the limited polarized radiometry data from the Magellan mission to prepare for the scientific exploitation of the Envision VenSAR/EuroSAR polarimetric radiometry experiments. We focus on observations over Ovda and Beta Regios, two prominent examples yet completely different of highland regions characterized by anomalously low emissivity, with Ovda being tessera-dominated and Beta being volcano-dominated.
Magellan radiometry data and method
The Magellan radar mapped the surface of Venus at 12.6 cm over three cycles from September 1990 to September 1992. Data were acquired from a near-polar elliptical orbit, primarily in H-polarization, at incidence angles of 15°-45°, using a left-looking geometry during cycles 1 and 3 and a right-looking geometry during cycle 2. By mission end, ~98% of the surface had been mapped in both active and passive modes.
In its passive operating mode, the Magellan radar functioned as a microwave radiometer, recording the surface brightness temperature, which can be directly converted into emissivity. To first order, emissivity is controlled by the permittivity of the surface, itself primarily related to the bulk composition and density of the surface material. It can therefore be used to discriminate between different surface units.
Planetary surface materials typically exhibit permittivities between 3 and 10. On Venus, Magellan H-polarized emissivity data suggest that the lower end of this range corresponds to low-density rock powders [5], while the extensive plains show values of 4.0–4.5, consistent with moderately dense basaltic material. As previously mentioned, Magellan also identified several high-elevation regions with anomalously low emissivity, generally interpreted as evidence for unusually high permittivity.
Though the Magellan data were collected primarily in H-polarization, a small number of orbits were collected with V polarization. Co-located H and V data can be used to derive the Degree of Polarization (DoP), defined as
where and denote the horizontally and vertically polarized emissivities, respectively. The DoP is generally less sensitive to surface roughness than either individual emissivity component and can be used to provide an independent estimate of the permittivity through comparison with emissivity models (Fig. 1).
For this work, (i) we identified all available co-located H- and V-polarized radiometry observations, (ii) rasterized these data onto a common spatial grid with a resolution of 0.1° in latitude and longitude (about 10 km at the equator), (iii) constructed maps of the DoP (Fig. 2a), and (iv) estimated the surface permittivity for each pixel by inverting the White and Cogdell (1973) model [6] (Fig. 2b). This model relates the DoP to permittivity and large-scale surface roughness (expressed as rms slope) for rough planetary surfaces, more specifically Kirchhoff-like surfaces without small-scale roughness or volume scattering effects. The retrieved permittivity values can then be compared with the H-polarized emissivity measurements to quantify the extent to which the Venusian surface departs from an ideal Kirchhoff surface.
Results and future work
Fig. 1 shows that the measured DoP follows the expected trend with local incidence angle for permittivities of approximately 3-4, while also revealing regions of high permittivity. Fig. 2a displays the DoP map obtained from co-located polarized measurements acquired over Ovda Regio. Elevated DoP values are clearly associated with Ovda Regio, indicating higher local permittivity and confirming the expected correlation between low H-polarized emissivity and high DoP. Fig. 2b presents the retrieved permittivity values as a function of altitude in Ovda Regio. It confirms the presence of exceptionally high permittivity values in this region as well as the decrease of the permittivity at the highest elevations. Similar results will be shown and discussed for Beta Regio and compared to the backscatter values measured in the active mode of the radar.
Fig. 1: Measured DoP (black dots) as a function of the incidence angle compared to predictions from the White and Cogdell (1973) model for different values of permittivity ε and a rms slope of 15°.
Fig. 2: (a) Map of the DoP around Ovda Regio overlaid on the Magellan H-polarized emissivity mosaic. (b) Estimated permittivity as a function of the altitude in the Ovda Regio (for an assumed rms slope of 15°).
1. Arvidson et al., 1991, New Series 252, 270- 275
2. Pettengill et al, 1992 J. Geophys. Res. 97(E8):13067–13090
3. Shepard et al., 1994, Geophys. Res. Lett. 21-6, 469-472
4. Treiman et al., 2016, Icarus 280, 172-182
5. Campbell and Campbell, 1992, J. Geophys. , 97, 16293-16314
6. White and Cogdell, 1973, Moon 6, 235–249
How to cite: Le Gall, A., Menard, R., Lanoix, L., Ganesh, I., Byrne, P., Herrick, R., Margot, J.-L., and Jessup, K.: Polarized microwave radiometry observations of Ovda and Beta Regios : Insights into Venus’ surface composition and texture, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-799, https://doi.org/10.5194/epsc2026-799, 2026.
Venus is similar to Earth in size, mass, and bulk density. However, its thermal, tectonic, and atmospheric evolution has been very different. Its hot, dense CO₂-rich atmosphere, surface dominated by volcanic features [Hahn & Byrne, 2023], and potentially ongoing volcanic activity [Herrick and Hensley, 2023] make Venus a key target for understanding magmatic processes and their role in shaping the surfaces of terrestrial planets.
The composition of Venus’ surface is poorly known because in situ surface investigations are difficult to conduct in such a harsh surface environment, and orbital measurements of Venus’ surface can only be performed for narrow near-infrared spectral windows, as the opaque and thick atmosphere of Venus restricts direct surface observations. These atmospheric windows are central to upcoming Venus missions such as EnVision and VERITAS [Smrekar et al., 2022; Straume-Lindner et al., 2025], which aim to constrain surface composition, volcanic activity, and geodynamic evolution through orbital observations. Since surface emissivity measurements are sensitive to rock composition, including the FeO content of these rocks [Dyar et al. 2020; Helbert et al. 2021], they provide a potential link between observable surface materials and the interior processes that generated them. In turn, the FeO content influences mantle density, melting behaviour, and melt composition, and variations in bulk mantle FeO can affect the thermal evolution and magmatic history of Venus. Some of the only direct compositional constraints on Venus’ surface rocks come from the Venera and Vega landers [Surkov et al., 1984, 1986], which measured basaltic compositions at the surface.
Jennings et al. [2026] used Perple_X thermodynamic modelling to investigate Venus mantle compositions and proposed candidate compositions, including M80, capable of producing Venera- and Vega-like melts. Building on this work, we combine geodynamical modelling with GAIA and Perple_X-derived melting curves to investigate how variations in bulk mantle FeO content influence melting behaviour, melt production, and melt properties under Venus-like mantle conditions. These results are linked to high-temperature emissivity measurements of Venus analogue materials, with the broader goal of supporting the interpretation of future observations from EnVision and VERITAS.
We use the mantle convection code GAIA in a 2D spherical annulus geometry [Hüttig et al., 2013; Fleury et al., 2024] to model the long-term thermal and magmatic evolution of Venus’ mantle with the different bulk mantle FeO generated by Perple_X. The simulations include temperature- and pressure-dependent viscosity, thermal conductivity, and thermal expansivity, and account for internal radiogenic heating [Breuer et al., 2009; Moroz et al., 1980] and core cooling [Steinbach & Yuen, 1994].
The different FeO content between the simulations is reflected in the mantle solidus and liquidus temperature, whose parameterisation is based on Perple_X thermodynamic calculations. We use M80 composition from Jennings et al. [2026] as the reference composition and compare it with the FeO-variable suite M301–M306, generated by varying bulk FeO relative to M80 in steps of approximately ΔFeO ≈ 3 wt%. The Perple_X-derived solidus and liquidus curves were smoothed, segmented, and fitted with piecewise polynomial functions before being implemented in GAIA.
We compare two magmatic emplacement regimes: a fully extrusive case and a mixed case with 20% intrusive and 80% extrusive melt emplacement, with intrusions placed at 50 km depth. Simulation outputs are post-processed to analyse thermal evolution, melt production, cumulative melt volume, melt depth, melt temperature, and lithospheric thickness.
The simulations show that the effect of bulk mantle FeO content depends strongly on the magmatic emplacement regime. In fully extrusive cases, melt production rates, cumulative melt volumes, melt depths, and melt temperatures converge across FeO compositions, suggesting limited compositional sensitivity when melt is efficiently extracted to the surface. In contrast, the mixed intrusive–extrusive regime shows clearer FeO-dependent behaviour, with higher-FeO cases producing larger melt volumes and stronger variations in melt-related quantities.
The temperature and depth of melting also vary with composition. Low-, reference-, and high-FeO cases occupy different regions in melt temperature–melt depth space, indicating that FeO content affects the range of depths and temperatures at which melt is generated. In the mixed intrusive–extrusive regime, higher-FeO cases show a broader spread of melt-generation conditions, suggesting that FeO influences not only the amount of melt produced, but also where and under which thermal conditions melting occurs.
Laboratory emissivity measurements provide the observational link to the geodynamic results. We compare the model outputs with high-temperature emissivity spectra of two FeO-variable Venus analogue glasses synthesised at the University of Münster. These glasses represent partial melt compositions calculated with Perple_X from the M80 and M302 mantle compositions. The spectra were measured at Venus surface temperature in the Planetary Spectroscopy Laboratory and calibrated using hemispherical reflectance and blackbody measurements.
The two glasses show systematic emissivity differences within the near-infrared atmospheric windows targeted by VEM/VenSpec-M. Together, the geodynamic and laboratory results suggest that bulk mantle FeO content affects Venus’ melting history and may produce surface materials with distinguishable emissivity signatures relevant to future Venus missions. The combined approach presented here provides a framework for linking modelled mantle melting, melt properties, and surface spectral observations.
How to cite: Mohamed, Y., Herrera, C., Jennings, L., Alemanno, G., Plesa, A.-C., and Klemme, S.: On the role of bulk FeO content in Venus’ mantle thermal evolution, melt production, and surface emissivity, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-595, https://doi.org/10.5194/epsc2026-595, 2026.
