Ian Thomas

Aims . We use carbon monoxide (CO), a long-lived species in the Martian atmosphere, as a tracer to constrain atmospheric transport by characterizing its vertical distribution from the near-surface to an altitude of about 120 km. Methods . We retrieved CO vertical profiles from solar occultation (SO) spectra acquired by the SO channel of the Nadir and Occultation for MArs Discovery (NOMAD) instrument on board the ExoMars Trace Gas Orbiter (TGO). The dataset covers L _s = 160° in Mars year (MY) 34 to L _s = 120° in MY 36, enabling analyses over broader altitude and seasonal ranges than in previous works. We validated the retrievals using co-located measurements from the from Atmospheric Chemistry Suite (ACS) instrument on board TGO. Results . The retrieved CO volume mixing ratio (VMR) is enhanced above 40 km at both poles during seasonal spring and autumn. In summer and winter, the enhancement is largely confined to the winter polar region. These variations are in quantitative agreement with earlier observations and are consistent with seasonal changes in the meridional circulation. We also find larger CO number densities near the morning terminator during local winter in the 80–100 km altitude range, consistent with a modulation of the transport by a semidiurnal tide. During the MY 34 planet-encircling dust event, enhanced CO VMRs are confirmed at 80–110 km in altitude, but no corresponding enhancement in the CO number density is seen, suggesting that the apparent VMR variation is driven primarily by changes in atmospheric dynamics, rather than by photochemistry.

IntroductionThe 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 GroupNeed for solar spectral irradiance at VenusGiven 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 GroupThe 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 & PerspectivesThe 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.

IntroductionThe Martian atmospheric aerosols are mainly composed of mineral dust and/or water ice. Water ice clouds affect both the radiative balance [1] and the water cycle [2], while mineral dust is globally the most abundant component, modifying the thermal structure and atmospheric dynamics [3,4]. It can affect observations from both orbiting satellites and rovers on ground, especially at the dusty season around perihelion, where many storms are initiated at different temporal and spatial scales [5].Both aerosol types are related, as dust can serve as a base for water ice cloud formation [5]. Therefore, a comprehensive understanding of the Martian atmosphere requires a simultaneous climatology of both components, such as the one presented in this work.Dataset and methodologyNOMAD is a three spectrometers suite on board the Trace Gas Orbiter (TGO). It has been routinely observing the Martian atmosphere since April 2018 [6], providing detailed atmospheric transmission vertical profiles. Data acquired from its solar occultation (SO) channel are used to retrieve aerosol properties and their vertical distributions in the infrared at high vertical resolution. This is achieved by combining multiple diffraction orders (i.e., wavelength intervals), selected to maximize coverage of the SO spectral range while consistently including an order near 3 μm. This spectral region is key to distinguish between dust and water ice aerosols [6].Our retrieval strategy builds on [7] and is thoroughly described there. The inferred aerosol characteristics using this methodology are size (effective radius and variance) and composition (proportions of mineral dust and water ice). These magnitudes are used to derive other aerosol magnitudes such as number density, mass loading and mass mixing ratio.We processed ~3000 SO observations from Ls = 194° (MY34) to the end of MY37, significantly extending the dataset in [7], focused only on the first year of NOMAD observations. We have also developed a scheme to identify cases with mixed aerosol components (dust and ice) from those where there is a single dominant component, and the secondary one is only adding noise to the results. ResultsIn contrast to [7], due to our extended dataset we can study latitudinal and interannual comparisons between the different Martian Years, being able to detect the global patterns that govern the distribution of dust and water ice clouds.We report an average maximum altitude of aerosol detection around 60 km near perihelion (Ls ~ 270°) and 40 km near aphelion (Ls ~ 90°). Variations within these values are sometimes significant, and linked to the latitude of the observations. Our results reveal features such as water ice clouds and signatures of both regional and global dust storms. All four Martian Years show systematic differences of their aerosol properties between aphelion and perihelion, which is consistent with the previous work by [7].Lastly, a comparison of our results with similar datasets from NOMAD-UVIS [8] and ACS [9] has been performed. This comparison focuses on