INTRODUCTION
Venus’ magmatic history remains unconstrained since its geologically young surface causes major uncertainties in the planet’s mantle rheology, volatile content, and long-term cooling history. Recent evidence of ongoing volcanic activity on Venus (Herrick & Hensley, 2023) suggests magmatism still plays a key role, but reconstructing the past to understand why Venus and Earth evolved differently despite their similarities is a key challenge in planetary sciences. Global climate models suggest Venus could have had mild temperatures and liquid water until <1 Ga (Way et al., 2016, 2020), but other studies suggest that a hot surface, possibly hotter than today (Noack et al.,2012), persisted for most of its history (Figure 1). Surface temperature is linked to the magmatic and outgassing history, but the mantle volatile content is unclear. While some studies suggest that Venus’ interior may be intrinsically dry (Constantinou et al., 2024), others propose that volatiles could persist in the lower mantle (Smrekar & Sotin, 2012), affecting mantle dynamics.
Venus’s geodynamic regime and surface tectonics are poorly constrained. Several scenarios including catastrophic resurfacing, episodic plate tectonics, and stagnant lid regime were proposed. Early geodynamic models considering magmatism mostly assumed eruption-dominated (extrusive) magmatism known as the heat-pipe regime (Moore & Webb, 2013), but more recent studies explored intrusion-dominated (intrusive) magmatism known as the plutonic-squishy regime (Lourenco et al., 2020).
A global perspective of the intrusive-to-extrusive ratio is still unclear. The >85,000 volcanoes (Hans & Byrne, 2023) reflect Venus’ volcanic nature, however, ~740 coronae (Gülcher et al., 2025), features related to plume-mantle interactions, and interpretations from gravity-topography data (Maia et al., 2023) reveal that intrusions also take place. Geodynamic models constrained from observational data point to a highly intrusive magmatism (Herrera et al., 2024; Maia et al., 2025); however, how this could have differed in the past if the planet had different surface and lithospheric conditions is poorly understood. Therefore, we analyze the effect of the end-member magmatic styles (i.e. ‘fully intrusive’ vs. ‘fully extrusive’ magmatism).
We explore the relative roles of these magmatic styles for the planetary evolution under varying surface temperatures and mantle viscosities, aiming to understand how surface and mantle conditions influence the melt production rate and the pressure and temperature conditions at which melts are first generated on Venus.
METHODS
We use the geodynamic code GAIA in 2D spherical annulus geometry (Hüttig et al.,2013; Fleury et al.,2024). We assume a temperature- and depth-dependent viscosity (Hirth & Kohlstedt,2003), pressure- and temperature-dependent thermal conductivity and expansivity (Tosi et al.,2013), radiogenic heat decay (Moroz et al., 1980), core cooling (Steinbach & Yuen, 1994), and melting curves from thermodynamic models (Stixrude et al.,2009; Jennings et al., 2025). Figure 1 illustrates our melting modeling. Melt extraction occurs instantaneously (Condomines et al., 1988). Extrusive melts instantaneously cool to surface temperature while intrusive melts, placed at 30 km depth, cool adiabatically. Magmatic intrusions also evolve according to the rheological critical melt fraction (Arzi, 1978) depending if they are in a solid- or melt-dominated regime, which respectively reduce the viscosity as a function of the melt fraction or increases the thermal conductivity to capture the effect of small-scale convection in the melt.
RESULTS
Our results highlight surface-mantle feedbacks as a key control on magmatic and cooling history, which may be reflected in the surface composition as well as shape the inner mantle structure: hot surfaces favor a more efficient mantle cooling if intrusive magmatism dominates, and vice versa; while the mantle viscosity modulates this effect (Figure 2). Intrusive magmatism efficiently cools the mantle when an efficient lithospheric recycling occurs, and such process influences crustal and lithospheric conditions, affects volatile redistribution in the mantle, and boosts melt production that, consequently, increases outgassing and impacts atmospheric composition.
Constraining the surface temperature evolution depends on interior-surface-atmosphere feedback that remains to be studied. As a first-order approximation that allows us to analyze the effects of a surface temperature variation on the magmatism, we impose an abrupt temperature increase until today’s surface temperature (737 K) to mimic a catastrophic event that ended a phase with milder conditions. Similarly, we model the other end-member scenario in which an initially hotter surface temperature decreases until the modern-day temperature is reached. We analyze the implications of such changes in temperature in terms of the melt generation on Venus, and how this affects mantle and lithospheric properties for both magmatic styles.
For all our cases, we compare the depth and temperature of the melt sources with thermodynamical models that explain the surface composition measured by Venera 14 and Vega 2 (Jennings et al., 2026) to study the link between our melt sources and present-day surface compositions, potentially helping to constrain the magmatic evolution on Venus.
SUMMARY
Surface temperature and mantle viscosity are key factors in determining the efficiency of planetary cooling for different magmatic styles (intrusive or extrusive), as well as have a direct influence on when, where, and how much melt is produced in the mantle. Changes in the region (pressure and temperature) of the melt sources through time could be linked to the evolution of melt composition, that could be connected to present-day observations of surface composition. Our findings could provide insights on the differences in the cooling pathways of early Earth vs. Venus, and give perspectives for potential habitability of exo-Venuses.
How to cite: Herrera, C., Plesa, A.-C., Jennings, L. A., Maia, J., Breuer, D., and Klemme, S.: Evolution of melt production and melting region on Venus influenced by surface-mantle feedbacks, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-1108, https://doi.org/10.5194/epsc2026-1108, 2026.
Venus hosts hundreds of enigmatic circular tectono-magmatic features known as coronae, whose origins, activity state, and role in planetary heat loss remain among the most persistent open questions in Earth and planetary sciences. Coronae display extraordinary diversity in size, morphology, topography, gravity signatures, and tectonic setting, indicating that they do not represent a single formation mechanism, but instead reflect a spectrum of dynamic processes. Understanding these structures is critical for deciphering Venus’ geodynamic evolution and present-day state. In particular, several coronae are among the prime candidates for ongoing tectonic and volcanic activity on Venus and therefore represent key targets for detecting active deformation, magmatism, and surface change with forthcoming missions such as ESA’s EnVision and NASA’s VERITAS.
Here, we first present results from a newly compiled global corona database [1] that systematically reassesses Venusian coronae using Magellan radar and topography datasets. The updated database contains 740 coronae (Figure 1), substantially more than previously catalogued, and defines coronae purely based on the original morphological definition using three identification criteria: (1) the presence of a partial or complete annulus of closely spaced concentric fractures, (2) with or without associated quasi-circular topographic relief, and (3) a minimum diameter of 60 km. Importantly, the term “corona” is descriptive rather than genetic and does not imply a specific formation mechanism. The expanded database reveals that coronae span a broad continuum of morphologies, geological settings, and can overlap with other surface feature nomenclature, such as volcanoes, paterae, novae, and arachnoids. The database further identifies numerous previously unrecognized corona-like structures, including ambiguous features embedded within tessera terrain. These observations demonstrate that coronae cannot always be treated as a uniform class of features and highlight that studies invoking specific formation scenarios may in practice investigate only subsets of the global corona population rather than the full morphological spectrum observed on Venus.
Figure 1. Global distribution centered at 130 degrees East of Venusian coronae according to our new database [1]. All 740 coronae are plotted as circles using their central coordinates and average radii. Type 1 coronae are shown in white and Type 2 in red. (b) Bar graph showing the number of Type 1 and Type 2 coronae. (c) Diameter-count distribution shown as a stacked histogram for Type 1 (gray) and Type 2 (red) coronae, together with a normalized lognormal fit (solid black line).
With the assumption that the largest coronae on Venus are formed by different types of plume-lithosphere interactions, we investigate their topography and gravity signatures in comparison with geodynamic models. We use recent three-dimensional thermo-chemical geodynamic models of plume-lithosphere interaction on Venus [2] that define four geodynamic end-member scenarios for plume-induced corona formation: (1) lithospheric dripping, (2) short-lived subduction, (3) embedded plume, and (4) underplated plume, reflecting different relationships between plume buoyancy and lithospheric strength. To enable direct comparison with observations, the modeled gravity signatures are rescaled to the spatial resolution of the Magellan gravity field, which has a typical spherical harmonic degree strength of ~75–90, corresponding to spatial resolutions of ~210–315 km. This relatively coarse gravity resolution severely limits detailed comparisons between observed and modeled corona gravity signatures, particularly for smaller-scale anomalies and narrow features. For example, only 75 out of all 740 coronae on Venus are considered “broadly resolved” in the Magellan gravity data. Nevertheless, by comparing predicted and observed free-air gravity anomalies together with topography, we identify distinct classes of coronae consistent with different styles and evolutionary stages of plume-lithosphere interaction, including scenarios in which crust is recycled back into the mantle through lithospheric delamination or subduction-like processes [3]. Of the 75 resolved coronae, 52 best match a mantle-lithosphere interaction scenario involving underlying buoyant mantle material and potentially ongoing tectono-magmatic activity.
Figure 2. Global map centered at 130 degrees East showing the geoid and the 75 coronae considered resolved in the Magellan gravity data, coloured according to their topographic and gravity signatures [3]. Circle fill and outline indicate the associated free-air gravity anomaly type, while colors represent topographic classification. Coronae with positive free-air gravity anomalies are interpreted as active sites of ongoing plume–lithosphere interaction. Of these, coronae with topographic trenches (blue, red) match modeled crustal or lithospheric recycling at plume margins, whereas those with raised rims and elevated interiors (purple) best match modeled embedded or underplated plumes [3].