comparing the extinctions and effective radius retrieved, as well as their seasonal and latitudinal distribution. We have found that NOMAD-UVIS retrieves in average smaller particle sizes than SO, which is more sensitive lo larger sizes. Therefore, both wavelength ranges, ultraviolet and infrared, are complementary to produce a complete climatology of Martian aerosols. This combined information is important for improving climate models, which rely on a priori assumptions about aerosol microphysics, composition, and optical properties. References: Wilson, R.J, et. al., 2008.Montmessin, F. et. al, 2004.Michael Battalio and Huiqun Wang, 2021.Smith, M.D. et. al, 2019.Määttänen, A. and Montmessin, F., 2021Vandaele, A, C. et. al, 2018Stolzenbach, A. et. al, 2023.Flimon, Z., et. al, 2025.Schterbinine, A. et. al, 2022

Introduction and GoalThe upper atmosphere of Mars, spanning the mesosphere (60–120 km) and the thermosphere up to the exobase (180–230 km), remains one of the least characterized regions of the planet [1]. Its structure is shaped by solar forcing, upward‑propagating waves, and dust‑driven variability originating in the lower atmosphere; however, the relative importance of these processes and their vertical coupling are not yet fully understood [2]. Two recent missions provide complementary datasets: NASA’s MAVEN mission, operational since 2014, focuses on upper‑atmosphere processes and atmospheric escape, while ESA–Roscosmos’ Trace Gas Orbiter (TGO), in routine operation since 2018, carries the NOMAD and ACS instruments, which retrieve atmospheric profiles from near‑surface layers to the upper thermosphere.In this work, we combine MAVEN and TGO observations with the primary objective of producing a comprehensive climatology of the thermal structure of the Martian upper atmosphere. This study is part of a broader andn recent project funded by the International Space Science Institute (ISSI) entitled “A multi-mission approach to close the gaps in understanding of the structure and variability in the Mars upper atmosphere”. Most TGO datasets concentrate below 100 km, whereas MAVEN primarily samples thermospheric altitudes. Because TGO data extend to lower altitudes, we actually present results spanning from the troposphere to the exosphere. The combined dataset integrates nine types of measurements from both missions, including in situ observations (NGIMS/MAVEN) and remote‑sensing measurements from NOMAD, ACS, EUVM, and IUVS (solar and stellar occultations, as well as dayglow). Together, these datasets cover multiple Martian years and an altitude range of 30–180 km, providing unprecedented vertical and temporal coverage. Exploiting this complementarity, particularly the vertical coupling between the lower and upper atmosphere, is also a major scientific goal of the present research.In this climatological study, we explicitly exclude a set of short‑lived and sporadic phenomena, such as dust storms, solar eruptions, and small‑scale atmospheric waves. Our focus is on the systematic variations associated with the following geophysical variables: altitude, latitude, season, local time, solar cycle, and longitude.Datasets, Synergies, and ChallengesThe datasets exhibit highly diverse characteristics, including field of view, spatial and temporal coverage, sensitivity, and noise levels, posing challenges for the synergetic analysis pursued here. To address coverage differences, we devoted substantial effort to designing appropriate binning strategies and averages across geophysical variables. Regarding sensitivity and retrieval performance, we used nominal uncertainties but filtered out the highest‑uncertainty percentile, and we developed a unified quality‑control framework applied to the nominal errors of each experiment. This framework aims to eliminate spurious values and identify potential biases, as revealed through cross‑comparisons within well‑defined geophysical bins. We also performed a variance‑partitioning analysis as a function of geophysical forcings, enabling us to distinguish intrinsic atmospheric variability from instrumental effects. Two vertical coordinates were used: altitude above the Martian aeroid and a modified‑CO₂ scale‑height coordinate, which is more suitable for upper‑atmosphere comparisons. Special attention was given to solar‑occultation datasets from both MAVEN and TGO (terminator measurements at dawn and dusk) owing to their synergistic local‑time coverage and excellent vertical resolution.Selected ResultsWe will present a representative sample of this extensive analyses across this broad parameter space, including global composite temperature profiles, deviations from mean distributions, multi‑year time series, and an assessment of the dominant sources of thermal variability. Our results reveal substantial atmospheric variability, highly non‑linear with respect to geophysical parameters, and a hierarchy of dominant processes that varies with altitude and which shapes the global thermal