Importantly, our analysis further reveals that the limited spatial resolution of the Magellan gravity field could obscure or suppress positive gravity anomalies beneath some coronae, particularly where deep annular troughs surround an uplifted interior. This suggests that a subset of potentially active coronae could be effectively “hidden” in current geophysical datasets [3]. These coronae therefore represent key observables for forthcoming missions such as ESA’s EnVision and NASA’s VERITAS. Moreover, the improved gravity resolution of these missions is expected to resolve more coronae and substantially enhance our ability to distinguish between different tectonic and magmatic regimes on Venus.
References:
[1] Gülcher, A. J. P., Sabbeth, L., E. Stofan, and Smrekar, S. E. (2025), Coronae on Venus: an updated global database and insights into morphological, geologic, and lithospheric properties. Journal of Geophysical Research: Planets, vol. 130 (5), e2024JE008749. https://doi.org/10.1029/2024JE008749
[2] Gülcher, A. J. P., Gerya, T.V., Montési, L.G.J. and Munch, J. (2020) Corona structures driven by plume- lithosphere interactions and evidence for ongoing plume activity on Venus. Nature Geoscience, vol. 13, pp. 547-554, 10.1038/s41561-020-0606-1
[3] Cascioli, G., Gülcher, A. J. P., Marzarico, E., and Smrekar, S. E., (2025), A spectrum of tectonic processes at coronae on Venus revealed by gravity and topography. Science Advances, vol. 11 (20), eadt5932, https://doi.org/10.1126/sciadv.adt5932
Acknowledgements: This research was partially conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract (80NM0018D0004) with the National Aeronautics and Space Administration.
How to cite: Gülcher, A., Cascioli, G., and Smrekar, S.: Venus' coronae enigma: Insights and limitations from geodynamic models, topography, and gravity, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-837, https://doi.org/10.5194/epsc2026-837, 2026.
Introduction
The Cosmic Vision M5 mission EnVision from ESA will launch by the end of 2031 to study Venus for a nominal duration of 4 years. Its payload includes the VenSpec spectrometry suite, comprising three complementary spectrometers developed by BIRA-IASB, DLR, and LATMOS to study the atmosphere and surface of Venus from the UV to the infrared range. The scientific objectives of the suite are to characterize the diversity of the surface mineralogy as well as to assess the spatial distribution of gaseous species of interest (H2O, HDO, CO, SO2, SO) in order to better understand the interplay between chemistry, dynamics and surface interactions within the atmosphere of Venus [1, 2, 3, 4].
Role of the Working Group
Need for solar spectral irradiance at Venus
Given the radiative properties of the planet, the foremost signal coming from Venus in the wavelength bands used by the spectrometers on the day side is the reflected Solar Spectral Irradiance (SSI). In order to extract the planetary signal, an accurate SSI from the ultraviolet to the infrared needs to be known at the spectral resolution of the instrument channels, and at the date and position of Venus with respect to the Sun. Such an information is difficult to obtain from Earth-based or L1 observatories.
Based on this constraint and on the fact that the spectrometers’ optics will age over time, regular observations of the solar disk will be performed about every three months by the VenSpec suite to calibrate the instrument. These regular observations can also be of interest to complement Earth’s solar irradiance monitoring and global solar irradiance models.
Activities of the Working Group
The activities of the Working Group have been dedicated to the following topics of investigation:
1. to review the Solar Spectral Irradiance (SSI) data available, its consistency over time (some discrepancies are noted between different observatories and will be assessed) and its variability. Over a solar cycle, the SSI variability is lower than 0.1% in the infrared but increases at shorter wavelengths and is about 5% at 200 nm in the UV [5].
2. to work on defining the SSI indices that could be the most useful to generate the Venus-based SSI required by VenSpec especially in the UV where the variability is more important. Typical indices of interest are, for example, the MgII 280 nm doublet [6], the CaII-K bands at 393 nm and the H-1 Lyman-α line at 121.6 nm [5].
3. to review all the observatories that have generated relevant SSI indices over time, and which ones would be active during the planned nominal phase of the mission (2034-38) to be used as validation for the VenSpec generated index suites during Venus conjunction periods (e.g. the US Earth observation mission GOES-U, GOES-R; the Indian solar mission Aditya-L1).
Figure 1: Inventory of SSI monitoring missions through time with potential missions active during the EnVision mission (adapted from [8]).
4. to assess tools that have been developed to predict SSI for positions other than Earth’s in the Solar System like the Flare Irradiance Spectral Model (FISM) developed at LASP [7] and how they could be used during the mission.
5. to work on data taken at Venus by previous missions, such as Venus Express, to assess the validity of the methodology developed to obtain relevant SSI constraints at Venus’ position during the science phase of EnVision.
Conclusion & Perspectives
The Solar observations Working Group of the VenSpec spectrometry suite for the EnVision mission has started to develop a methodology to derive relevant SSI information at Venus for spectral calibration and data analysis. Preliminary assessments and applications of the methodology will be presented at the conference.
References
[1] Helbert, Jörn, et al. Infrared remote sensing and instrumentation XXVII. Vol. 11128. SPIE, 2019.
[2] Marcq, E., et al. Advances in Space Research 68.1 (2021): 275-291.
[3] Lustrement, B., et al. In Infrared Remote Sensing and Instrumentation XXXII, vol. 13144, pp. 164-196. SPIE, 2024.
[4] Robert, S., et al. Journal of applied remote sensing 19.1 (2025): 014525. doi: 10.1117/1.jrs.19.014525
[5] Woods, T. N., and M. T. DeLand. Earth and Space Science 8.8 (2021): e2021EA001740.
[6] Heath, D. F., and B. M. Schlesinger. Journal of Geophysical Research: Atmospheres 91.D8 (1986): 8672-8682.
[7] Chamberlin, P. C., et al. Space Weather 18.12 (2020): e2020SW002588.
[8] Woods, T. N., et al. Solar physics 293.5 (2018): 76.
How to cite: Lasue, J., Bolsee, D., Alemanno, G., Lopez Ariste, A., Baggio, L., Bertran, S., Chide, B., Conan, L., Juin, A., Leduc, B., Lustrement, B., Marcq, E., Pereira, N., Pinet, P., Reville, V., Robert, S., Rouanet, N., Rouillard, A., Stcherbinine, A., and Thomas, I. and the VenSpec Solar Observations Working Group: Activities of the VenSpec Solar Observations Working Group in preparation for the EnVision mission, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-534, https://doi.org/10.5194/epsc2026-534, 2026.
Sulphur dioxide (SO2) is arguably the most variable trace at Venus’ cloud top, with observable column density variations spanning about 2-3 orders of magnitude over spatial extents ranging from a few hundred of kilometers to planetary scale, and over time scales ranging from about an Earth day to several decades [2, 3, 1-6]. The most recent extensive datasets on the day side have been acquired by the UV spectrometer SPICAV-UV on board ESA’s Venus Express (2006-2014) operating in nadir mode, and by the UV imager UVI on board JAXA’s Akatsuki (2015-2025), both using SO2 UV absorption featured in the solar light reflected by the cloud top.
Both instruments agree about the latitudinal distribution of SO2, enhanced at lower latitudes compared to higher latitudes due to the interplay between the vertical-meridional general circulation and photochemical destruction. There is however a discrepancy between the two datasets regarding the SO2 distribution with respect to local solar time. Whereas SPICAV-UV [3] found a minimum near the subsolar point at noon, UVI [5] evidenced a morning/evening asymmetry with an afternoon maximum, consistent with the effect of solar tides and with recent 3D photochemical-dynamical coupled numerical models [4].
Recent advances in radiative transfer numerical calculations, especially involving 3D Monte-Carlo solvers such as htrdr-planets [7], now allow for simulating accurately the solar light scattered even for large solar zenith angle values such as near the morning and evening terminators (Fig. 1). This part of the SPICAV-UV dataset could not be processed before using pseudo-spherical radiative transfer solvers like DISORT, and thus the corresponding reflectance spectra were dismissed from previous analyses. Using an updated Venus atmospheric model and a corrective approach involving both DISORT and htrdr-planets (combining DISORT’s computation speed and htrdr-planets’ accuracy), we will present our reanalysis of the whole SPICAV-UV data set, including regions near the terminator. We will then examine if the trends seen in climatological variables such as SO2, O3, cloud top altitude, or the UV absorber with respect to latitude, longitude and local solar time are consistent with previous findings.
Figure 1: Comparison of synthetic radiance factors for the nominal case using two different solvers, DISORT (pseudo-spherical, red) and htrdr-planets (Monte Carlo 3D, black). Both solvers agree at low solar zenith angle (SZA) values, but DISORT underestimates significantly Venus’ brightness for a grazing Sun near the terminator.
This work has been funded by the French National Research Agency (ANR), project RaD3-net, grant number ANR-21-CE49-0020.
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Bibliography
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[1] Encrenaz et al., A & A (2012)
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[2] Marcq et al., Nature Geosci. (2013)
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[3] Marcq et al., Icarus (2020)
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[4] Stolzenbach et al., Icarus (2023)
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[5] Iwanaka et al., JGR Planets (2025)
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[6] Encrenaz et al., A & A (2025)
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[7] He et al., JQSRT (2026)
How to cite: Salugová, E., Marcq, E., He, Z., Vinatier, S., and Bertaux, J.-L.: Cloud top sulphur dioxide measurements from the morning to the evening terminator on Venus, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-549, https://doi.org/10.5194/epsc2026-549, 2026.
Sulphur dioxide (SO2) is arguably the most variable trace gas at Venus’ cloud top, with observable column density variations spanning about 2-3 orders of magnitude over spatial extents ranging from a few hundred of kilometers to planetary scale, and over time scales ranging from about an Earth day to several decades [1, 3-7, 4, 5]. Orbital investigations from ESA’s Venus Express (2006-2014), and JAXA’s Akatsuki (2015-2025) have provided long term measurements series of cloud top SO2, but suffer from instrumental limitations in terms of size, weight, power, and spectral resolution when compared to ground instrumentation.
As a complement of the orbital monitoring with inevitable gaps in time between active space missions, as well as considering the known variability of SO2, Encrenaz et al. [3-7] have been running a monitoring campaign using the high-resolution (R ~ 105) mid IR spectrometer TEXES [2], a guest instrument hosted at the IRTF telescope in Hawaii. During most Venusian quadrature events from 2012 up to the present day, they have recorded hyperspectral cubes of Venus near 7.4 µm, 8.6 µm and 19 µm, probing altitudes ranging from 57 to 67 km, within the upper clouds of Venus. Using simple weak line ratios of SO2/CO2 on one hand, and HDO/CO2 on the other hand, they confirmed the striking variability of SO2 over short timescales (a few terrestrial hours) and spatial extents of about 1000 km (so called “SO2 plumes”), in comparison with the spatially uniform HDO maps used here as a proxy for H2O. Long-term variations of HDO were nevertheless evidenced, exhibiting complex correlations with SO2 [5].
We have now undertaken the reprocessing of the whole TEXES data set, along two main directions of improvement. First, we shall map the spectral cubes onto a suitable and consistent coordinate system (latitude, longitude, local solar time) to assess SO2 variability more accurately than using only the existing full disk images. Then, we shall develop a radiative transfer model that should allow for more accurate retrievals of minor species, possibly allowing for limited temperature and SO2 vertical profiling within the upper cloud. We shall present here our preliminary results, and plan to use this pipeline for future TEXES observations that the team will lead.
Figure 1: Synthetic spectrum with 5 ppm of H2O at 65 km and variable amounts of SO2. Besides SO2 spectral lines, a CO2 line can be seen near 1345.25 cm-1, as well as a HDO line near 1344.9 cm-1
Bibliography
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[1] Esposito et al., Science (1984)
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[2] Lacy et al., PASP(2002)
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[3] Encrenaz et al., A & A (2012)
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[4] Marcq et al., Nature Geosci. (2013)
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[5] Marcq et al., Icarus (2020)
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[6] Encrenaz et al., A & A (2023)
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[7] Encrenaz et al., A & A (2025)
How to cite: Marcq, E., Verbaenen, E., Greathouse, T., Roos-Serote, M., Aoki, S., Bézard, B., and Encrenaz, T.: Monitoring of sulphur dioxide observed in the upper clouds of Venus by TEXES/IRTF in the thermal IR, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-560, https://doi.org/10.5194/epsc2026-560, 2026.
We will present summarised findings from our JCMT-Venus project, a long-term disc-integrated monitoring programme using the 15-metre James Clerk Maxwell Telescope (JCMT), a single-dish telescope operating at millimetre and submillimetre wavelengths, to probe the upper mesosphere of Venus at altitudes of approximately 90–110 km. The region probed marks the dynamical transition between superrotation and subsolar-to-antisolar flow, and is also a photochemically active layer central to Venus’ chemical cycles. The variability of key chemical species in this region has been relatively poorly characterised. Existing observations used to probe this region have important limitations: occultation measurements are often restricted to specific Local Solar Time (LST) or latitude ranges, while millimetre and submillimetre observations generally have sparse temporal sampling [1,2].
With the main aim of following up our detection of phosphine (PH3), whose presence implies chemical disequilibrium and is therefore of potential biological interest [3], the project has since expanded into a broader investigation of Venus’ upper mesosphere. The wide spectral bandwidth of the observations provides simultaneous coverage of several important species, including H2O (via HDO), SO2, SO, H2SO4, OCS, and HCO+. To date, four multi-week observing campaigns have been completed, with a fifth approved for July 2026. These campaigns sample complementary LST ranges, covering dayside and nightside and different stages of the solar cycle for comparison. Together, they provide invaluable insights into the simultaneous variability of species that are important for understanding the chemistry and the dynamics of this region. The talk will include three main parts, 1) a study of the daily variability of H2O and SO2, 2) daily constraints on SO, H2SO4, and OCS, and 3) the re-detection of PH3.
The first part of the talk will discuss the variability of H2O and SO2, which are key species in Venus’ photochemical cycles leading to the formation of the global sulphuric acid cloud and haze layers. Their variability in the upper mesosphere is poorly understood, mostly because at least two of the short-term, LST-dependent, spatial, and potential long-term effects were entangled in individual studies. Combining independent observations is also challenging, since even observations made over similar periods can produce very different results, possibly because of differences in instrumentation and data reduction [1,4]. We apply a consistent reduction method to all campaigns, with particular attention to standing-wave removal, a common issue in Venus mm/submm spectroscopy. We have four main findings. First, SO2 exhibits long-term variability (Fig. 1) and appears to follow the long-term cycle observed near the cloud-top altitude [5], further constraining any upper-mesospheric SO2 reservoir to be linked to the supply of SO2-related species from below. Second, H2O also exhibits long-term variability in the form of an anti-correlated response to the long-term change in SO2, likely because higher SO2 abundance consumes more H2O through H2SO4 formation (Fig. 1). Third, in the absence of long-term effects, SO2 shows a clear LST-dependent trend that can be reproduced using an independent model (Fig. 2) [6]. Finally, H2O variability is broadly consistent with the noise level over each campaign, although individual excursions are present in the form of sudden depletion events.
The second part will report results for other major sulphur-bearing species, including SO, OCS, and H2SO4. These species are investigated in temporal parallel with the daily variations of H2O and SO2, providing benchmark data for photochemical models and constraining existing models of the SO2 inversion profile [7,8]. The third part will discuss the new PH3 detection and its robustness.
Figure 1: Disc-integrated SO2 and H2O abundances as a function of sampled LST for the first three campaigns in February 2022, July 2023, and August-September 2023. SO2 is broadly absent in Campaign 1 but detected in Campaigns 2 and 3, indicating long-term variability. H2O is largely stable between Campaigns 2 and 3, but is higher in Campaign 1, likewise indicating a long-term effect.
Figure 2: Daily SO2 abundances as a function of LST in Campaigns 2 and 3, compared with independent LST model predictions for different Kzz values and dynamical-component weightings [6]. The best agreement is obtained for a mixed dynamical case with 75% superrotation and a 25% subsolar-to-antisolar contribution, suggesting that, in the absence of long-term effects, SO2 variability in Venus’ upper mesosphere is primarily LST-dependent.
References:
[1] Sandor B. J. & Clancy R. T., 2005, Icarus, 177, 129.
[2] Chamberlain S. et al., 2020, Icarus, 346, 113819.
[3] Greaves J. S. et al., 2021, Nature Astronomy, 5, 655.
[4] Gurwell M. A., Melnick G. J., Tolls V., Bergin E. A. & Patten B. M., 2007, Icarus, 188, 288.
[5] Encrenaz T. et al., 2025, A&A, 703, A219.
[6] Shao W. D., Zhang X., Mendonça J. & Encrenaz T., 2022, The Planetary Science Journal, 3, 3.
[7] Zhang X. et al., 2010, Nature Geoscience, 3, 834.
[8] Zhang X. et al., 2012, Icarus, 217, 714.
How to cite: Tang, W., Clements, D., Greaves, J., Richards, A. M. S., and Peel, M.: JCMT-Venus: Long-term Monitoring of Chemical Variability in Venus' Upper Mesosphere, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-1119, https://doi.org/10.5194/epsc2026-1119, 2026.
Introduction: Within the Venusian volcanic plains, long meandering channels have been identified and classified as so-called ‘canali’ (e.g. [1]). Canali are channels of great length that are thought to have been formed by melts and/or fluids on the Venusian surface. Canali may have formed through a combination of mechanical and thermal erosion or collapse of subsurface lava flows [2]. The morphological properties of canali show a great degree of similarity to terrestrial rivers [3], suggesting that the fluid that formed them must have been a low-viscosity fluid, likely similar in viscosity to water. Additionally, the extreme length and constant width of the longest canali imply that the responsible fluid was stable over a vast distance and thus a large amount of time. Water cannot have been responsible for the formation of canali, as liquid water is unstable due to the high surface temperatures. Instead, a magma or fluid-rich melt is more likely to have carved the canali. However, ordinary basaltic magmas are too viscous to form the observed channel geometries [4], and would also cool too quickly and could, therefore, not produce the observed length of the channels. Several other candidates have been proposed based on stable mineral phases on the Venusian surface. This study aims to constrain the melting behaviour of carbonate melts relevant to the Venusian crust while assessing their potential as a source for the formation of canali on Venus.