structure.In particular we found that thermospheric temperatures respond strongly to solar flux, with variations exceeding 50 K above 150 km and decreasing toward 100 km, being very small below this altitude. In contrast, mesospheric temperatures are dominated by global circulation, producing seasonal and latitudinal gradients of 20–40 K. We will show how the combined datasets also reveal interhemispheric asymmetries, the impact of dust storms at multiple altitudes, and the propagation of atmospheric waves.Comparisons with MarsPCM and MCD simulations demonstrate that the model reproduces very well the mean vertical structure as well the seasonal and latitudinal variations observed, but underestimates the variability by factors of 1.5–2 and exhibit a few biases in the mesopause and upper thermosphere. In particular, tidal amplitudes in the mesosphere are weaker in the models, the lower‑thermosphere thermal gradient occurs at lower altitudes than what is observed, and the coldest thermospheric temperatures predicted by the models are significantly colder than those reported by EUVM.The resulting MAVEN–TGO climatology provides a robust reference for future measurements, model validation, and studies of Martian atmospheric dynamics and evolution. References[1] Bougher et al., JGR-Planets, 2017 [2] López-Valverde et al., Space Sci. Rev., 2018 [3] Giuranna et al., Space Sci. Rev., 2025 [4] Heavens et al., Nature, 2018 [5] Yiğit et al., Nature Geoscience, 2023 [6] Jakosky et al., Science, 2015 [7] Korablev et al., Space Sci. Rev., 2018 [8] Vandaele et al., Space Sci. Rev., 2018

Gravity waves play an important role in the dynamical forcing of the Martian climate. If the horizontal resolution of a Global Climate Model (GCM) is larger than the scale of these waves, their impact should be parameterised to simulate their effects on the mean flow. Typically, the parameterisations derive from Earth models and are not well constrained.The GEM-Mars GCM (Neary and Daerden, 2018; Daerden et al., 2023) has two schemes: one to simulate the impact of gravity waves from orographic sources such as mountains and topography (McFarlane, 1987), and one for non-orographic sources such as convective forcing and baroclinic waves (Hines, 1997a; 1997b; 2004; Charron et al., 2002). Both schemes calculate a deceleration of the grid-scale winds, often termed “gravity wave drag”. This can have an indirect effect on temperature and on the distribution of trace gases.The schemes include some “tuning” parameters that can be adjusted to modify when and where this drag occurs. For example, in the non-orographic scheme, the level at which waves are expected to be launched and the lower bound vertical wavenumber, which limits the maximum vertical wavelength of the spectrum allowed, can be adjusted.Using estimates of wave activity derived from perturbations in observed temperature profiles from the ExoMars Trace Gas Orbiter and MAVEN (Neary et al. submitted), we will explore how these tuning parameters affect the resulting gravity wave drag climatology in GEM-Mars. By comparing model output with observational constraints across latitude, season, and local time, we aim to identify parameter settings that better reproduce the observed distribution and intensity of wave activity. This approach will help assess how well the current parameterisations capture the Martian atmosphere and where further refinement is needed.References:Charron, M. et al., 2002. Intercomparison of gravity wave parameterizations: Hines Doppler-spread and Warner and McIntyre ultra-simple schemes. Journal of the Meteorological Society of Japan 80, 335–345.Daerden, F. et al., 2023. Heterogeneous Processes in the Atmosphere of Mars and Impact on H2O2 and O3 Abundances. Journal of Geophysical Research: Planets 128, e2023JE008014. https://doi.org/10.1029/2023JE008014Hines, C., 1997a. Doppler-spread parameterization of gravity-wave momentum deposition in the middle atmosphere: Part 1 Basic Formulation. Journal of Atmospheric and Solar-Terrestrial Physics 59.Hines, C.O., 1997b. Doppler-spread parameterization of gravity-wave momentum deposition in the middle atmosphere. Part 2: Broad and quasi monochromatic spectra, and implementation. Journal of Atmospheric and Solar-Terrestrial Physics 59, 387–400.Hines, C.O., 2004. The Doppler spread theory and parameterization revisited. Journal of Atmospheric and Solar-Terrestrial Physics 66, 949–956. https://doi.org/10.1016/j.jastp.2004.02.005McFarlane, N.A., 1987. The effect of orographically excited gravity wave drag on the general circulation of the lower stratosphere and troposphere. Journal of the Atmospheric Sciences 44, 1775–1800.Neary, L., Daerden, F., 2018. The GEM-Mars general circulation model for Mars: Description and evaluation. Icarus 300, 458–476. https://doi.org/10.1016/j.icarus.2017.09.028Neary, L., et al., 2026. A multi-mission climatology of gravity waves in the Martian mesosphere and thermosphere. Submitted to Space Science Reviews.