Methods: We performed high-pressure and -temperature experiments in a Bristol-type end-loaded piston cylinder press. Experiments were conducted at the Institute for Mineralogy, Münster University, and the Department of Earth Sciences, VU, Amsterdam. Three compositions were studied. All compositions consisted of 75 wt% Ocean Island Basalt (OIB), a basaltic equivalent to the Venusian upper crust, while the remaining 25% consisted of either Na2CO3, CaCO3, or a mixture of 50 wt% Na2CO3 and 50% CaCO3. The OIB was created by mechanically mixing reagent grade powders of SiO2, Al2O3, Na2CO3, MgO, CaCO3, TiO2, Fe2O3, K2CO3 and MnO under ethanol, after which the material was decarbonated and molten into a glass. The glass was ground into a fine powder, after which the corresponding carbonate was added to obtain the final three compositions. Starting compositions were directly loaded in 2.0 mm outer diameter, 1.7 mm inner diameter Pt capsules. Three loaded capsules, each containing one of the three starting compositions, were placed in boron-nitride (BN) three-holed spacers. The capsule-containing BN spacers were loaded into regular ½ inch talc-pyrex assemblies. A ruby disc was placed on top of the BN spacer, followed by an MgO sleeve containing a 1.6 mm outer diameter and a 4-bore alumina thermocouple sleeve containing thermocouple wires. At the top of the assembly, a hardened steel plug and pyrophyllite ring were placed. Temperatures were measured using W95Re5 – W74Re26 (type C) thermocouple wires placed at the assembly hotspot. A total of 15 experiments were performed, all lasting 2 hours, while temperature and pressure were varied (T = 1050, 1100, 1200, 1300, 1400 °C; P = 0.5, 0.85, 1.7 GPa). Capsules were subsequently polished to expose the interior. Phases were identified and major element concentrations were measured using EPMA at Münster University and the Netherlands Geological Facility at Utrecht University.
Results: Various phases were identified. The OIB+Ca experiments did not produce carbonate melt under any of the experimental conditions, CaCO3 broke down to CaO and CO2 before the liquidus of the system was reached (Fig 1). Both the OIB+Na and the OIB+mix experiments produced carbonate melt at 1100 °C at various pressures (Fig 2). Details will be presented at the conference. Our results are used to create OIB + carbonate stability fields (Fig. 3).
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Figure 1. CaCO3 has decomposed fully, resulting in an ultra-calcic silicate melt coexisting with a supercritical CO2 phase at 0.85 GPa, 1300 °C. |
Discussion: Pure CaCO3 does not produce carbonate melts under the explored experimental conditions. In contrast, pure Na2CO3 or a mixture of the two will produce carbonate melt at some of the experimental conditions. Depending on the oxygen fugacity and composition of carbonates in the Venusian crust, this may have various implications. Carbonates in the Venusian crust may have various origins. Carbonates have been suggested to result from evaporated oceans [5], liquid immiscibility of carbonated silicate melt [2], or buried reaction products as a result of chemical weathering [6]. Basic studies have been performed on the chemical composition of chemically weathered Venusian minerals and/or rocks (e.g. [7]), but more a qualitative approach is needed to fully understand weathering rates and processes. Depending on the geotherm, these potential carbonates might remain solid, melt to from carbonate melts or dissociate to produce CO2. If carbonate melt is stable, a mechanism to concentrate and erupt the melt would be required to act as a canali-forming source. Experimentally studying the rheological properties of carbonates will lead to a better understanding of the potential carbonatites hold as a canali-forming source. Additionally, this study has implications for the solubility of CO2 in silicate melt. Experiments show that the solubility increases with increasing pressure. Given the abundance of CO2 in the Venusian atmosphere, carbonatites and/or carbonated magmas have played a major role in the outgassing of CO2 and, thus, the evolution of Venus.
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Figure 2. Stable carbonate melt coexisting with silicate melt at 1.7 GPa, 1100 °C. |
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Figure 3. Schematic estimated stability field of 75% OIB + 25% CaCO3. |
Acknowledgements: This study was supported by the ERC StG VenusVolAtmos and NWO M-Invest Canali awarded to ESS.
References: [1] Komatsu et al. (1992), GRL. [2] Trussell et al. (2025), Science Advances. [3] Bray et al. (2007), JoGR.[4] Treiman (2009), 40th LPSC 2009. [5] Zolotov (2018), RiMaG. [6] Kargel et al. (1994), Icarus. [7] Santos et al. (2023), JGR Planets.
How to cite: Aerts, G., Jorritsma, J., Berndt, J., Klemme, S., van Westrenen, W., and Steenstra, E.: An experimental perspective on the feasability of the formation of Venusian canali via carbonatitic melts, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-912, https://doi.org/10.5194/epsc2026-912, 2026.
Introduction
The three space missions by ESA and NASA (Veritas, DAVINCI and EnVision) underscore the growing scientific interest to understand our closest neighbour, Venus. It has a young (McKinnon et al., 1997) but poorly constrained (~350-1 Ga) and seemingly uniform surface age determined by the random distribution of ~950 impact craters (Herrick & Phillips, 1994) (Fig 1). The apparent random distribution of impact craters on the surface suggests an equilibrium resurfacing model of the crust (Phillips et al., 1992). Previous studies (e.g., Ivanov & Head, 2011) have determined relative ages of geological units based on superposition principles. The spatial distribution of craters and the geological units defined by Ivanov & Head (2011) have not been combined previously.
This study aims at investigating the spatial distribution, timing and statistical significance of impact craters and the stratigraphy mapped by Ivanov & Head (2011). Based on the database by Herrick & Phillips (1994), we added parameters, where each impact crater was characterised based on the time of formation, target unit, and an improved degradation classification.
We are testing different statistical methods, such as Kolmogorov–Smirnov (KS) test, to find correlation between the classification parameters and the geological units.
Fig 1. Geological map of Venus in Robinson projection based on Ivanov & Head (2011) with the spatial distribution of impact craters and their diameters. Colour bar shows the variation in diameter in log scale.
Results
The improved weathering index was obtained by:
Wi = (central structure diameter) / (total diameter) * (degradation state) / (rim completeness)
Where the degradation state assumes values 1 for pristine craters with ejecta, 2 for craters with partially preserved ejecta and 3 for heavily degraded craters without ejecta blanket (Herrick & Phillips, 1994).
The spatial distribution of the weathering index was then plotted on the topography (Fig 2a). The degradation state that was previously mapped by Herrick & Phillips (1994) shows a strong correlation with altitude (Fig 2b).
Fig 2. Spatial distribution of the degree of weathering with topography by us (a) and by Herrick & Phillips (1994) (b). c. crater density on different stratigraphical units
The p-value in the KS clustering analysis shows a range from 0.0168 to 0.6707 between the crater size frequency distribution in the different stratigraphic units.
References
Herrick, R. R., & Phillips, R. J. (1994). Implications of a Global Survey of Venusian Impact Craters. Icarus, 111(2), 387–416. https://doi.org/10.1006/ICAR.1994.1152
Ivanov, M. A., & Head, J. W. (2011). Global geological map of Venus. Planetary and Space Science, 59(13), 1559–1600. https://doi.org/10.1016/J.PSS.2011.07.008
McKinnon, W. B., Zahnle, K. J., Ivanov, B. A., & Melosh, H. J. (1997). Cratering on Venus: Models and Observations. Veii, 969. https://ui.adsabs.harvard.edu/abs/1997veii.conf..969M/abstract
Phillips, R. J., Raubertas, R. F., Arvidson, R. E., Sarkar, I. C., Herrick, R. R., Izenberg, N., & Grimm, R. E. (1992). Impact craters and Venus resurfacing history. Journal of Geophysical Research, 97(E10), 15923–15948. https://doi.org/10.1029/92JE01696;JOURNAL:JOURNAL:21562202E;WGROUP:STRING:PUBLICATION
How to cite: Das, R., Kenkmann, T., Karagoz, O., and Hergarten, S.: The impact cratering inventory on Venus: time resolved size-frequency distributions, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-1174, https://doi.org/10.5194/epsc2026-1174, 2026.
In preparation for the Envision mission to Venus, multi-frequency airborne Synthetic Aperture Radar (SAR) data collected in August 2023 over Iceland, by the DLR for NASA JPL and the VERITAS mission team (using the F-SAR system) [2-5], has been analysed across a series of basaltic lava flows of differing ages. Fieldwork in July-August 2026 in the Reykjanes Peninsula has provided some vital ground-truth (surface roughness and very high-resolution topography) for our analysis. Our investigations are aimed at better understanding the scales and scattering characteristics of young basaltic volcanic landscapes, and SAR data-processing algorithms applied to volcanic terrain data.
Analysis of the 2023 F-SAR data at Askja enabled characterisation of seven lava flow units from 1961 (Vikrahraun) to >6100 yr BP using the full-polarimetric X-, S-, and L-band SAR with paired pin-profilometer and drone Digital Elevation Model (DEM) data (Figure 1). Across the Askja flow sequence, mean backscatter decreases systematically with flow age, and decomposition techniques partitions the flows sequence by facies. We now extend this framework to the Reykjanes Peninsula. 
Figure 1. Representative surface units. Left: field photos; centre: drone orthomosaics; right: drone-derived DEMs. (A) Inflated pāhoehoe with pressure ridges; (B) a'ā-pāhoehoe contact; (C) tephra plain with aeolian bedforms. Horizontal scale bars and DEM elevation ranges (m a.s.l.) shown per row.
Complementary analysis of field data across the fresher flows at the Reykjanes Peninsula enables bare-versus-mantled backscatter comparison of several flow units because of the occurrence of moss/lichen colonisation in a slightly warmer climate (Figure 2). Five age groups have been sampled: the Sundhnúkur-Svartsengi system, with nine flows emplaced between December 2023 to August 2025 along a c. 10 km fissure north of Grindavík (fieldwork ages 1-2.5 yr [6]); the Fagradalsfjall system comprising the 2021 Geldingadalir flow (5 yr [7]); the Skollahraun and younger Afstapahraun lavas (c. 2000 yr [8]); the Litla Eldborg flow field (>4000 yr [8]); and the Þráinsskjöldur shield (c. 12,500-14,100 yr [8]). The older three groups carry progressively thicker moss and lichen coverage. This combination delivers a bare versus mantled comparison at matched ages within a single field area at near-uniform basaltic composition, and supports lava-flow facies analysis within each flow field. 
Figure 2 Field morphology and flow-age contrasts. (A) Direct contact between younger a'ā and older moss-covered pāhoehoe; foreground field of view c.3 m. (B) Examples of morphological end-members: rubbly a'ā, inflated pāhoehoe, and sheet pāhoehoe; foreground field of view c.2 m.
Our 2026 field investigations yielded a series of important datasets: facies maps of the Sundhnúkur sequence at 1:5000 scale (classifying pāhoehoe, rubbly pāhoehoe, slabby/platy, spiny, and ʻaʻā facies on selected flows); pin-profilometer surface roughness measurements across the Reykjanes flows (distributed by facies, age, and surface-cover) (Figure 3), and drone-derived DEMs spanning the different facies and ages for scaling roughness statistics up to the scale of the spatial resolution of the F-SAR data (2 m). Together, these measurements deliver fine-scale topography (slopes at cm, dm, and m scales) linking millimetre-scale surface roughness to SAR backscatter at S- and X-band, and enable the quantification of fine-scale morphology (channels, breakouts, tumuli, rubble margins) for direct correlation with radar backscatter. Combined with the existing Askja results, these datasets deliver age sequences of basaltic lava flows with bare and mantled patches, co-located ground-truth from mm to m scale, all tied to multi-frequency polarimetric F-SAR data.
Figure 3 Ground-truth surface roughness characterisation. (A) Ropy pāhoehoe close-up with lens cap (c.7 cm diameter) for scale. (B) Penn Industries M5-S pin profilometer (1 mm pin spacing) capturing a transverse profile across pāhoehoe ropes.
The combined F-SAR and field dataset has supported four types of analysis: (i) comparison of Mascolo dual-pol [9] and Freeman-Durden quad-pol [10] decompositions across the facies and age, across Askja and Reykjanes flow sequences; (2) Comparison of bare and mantled flows to test penetration by long wavelengths through dry mantling materials into lava-roughness scattering; (3) integrated analysis of multi-temporal airborne F-SAR scenes and with; and (iv) progressive degradation of F-SAR products from 2 m to 10 m, 30 m to simulate VenSAR imagery and evaluate the effect of spatial resolution on scattering characteristics.
Venus is a barren basaltic landscape where surface modification is driven by chemical weathering and cementation from basalt–atmosphere interactions at 460°C and 92 bar [11], rather than by the rapid aeolian and biological processes that dominate Earth's basaltic surfaces. These reactions progressively modify surface texture and dielectric properties relevant to radar scattering. This terrestrial analogue work cannot directly emulate Venusian weathering, but it can rigorously partition modification mechanisms on Earth and demonstrate systematic backscatter patterns across them.
The analysis yields a multi-frequency polarimetric scattering library resolved by flow age and facies at the VenSAR pixel scale, with bare-versus-mantled comparisons of flows of various ages, and a quad-pol versus dual-pol decomposition comparison tuned to VenSAR’s HH+HV configuration. In addition, a quantitative framework is built which links mm- and cm- scale topography to m- and dm- scale backscatter, slopes, and polarimetric signatures over basaltic volcanic landscapes, supporting sub-pixel detection of surface properties.
References. [1] EnVision Red Book, ESA-SCI-DIR-RP-003. [2] Keller et al., EUSAR 2024. [3] Hensley et al., LPSC 2024 #1137. [4] Mastrogiuseppe et al., LPSC 2024 #1447. [5] Nunes et al., LPSC 2024 #1681. [6] Pinter et al., Nat Hazards 2026. [7] Pedersen et al., GRL 2022. [8] Sæmundsson et al., Jarðfræðikort af Suðvesturlandi 1:100,000 (2nd ed.), Íslenskar orkurannsóknir, 2016. [9] Mascolo et al., IEEE TGRS 2021. [10] Freeman & Durden, IEEE TGRS 1998. [11] Filiberto et al., Sci Adv 2020.
How to cite: Davidova, N., Gallardo i Peres, G., Gao, Y., Awasthi, S., Ghail, R., Moreira, A., Jaeger, M., Benedikter, A., and Mason, P.: Multi-scale surface characterisation of recently erupted lava flows on the Reykjanes Peninsula: a 2026 field campaign in support of EnVision mission science development, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-858, https://doi.org/10.5194/epsc2026-858, 2026.
With 1 Venusian day lasting 243 Earth days, Venus is the slowest-spinning planet in the Solar System and its rotational bulge is anomalously small. A rotational bulge (flattening) is the excess mass around the equator that stabilizes the orientation of planets. Having only a tiny stabilizer, the rotational pole of Venus is expected to easily separate from the figure pole (main inertia axis of the planet, MIA), which has been used to explain why both poles are observed to be 0.5° apart (Konopliv et al., 1999), several orders of magnitude more than on other terrestrial bodies.
One possible explanation for the 0.5° spin-figure axes (ω-MIA) offset is mantle convection (Spada et al., 1996). Here, we couple 3D mantle-convection simulations and polar motion dynamics to explore how mantle flow, and in particular surface mobilization, drives Venus’s polar motion. We provide a predictive framework for polar motion on slow rotators and show that the spin-figure pole separation (or offset) follows a simple law: it scales with the figure-axis drift rate times the planet’s Chandler period (Fig. 1b). However, in models matching Venus’s geoid, the figure-axis drift rate reaches only up to a few degrees per Myr (Fig. 1c), which is too slow compared to ca. 60°/Myr that is needed to excite the observed 0.5° offset (Patočka et al., 2025).
Another possibility is that it is the torque exerted on the solid Venus by its atmosphere that drives the ω-MIA offset. The atmosphere of Venus is extremely dense, with pressures reaching 93 bar at the surface, and its 4-day superrotation remains enigmatic. Several studies suggest that significant torques could result from the friction accommodating the interaction between atmospheric circulation and the topography of Venus (Navarro et al., 2018; Navarro and Schubert, 2024). Length of day variations suggest that the relative angular momentum of Venus’s atmosphere varies over time with diurnal and semidiurnal frequencies (Margot et al., 2021). To understand the role of torques exerted by the atmosphere on solid Venus, we solve the polar motion dynamics equations for arbitrarily prescribed surface forcing and investigate how the spin and figure axes separate during the excited polar motion. Both time-constant and time-varying torques are applied, mimicking different possible mechanisms of angular momentum transfer between the atmosphere and solid Venus. The results help in understanding the link between the atmospheric and polar motion dynamics of Venus and can be used to constrain the transfer of angular momentum between the atmosphere and the solid surface.
Figure 1: Polar motion response of Venus. a,b) Synthetic tests in which the loading is artificially prescribed: inertia axis of the load is first moving at the rate of 5°/Myr (polar motion is scalloped) and then abruptly slowing down to 1.2°/Myr (the change induces wobbling). The imposed difference between the main and the minor moments of inertia (C−A) is 2 orders of magnitude larger than C−A of the rotational bulge, similarly to values obtained from the observed geoid. In
steady state, the angular offset between the spin and figure axes α follows our scaling law, shown by the orange dashed line and described in the legend. c-d) Mantle convection simulation with moderate surface mobility. Paths of the rotational and figure poles on the globe (c), the evolution of Chandler period, as computed from the mantle flow-induced geoid (d), and the time evolution of the spin-figure axes offset, compared with our scaling law (panel e, blue vs. orange lines). The average angular separation of the figure and rotation axes is two orders of magnitude below the observed value (gray
dashed line). Adopted from (Patočka et al., 2025).
References
Konopliv, A., Banerdt, W., Sjogren, W., 1999. Venus gravity: 180th degree and order model. Icarus 139, 3–18.
doi:10.1006/icar.1999.6086.
Margot, J.L., Campbell, D.B., Giorgini, J.D., Jao, J.S., Snedeker, L.G., Ghigo, F.D., Bonsall, A., 2021. Spin state and
moment of inertia of venus. Nat. Astro. 5, 676–683. doi:10.1038/s41550-021-01339-7.
Navarro, T., Schubert, G., 2024. Mountain waves in the upper atmosphere of venus. Geophys. Res. Lett. 51,
e2023GL104922. doi:10.1029/2023GL104922
Navarro, T., Schubert, G., Lebonnois, S., 2018. Atmospheric mountain wave generation on venus and its influence on the
solid planet’s rotation rate. Nat. Geo. 11, 487+. doi:10.1038/s41561-018-0157-x.
Patočka, V., Maia, J., Plesa, A.C., 2025. Polar motion dynamics on slow-rotating venus: Signatures of mantle flow. AGU
Advances 6, e2025AV001976. doi:10.1029/2025AV001976.
Spada, G., Sabadini, R., Boschi, E., 1996. Long-term rotation and mantle dynamics of the Earth, Mars, and Venus.
J. Geophys. Res. Planets 101, 2253–2266. doi:10.1029/95JE03222.
How to cite: Patočka, V., Maia, J., and Plesa, A.-C.: Mantle and atmospheric drivers of the 0.5° offset between the spin and figure axes of Venus, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-786, https://doi.org/10.5194/epsc2026-786, 2026.