Carbon monoxide (CO) is one of the most important tracers of atmospheric circulation and photochemical activity in the Martian atmosphere. Because of its relatively long chemical lifetime, its spatial and vertical distribution is strongly linked to the large-scale transport processes that shape the Martian climate. At the same time, CO is directly connected to the CO₂ photochemical cycle, making it a valuable probe of the coupling between atmospheric dynamics and chemistry. Since its first detections through ground-based observations several decades ago [1,2], CO has been extensively investigated by orbiters and space missions dedicated to the exploration of Mars. These observations have revealed strong seasonal, latitudinal, and vertical variations, highlighting the complexity of the Martian atmosphere and the need for long-term, high-resolution measurements to better constrain atmospheric circulation and photochemical models.The ExoMars Trace Gas Orbiter (TGO), launched in 2016, has significantly improved our capability to study trace species in the Martian atmosphere thanks to its high spectral resolution and global coverage. Among its scientific payload, two instruments are capable of observing CO: NOMAD and the Atmospheric Chemistry Suite (ACS) [3,4]. In particular, the ACS-MIR channel provides high-quality solar occultation measurements with exceptional sensitivity to the vertical structure of the atmosphere, allowing the retrieval of atmospheric profiles over a broad altitude range.In this work, we analyze solar occultation spectra acquired by the ACS-MIR channel, focusing on the CO (2–0) overtone absorption band between 4150 and 4350 cm⁻¹. We describe in detail the preprocessing steps applied prior to the atmospheric retrievals, including corrections for spectral bending and wavelength shifts, as well as improvements in the characterization of the instrumental line shape [5]. Particular attention has been devoted to the refinement of the error budget in order to properly account for instrumental and spectroscopic uncertainties affecting the measurements. These improvements are essential to maximize the accuracy and stability of the retrievals, especially when combining information from lines with very different sensitivities throughout the atmosphere.The spectra are analyzed using the KOPRA radiative transfer model coupled with the RCP inversion code [6] to retrieve vertical profiles of CO volume mixing ratio (VMR) and temperature. A detailed sensitivity analysis of the CO absorption lines at different atmospheric altitudes is also presented. Because the strongest CO lines become saturated below ~50 km, retrieving reliable information across the full atmospheric column requires a careful selection and combination of spectral lines probing different altitude regions. While saturated lines reduce sensitivity in the lower atmosphere, they remain crucial for constraining CO abundances in the upper atmosphere, particularly between ~80 and 120 km. To address this challenge, we developed a dedicated retrieval strategy that allows us to derive robust and continuous CO vertical profiles from the lower atmosphere up to the thermosphere.In addition, we demonstrate for the first time the simultaneous retrieval of temperature and CO VMR from a dataset containing only CO absorption lines. This is possible because the full CO absorption band is observed: the overall shape of the band contains information about the atmospheric thermal structure, while the depth and relative intensity of the individual absorption lines constrain the CO abundance. The methodology developed for this simultaneous retrieval represents a significant step forward for the analysis of ACS-MIR observations, and a more detailed explanation of this approach will be presented in this work.Using this method, we