In the absence of seismic measurements, a powerful method that can be used to probe the interior structure of Venus is the joint analysis of gravitational and topographic data (see Wieczorek, 2015a for a review). Several studies have used gravity and topography data to construct global crustal thickness maps of Venus over the past two decades (Anderson and Smrekar, 2006; James et al., 2013; Jiménez-Díaz et al., 2015; Yang et al., 2016; Zampa et al., 2018; Batov et al., 2023; Broquet et al., 2025), with differences in crustal thickness values associated with differences in the method and/or assumptions in the crustal thickness modeling. These studies found that the crustal thickness of Venus varies from 0 to >90 km. It is important to note that the assumptions in the crustal thickness modeling may lead to significant changes in the obtained results. The most important of these assumptions is the density contrast between the mantle and crust, which affects both the overall average crustal thickness as well as the amplitude of crustal variations in our model. In addition, it is required either to assume a mean crustal thickness or to anchor the inverted crustal thickness to a given value at a specific location (Wieczorek, 2015a).
For example, Jiménez-Díaz et al. (2015) constructed a global crustal thickness map assuming a mean crustal thickness of 25 km, and crust and mantle densities of 2900 and 3300 kg m-3, respectively. They found that the Venusian crust is usually 20–25 km thick with a thicker crust under the highlands. Since the crust-mantle density contrast was constrained to be 400 kg m-3 in their analysis, the assumed average crustal thickness of 25 km played an important role in the crustal thickness distribution. They found that the minimum and the maximum crustal thickness increase as the assumed average crustal thickness increases; also, the amplitude of crustal variations increases slightly with the average crustal thickness. In this study, we expand upon that work by exploring in more detail the density dependence of the crustal structure of Venus.
Global crustal thickness models were obtained from gravity and topography following the procedure described in Wieczorek and Phillips (1998) and Wieczorek (2015a). The topography and gravity data were obtained from the spherical harmonic models VenusTopo719 (Wieczorek, 2015b) and MGNP180U (Konopliv et al., 1999) respectively. The spherical harmonic coefficients have been truncated beyond degree 70 for all models.
Figure 1 shows how the assumed average crustal thickness affects the minimum and the maximum thickness of our global crustal thickness models. Furthermore, we consider the effects of the assumed density structure of the crust. Figure 2 shows the average and maximum crustal thicknesses as a function of crustal density. For each of our crustal thickness inversions, we assume a mantle density of 3300 kg m−3.
Finally, crustal plateaus, which are the largest tessera occurrences, have been proposed to be made up of differentiated crust with a continental-like composition (Romeo and Turcotte, 2008). A felsic composition for tessera terrain has been favored by infrared emissivity observations (Hashimoto et al., 2008; Helbert et al., 2008; Gilmore et al., 2015) and structural studies (Romeo & Capote, 2011; Resor et al., 2021). In order to account for lateral variations in crustal density (see Wieczorek et al., 2022), we have constructed a density model considering two densities, 2900 kg m−3 for the basaltic crust and 2800 kg m−3 for crustal plateaus considering them as felsic crust in our analysis (Figures 3 and 4). Note that we have included as differentiated crust Lakshmi Planum and the surrounding montes (including Maxwell Montes) for the purpose of discussion.
Figure 1. (a) Minimum (thin dashed lines) and maximum (thick solid lines) crustal thickness as a function of the average crustal thickness. Each colored curve corresponds to a different crustal density, ranging from 2600 to 2900 kg m−3. (b) Histograms of crustal thickness for an average crustal thickness of 15 and 50 km, respectively. For these specific models, the crustal density is 2900 kg m−3.
Figure 2. (a) Average and maximum crustal thickness as a function of crustal density. For this suite of models, the minimum crustal thickness is constrained to 1 km. (b) Histograms of crustal thickness for a crustal density of 2600 and 3100 kg m−3, respectively.
Figure 3. (a) Topography of Venus from the spherical harmonic model VenusTopo719 (Wieczorek, 2015b), referenced to the mean planetary radius. (b) Reference crustal density model.
Figure 4. (a) Crustal thickness model for Venus with a constant density crust. For this specific model, the crustal density is everywhere 2900 kg m−3, the mantle density is 3300 kg m−3, and the minimum crustal thickness is constrained to 1 km. (b) Global crustal thickness model that considers a lower crustal density for the crustal plateaus (2800 kg m−3) than for the surrounding plains and lowland regions (2900 kg m−3).
References:
Anderson, F.S., & Smrekar, S.E. (2006). J. Geophys. Res., 111(E8), E08006.
Batov, A.V., et al. (2023). Sol. Syst. Res. 57, 25–34.
Broquet, A., et al. (2025). J. Geophys. Res.: Planets, 130, e2025JE009139.
Gilmore, M. S., et al. (2015). Icarus, 254, 350-361.
Hashimoto, G.L., et al. (2008). J. Geophys. Res.: Planets, 113, E00B24.
Helbert, J., et al. (2008). Geophys. Res. Lett. 35, L11201.
James, P.B., et al. (2013). J. Geophys. Res.: Planets, 118(4), 859–875.
Jiménez-Díaz, A., et al. (2015). Icarus, 260, 215–231.
Konopliv, A.S., et al. (1999). Icarus, 139(1), 3–18.
Resor, P.G., et al. (2021). J. Geophys. Res.: Planets, 126, e2020JE006642.
Romeo, I. & Turcotte, D.L. (2008). Earth Plan. Sci. Let., 276, 85-97.
Romeo, I., & Capote, R. (2011). Planet. Spa. Sci., 59, 1428-1445.
Wieczorek, M.A. (2015a). In T. Spohn & G. Schubert (Eds.) Treatise on geophysics (2nd ed.), 10, 153–193. Elsevier.
Wieczorek, M.A. (2015b). Spherical harmonic model of the planet Venus: VenusTopo719 [Dataset]. Zenodo.
Wieczorek, M.A., et al. (2022). J. Geophys. Res.: Planets, 127, e2022JE007298.
Yang, A., et al. (2016). Planet. Space. Sci., 129, 24–31.
Zampa, L.S., et al. (2018). Planet. Space Sci., 157, 48–62.
How to cite: Jiménez-Díaz, A., Álvarez-Lozano, J., Egea-González, I., Wieczorek, M. A., Romeo, I., and Ruiz, J.: Effect of crust density in global crustal thickness inversions on Venus, Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-953, https://doi.org/10.5194/epsc2026-953, 2026.
Introduction: The geochemical behavior of C and S has strongly influenced Venus’ evolution. Their degassing from the interior shaped the present greenhouse atmosphere and clouds [1,2], while they may also contribute to the low-viscosity melts responsible for surface features such as canali channels [e.g. 3,4] and the formation of surface coatings [5]. C and S further affect core properties and the potential for thermochemical convection within Venus’ interior. However, Venus’ interior and core composition remain poorly constrained. Ref. [6] examined permissible core mass fractions and O and Si contents based on geochemical modeling and moment of inertia, but did not consider C and assumed very high S contents (<22 wt.%), whose compatibility with current bulk Venus composition estimates remains uncertain.
Methods: Constraints on the C and S fluxes during accretion of Venus requires constraints on the chemical composition of bulk Venus. There is a significant degree of chemical similarity between bulk Venus and bulk Earth [7]. Venera and VEGA chemical data indicate that the K/Th and K/U ratios of Venusian basalts, which are considered representative of the bulk planet given the incompatibility and lithophile behavior of K [8], could point to similar abundance of volatile elements in both planets. However, estimates of 1–3.1 wt.% S have been inferred for bulk Venus, based on equilibrium condensation models [9]. This is up to 5 times higher than bulk Earth [10]. Instead, Venus likely has a similar volatile element budget compared to Earth, for example reflected by N and C estimates [11,12]. Mass balance considerations and dynamical models both point to volatile element homogenization of the Earth and Venus region [13]. For bulk Venus, bulk Earth values for C and S are thus assumed (2650±2220 µg/g C, 6100±1465 µg/g S [10]). This estimate also takes a potential depletion of S in bulk Venus relative to bulk Earth into account (Fig. 1). The available geophysical and geochemical models indicate a relative core mass of 22 to 38 mass % [6] which is the range that will be explored here.
To quantify the C and S budget of the core and co-existing silicate magma ocean, partition coefficients (D's) are required. The D's and solubilities of C and S were calculated along the estimated liquidus temperature of terrestrial pyrolite [16,17] using existing high-pressure models [18–20] that are calibrated up to pressures largely relevant for Venus’ mantle. Crystallization of an outer magma ocean on Venus likely occurs bottom upwards [7], with a maximum (average) core equilibration pressure of 80 GPa [21,22]. A basal magma ocean could have existed on Venus [22], which would have evolved largely isolated from the outer magma ocean, thereby not affecting the subsequent evolution of C and S in the outer magma ocean. Accretion models of Venus indicate a peak temperature of metal equilibration of 3750 K and 71 GPa [e.g. 21]. Using the assumed bulk S and C content, the degree to which both C and S partitioned into the core and mantle was calculated assuming (1) a simplified single-stage and full equilibration model [6,18] assuming an ‘’average’’ core formation pressure or (2) by implementing the results of multi-stage accretion models [18,21] for Venus.
Fig. 1: Bulk planet S abundances [10,14,15] versus heliocentric distance
Results: In this abstract, we only report results on the single-stage accretion model. For the considered CMF range, the mantle FeO content was re-calculated to ensure internal consistency (Fig. 2). For example, for a bulk Venus composition with 31.2 wt. % Fe [10], comprising a 90 wt.% Fe core, a CMF of ~0.22 corresponds with a FeO mantle content of 20 wt.%. For the latter composition, the maximum CMF is ~0.35.