retrieve CO vertical profiles between ~7 and 120 km altitude and temperature profiles between ~7 and 100 km. We present temperature profiles for the first half of Mars Year (MY) 34 and compare them with other available datasets [8]. In addition, we show CO abundance maps covering MY 34 to MY 37, providing a multi-year overview of the seasonal and latitudinal variability of CO in the Martian atmosphere. The retrieved distributions are broadly consistent with previous studies [7,8], showing an approximately constant CO abundance below ~50 km and a marked increase at higher altitudes driven by photochemical production. Clear seasonal and latitudinal variations are also observed throughout MY 34–37, reflecting the influence of atmospheric transport and circulation processes. The implications of these results for our understanding of Martian atmospheric dynamics and photochemistry are discussed. [1] Krasnopolsky, V. A. (2007). Icarus, 190(1), 93–102. https://doi.org/10.1016/j.icarus.2007.02.015[2] Smith, M. D. (2004). Icarus, 167(1), 148–165. https://doi.org/10.1016/j.icarus.2003.09.010[3] Vandaele, A. C. et al. (2018). Space Science Reviews, 214(5), 80. https://doi.org/10.1007/s11214-018-0517-2[4] Korablev, O. et al. (2018). Space Science Reviews, 214(1), 7. https://doi.org/10.1007/s11214-017-0437-6[5] López-Valverde, M. A. et al. (2023). J. Geophys. Res. Planets, 128(2), e2022JE007278. https://doi.org/10.1029/2022JE007278[6] Stiller, G. P. (2000). FZKA Report, 6512, Forschungszentrum Karlsruhe.[7] Modak, A. et al. (2023). J. Geophys. Res. Planets, 128(3), e2022JE007282. https://doi.org/10.1029/2022JE007282[8] Fedorova, A. A. et al. (2022). J. Geophys. Res. Planets, 127(9), e2022JE007195. https://doi.org/10.1029/2022JE007195

Carbon monoxide (CO) is a minor trace gas of the Martian atmosphere that plays a key role in the photochemical cycle of carbon. CO is produced in the upper atmosphere by the carbon dioxide (CO2) photolysis, while its recycling through CO2 reformation occurs via catalytic reaction with the odd hydrogen radicals (HOx) produced by the water vapor (H2O) photolysis (see [1, 2] and references therein). As non-condensable species, CO column-averaged volume mixing ratio (VMR) is expected to show seasonal and spatial gradients that closely follow the seasonal CO2 condensation/sublimation processes at the poles and related surface pressure variation. Given its relatively long lifetime (~6 years), CO is often used as a tracer of the atmospheric dynamical patterns.Mars CO column abundance observations from space are relatively sparse, with Mars Express OMEGA [3] and PFS instruments [4, 5], and CRISM aboard the Mars Reconnaissance Orbiter [6, 7]. More recently, the ExoMars Trace Gas Orbiter NOMAD-LNO spectrometer has provided a climatology of CO VMR at a global scale covering slightly more than a full Martian Year (MY 34, Ls=150° to MY 35, Ls=241°; March 2018-July 2020) of observations [8]. The globally averaged CO VMR derived from these data sets is found to range from ~800 to 1000 ppm with corresponding uncertainties of 20-45%.Here we present the seasonal and spatial CO column abundance distributions derived from NOMAD-LNO dayside nadir observations over the full mission period (MY 34-38). LNO (Limb Nadir and solar Occultation) is one of the two echelle grating infrared spectrometers installed on the NOMAD (Nadir and Occultation for MArs Discovery) instrument aboard the ESA ExoMars Trace Gas Orbiter (TGO) [9]. In these spectrometers, the echelle grating is combined with an Acousto-Optic Tunable Filter (AOTF) for the spectral window selection [10]. As for our LNO H2O column retrieval [11], the LNO nadir CO column-averaged VMRs are retrieved using the Optimal Estimation scheme [12] implemented in the ASIMUT-ALVL radiative transfer tool [13]. ASIMUT-ALVL is applied separately to LNO reflectance factor spectra from grating orders 186-191 covering the ~4180-4330 cm-1 wavenumber range. Altitude, pressure, temperature, CO, dust, and water ice a priori vertical profiles are extracted at the spectra locations from the GEM-Mars General Circulation Model [14]. Scattering by dust and water ice particles is taken into account in the forward simulations by using the LIDORT radiative transfer model [15]. Our retrieval also includes the new evaluations of the LNO AOTF function and its central position temperature dependence [11].In this presentation, we will first discuss the consistency of the retrieval results between the selected diffraction orders and the impact of the CO absorption lines saturation on the retrieval results. The retrieved CO VMR seasonal, latitudinal, and inter-annual patterns will be then assessed over the full mission period and our data set will be compared to other available observational data sets (CRISM, PFS, and LNO from [7], [5], and [8], respectively), and to output from the GEM-Mars General Circulation Model. The correlation between LNO CO and H2O column abundances will be also investigated.AcknowledgementsThe NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA) with co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS) and the United Kingdom (Open University). This project acknowledges funding by: the Belgian Science Policy Office (BELSPO) with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401, 4000121493, 4000140753, 4000140863); by the Spanish Ministry of Science and Innovation (MCIU) and European funds (grants PGC2018-101836-B-I00 and ESP2017-87143-R; MINECO/FEDER), from the Severo Ochoa (CEX2021-001131-S) and from MCIN/AEI/10.13039/501100011033 (grants PID2022-137579NB-I00, RTI2018-100920-J-I00 and PID2022-141216NB-I00); by the UK Space Agency (grants ST/V002295/1, ST/V005332/1, ST/X006549/1, ST/Y000234/1 and ST/R003025/1); and by the Italian Space Agency (grant 2018-2-HH.0).References[1]McElroy M. B., and T. M. Donahue (1972), Stability of the Martian atmosphere, Science 177, 986–988, DOI: 10.1126/science.177.4053.986[2]Vandaele, A. C., et al. (2024), Composition and Chemistry of the Martian Atmosphere as Observed by Mars Express and ExoMars Trace Gas Orbiter, Space Science Reviews, 220:75, https://doi.org/10.1007/s11214-024-01109-7[3]Encrenaz, T., et al. (2006), Seasonal variations of the martian CO over Hellas as observed by OMEGA/Mars Express, Astronomy and Astrophysics, 459, 265–270, DOI: 10.1051/0004-6361:20065586[4]Sindoni, G., et al. (2011), Observations of water vapor and carbon monoxide in the Martian atmosphere with the SWC of PFS/MEX. Planetary and Space Science, 59, 149-162, DOI: 10.1016/j.pss.2010.12.006[5]Bouche, J., et al. (2021), Seasonal and spatial variability of carbon monoxide (CO) in the Martian atmosphere from PFS/MEX observations, Journal of Geophysical Research: Planets, 126, e2020JE006480, https://doi.org/10.1029/2020JE006480[6]Smith, M. D., et al. (2009), Compact Reconnaissance Imaging Spectrometer observations of water vapor and carbon monoxide, J. Geophys. Res., 114, E00D03, https://doi:10.1029/2008JE003288[7]Smith, M. D., et al. (2018), The climatology of carbon monoxide and water vapor on Mars as observed by CRISM and modeled by the GEM-Mars general circulation model, Icarus, 301, 117-131, https://doi.org/10.1016/j.icarus.2017.09.027[8]Smith, M. D., et al. (2021), The climatology of carbon monoxide on Mars as observed by NOMAD nadir-geometry observations, Icarus, 362, 114404, https://doi.org/10.1016/j.icarus.2021.114404[9]Vandaele, A. C., et al. (2015), Science objectives and performances of NOMAD, a spectrometer suite for the ExoMars TGO mission, Planetary and Space Science, 119, 233-249, https://doi.org/10.1016/j.pss.2015.10.003[10]Thomas, I. R., et al....