Fig. 2 Venus’ CMF versus mantle FeO, MgO for a bulk Earth composition. Vertical shaded bar represents the considered core mass fractions in this study [e.g. 6].
The resulting core and mantle composition for element i was then calculated using a simple mass balance approach [23]. The calculations suggest a bulk Venus core composition of 0.1–2.2 wt.% C and 1.2–3.4 wt.% S. Despite the many uncertainties related to Venus, several commonly assumed core compositions can be ruled out based on plausible geochemical constraints. The S content inferred for the core is generally lower than considered in previous studies: the calculations exclude intermediate or S-rich core compositions as proposed in previous work [6]. Unless bulk Venus was significantly enriched in S, which does not agree with existing geochemical or dynamical models of the inner solar system, the Venusian core is relatively S-poor, regardless of the accretion scenario considered. More modeling results will be reported at the meeting.
Fig. 3 Calculated bulk core and mantle C and S content assuming single-stage core formation. Given the overall iron-loving behavior of S and C across a wide range of P-T conditions, the core compositions are (near)-constant across the full P-T range applicable to Venus.
Acknowledgments: ESS acknowledges funding of ERC StG VenusVolAtmos.
References: [1] Gillmann et al. (2022) Space Sci Rev [2] Jorritsma et al. (this meeting) [3] Aerts et al. (this meeting) [4] Jorritsma et al. (2026) LPSC [5] Dyar et al. (2021) Icarus [6] Shah et al. (2022) Astrophys. J. [7] Lammer et al. (2020) Icarus [8] Treiman (2009) Venus Geochemistry: Progress, Prospects, and New Missions [9] Kaula et al. (1981) In: Basaltic volcanism on the terrestrial planets [10] Wang et al. (2018) Icarus [11] Halliday (2013) GCA [12] Lécuyer et al. (2000) EPSL [13] Wetherill (1986) In: Origin of the Moon [14] Lodders & Fegley (1997) Icarus [15] Steenstra et al. (2019) Icarus [16] Fiquet et al. (2010) Science [17] Andrault et al. (2011) EPSL [18] Suer et al. (2017) EPSL [19] Blanchard et al. (2022) ESPL [20] Steenstra et al. (2022) GPL [21] Rubie et al. (2015) Icarus [22] Trønnes et al. (2019) Tectonophys [23] Steenstra and van Westrenen (2020) Icarus
How to cite: Steenstra, E. and Suer, T.-A.: The Carbon and Sulfur Cycles during Accretion of Venus and Implications for its Enigmatic Evolution , Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-784, https://doi.org/10.5194/epsc2026-784, 2026.
Introduction: The possibility of oceans on early Venus remains at the centre of a wider debate about the evolution of climate divergence with Earth. Modern Venus’s atmosphere presents low water vapour abundance (e.g.,Bézard et al., 2011; Cottini et al., 2015; Encrenaz et al., 2015) and a substantially enriched deuterium-to-hydrogen D/H ratio relative to Earth (Fedorova et al., 2008; Taylor & Grinspoon, 2009; Krasnopolsky et al., 2013; Encrenaz et al., 2015; Wilson et al., 2021; Westall et al., 2023; Mahieux et al., 2024). This high D/H ratio might constitute evidence for loss of a substantial water reservoir (Taylor & Grinspoon, 2009; Way et al., 2016; Gillmann et al., 2020; Wilson et al., 2021). Climate modelling studies have also shown two possible scenarios. Some models argue that a temperate climate is possible from the combination of slow rotation and dayside cloud-albedo feedback (Yang et al., 2014; Way et al., 2016; 2020). Other models suggest that water condensation from the steam atmosphere was prevented by nightside stratospheric clouds (Turbet et al., 2021). Another line of evidence comes from tidal dissipation in a putative ocean. Green et al., 2019 showed a similar magnitude effect to the present-day torque exerted by the modern dense atmosphere can be produced by ocean tides on Venus in a 330-m mean depth ocean. Here, we explore a possible evolutionary branch on early Venus, assuming water condensation from the steam atmosphere, to examine ocean circulation, tides, and their transfer of angular momentum from the ocean to the solid body.
Ocean circulation: Assuming water condensation from the steam atmosphere, we will explore the ocean circulation and heat redistribution on a putative ocean on Venus at 2.9 Ga. We simulate the ocean using the 3D General Circulation Model (GCM), the ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics), developed at the NASA Goddard Institute for Space Studies (Way et al., 2017). We use a spatial resolution of 4º x 5º (latitude by longitude), a 40-layer atmosphere (top pressure, 0.1 hPa), and a 13-layer fully dynamic ocean (Russel et al., 1995) coupled to the atmosphere. All simulations use an isolation of 2001 W/m2, 1.47x times that of modern Earth, representing conditions at 2.9 Ga. Atmospheric composition is Earth-like, with a 1-bar N2 atmosphere (400 ppm CO2 and 1 ppm CH4) (Way et al., 2020). Modern values of Venus’s surface gravity, radius, obliquity, eccentricity and rotation rate (retrograde slow-rotator: -243 days) are used (Way et al., 2016).
Here we present results of four ocean scenarios, with different global equivalent layers (GEL): two using a modern Venus-like topography, 310-m and 1000-m, provided by the NASA/Magellan archive; one with a 1360-m bathtub ocean (subareal topography equal to the 310-m Venus, no bathymetry); and a 158-m aquaplanet. In the 310-m scenario (reference), the ocean covers about 60% of the surface and has a volume of 1.4 x 1017 m3, one order of magnitude below that of modern Earth’s Ocean or 10% its volume (Way et al., 2016). The 1000-m scenario explores a deeper ocean on Venus, with a volume of 35% of Earth’s Ocean and a surface area of about 88%. The 1360-m bathtub Venus explores the impacts of bathymetry and land distribution on the ocean circulation. The 158-m aquaplanet is used as a control case. Main results show a significant monthly-long diurnal cycle, leading to the day-night reversal of ocean and atmospheric circulations (see Figure 1) in all cases.
Figure 1. Coupled Ocean-Atmosphere stream functions for the four ocean scenarios. The left (right) part of each diagram depicts the day (night) circulation. The yellow circle represents the ocean surface.
This diurnal cycle also leads to the development of a considerable mixed layer at the equator, largely impacting global patterns of subsidence and upwelling. Our results also show that, due to the albedo feedback, lower sea surface area, the 310-m Venus has a colder global temperature: 15ºC colder than the 158-m Aquaplanet despite having the same water volume, highlighting the importance of land/sea surface in controlling climate and the longevity of this climate state. In the case of the 310-m Venus, a highly saline Southern Ocean forms controlled by a mass balance favouring evaporation and limited exchange with the remaining global ocean.
Ocean tides: Tides on a Venusian ocean are simulated using the Oregon State University Tidal Inversion Software (OTIS), which solves the linearised shallow-water equations (Egbert et al., 2004), and is extensively used to simulate tides on Earth (Green et al., 2017; 2018; Wilmes et al., 2017). Previous simulations assume a modern topography on Venus (Green et al., 2019). However, the present-day volcanic topographic rises might not have formed on early Venus, as geodynamic studies suggest (e.g.,Tian et al., 2023). In this work, we replace the volcanic rises with topography generated by geodynamic model evolution, while keeping the highlands as Aphrodite and Ishtar Terrae (see Figure 2). We explore the impact of multiple rotation rates (from prograde to retrograde, including fast- and slow-rotator cases), stratification, and ocean depth.
Figure 2. (Left) NASA/Magellan topography. (Right) New topography with the removal of volcanic topographic rises.
References: Bézard B, et al.,2011.Icarus.216:173 --Cottini et al.,2015.Space Sci.113:219 --Egbert, G.D., et al.,2004.JGRC,109,C03003 --Encrenaz T, et al.,2015. Space Sci.113:275 --Fedorova,A, et al.,2008.JGR:Planets, 113,E5 --Gillmann, C, et al.,2020.Nat Geosci,13,4 --Green, J., et al.,2017.E&PSL, 461,46 --Green, et al.,2018.GeoRL, 45, 3568 --Green, et al.,2019.ApJL,876, L22 --Krasnopolsky V, et al.,2013.Icarus.224:57 --Mahieux, A, et al.,2024.PNAS, 121,34 --Russell G.L., et al.,1995.Atmos-Ocean.33:683 --Taylor, F & Grinspoon, D,2009.JGR:Planets,114,E9 --Tian, J., et al.,2023.Icarus, 399, 115539 --Turbet M., et al.,2021.Nature.598:276 --Way M.J., et al.,2016.GRL.43 --Way M.J., et al.,2017.ApJS.213:12 --Way M.J. & Del Genio A.D. 2020.JGR:Planets.125 --Way M, et al.,2022. Sci. J.3:92 --Westall, F,2023.Space Sci Rev, 219, 2, 17 --Wilmes, S.-B.,2017.JGRC, 122, 8354 --Wilson, C.F., et al.,2022.Exp Astron, 54,2 --Yang J, et al., 2014.ApJL., 787, L2.
Funding: DQ acknowledges this work to be supported by FCT - Fundação para a Ciência e Tecnologia, I.P. by project reference and DOI identifier 10.54499/2023.05220.BD
How to cite: Quirino, D., Green, J. M., Way, M. J., Duarte, J. C., Machado, P., Gillmann, C., and Lourenço, D. L.: Tides and Ocean Circulation on a temperate ancient Venus , Europlanet Science Congress 2026, The Hague, The Netherlands, 6–11 Sep 2026, EPSC2026-1039, https://doi.org/10.5194/epsc2026-1039, 2026.