Hydrogen chloride (HCl) is one of the most recent trace species discovered in the Martian atmosphere, renewing interest in the study of its climatology. Since its unambiguous detection by the Trace Gas Orbiter (TGO) in 2021 [1,2], several studies have focused on characterizing the spatial distribution and variability of this trace species and on understanding the processes controlling its presence in the atmosphere. Observations from the two TGO instruments capable of detecting HCl in solar occultation geometry, NOMAD and ACS, have consistently reported detections mainly during the second half of the Martian year, corresponding to the perihelion season and southern summer. These enhanced abundances are followed by a rapid decline toward the end of the year. During aphelion and northern summer, however, HCl detections from orbit remain rare and close to instrumental detection limits. This pattern has been observed repeatedly across multiple Martian years, with no noticeable interannual variability.Several hypotheses have been proposed to explain the sources and sinks of HCl, its strong seasonal variability, and its preferential occurrence during perihelion. One possible source mechanism involves interactions between the surface and the atmosphere through the lifting of chlorine-bearing dust and subsequent reactions releasing chlorine species into the atmosphere. On the other hand, heterogeneous uptake by water ice particles has been proposed as a plausible sink for HCl [3, 4]. However, systematic observations of temporally and spatially collocated HCl and aerosol (dust and water ice) profiles are needed in order to provide further constraints on these hypotheses.In this work, we present a climatology of HCl derived from four Martian years of NOMAD Solar Occultation observations. This instrument is an excellent asset for the detection and systematic monitoring of trace species in the Martian atmosphere. It provides high spectral resolution (λ/∆λ ∼ 17000) and high sensitivity thanks to the excellent signal-to-noise ratio achieved in the solar occultation geometry [5]. We investigated the seasonal and latitudinal variability of HCl vertical profiles throughout 5245 solar occultations, of which 291 profiles showed reliable HCl detections. We focused the analysis on the vertical structure and local time dependence of the retrieved profiles during the perihelion season, in addition to the study of correlations between HCl and other atmospheric species such as water vapor and aerosols. Our analysis confirms that HCl is primarily observed during southern summer, in agreement with previous studies analyzing orbital [1,2,6] and ground-based observations [7], while no robust detections are identified during the aphelion at tangent altitudes with optimum transmittance levels. Our results show that HCl is generally found at altitudes where water vapor abundances are enhanced, and both species exhibit a strong positive correlation, in agreement with previous studies [8]. We also observe a remarkably similar vertical structure of HCl at the morning and evening terminators. Finally, using collocated aerosol observations, we compare HCl distributions with dust and water ice abundances, finding a positive correlation with dust abundance but no clear correlation with water ice abundance.References:[1] Korablev, O., Olsen, K. S., Trokhimovskiy, A., Lef`evre, F., Montmessin, F., Fedorova, A. A., . . . others (2021). Transient HCl in the atmosphere of Mars. Science Advances, 7 (7),eabe4386[2] Aoki, S., Daerden, F., Viscardy, S., Thomas, I. R., Erwin, J. T., Robert, S., . . . others (2021). Annual appearance of hydrogen chloride on Mars and a striking similarity with the water vapor vertical distribution observed by TGO/NOMAD. Geophysical Research Letters, 48 (11), e2021GL092506[3] Taysum, B. M., Palmer, P. I., Olsen, K., Luginin, M., Ignatiev, N., Trokhimovskiy, A., . . . Korablev, O. (2024). Observed seasonal changes in Martian hydrogen chloride explained by heterogeneous chemistry. Astronomy & Astrophysics, 687 , A191.[4] Luginin, M., Trokhimovskiy, A., Taysum, B., Fedorova, A. A., Korablev, O., Olsen, K. S.,. . . Lefevre, F. (2024). Evidence of rapid hydrogen chloride uptake on water ice in the atmosphere of Mars. Icarus, 411 , 115960.[5] Vandaele, A. C., Lopez-Moreno, J.-J., Patel, M. R., Bellucci, G., Daerden, F., Ristic, B., . . . others (2018). NOMAD, an integrated suite of three spectrometers for the ExoMars trace gas mission: Technical description, science objectives and expected performance. Space Science Reviews, 214 (5), 1–47.[6] Olsen, K. S., Fedorova, A. A., Kass, D. M., Kleinb¨ohl, A., Trokhimovskiy, A., Korablev, O. I., . . . others (2024). Relationships between HCl, H2O, aerosols, and temperature in the Martian atmosphere: 1. Climatological outlook. Journal of Geophysical Research: Planets, 129 (8), e2024JE008350[7] Faggi, S., Aoki, S., Liuzzi, G., Villanueva, G., Sagawa, H., Mumma, M. J., . . . Viscardy, S. (2025). Following the HCl cycle over three Martian seasons in Mars year 36. Journal of Geophysical Research: Planets, 130 (11), e2025JE009105.[8] Olsen, K., Fedorova, A., Kass, D., Kleinb¨ohl, A., Trokhimovskiy, A., Korablev, O., . . . others (2024). Relationships between HCl, H2O, aerosols, and temperature in the Martian atmosphere: 2. Quantitative correlations. Journal of Geophysical Research: Planets, 129 (8), e2024JE008351.

The science phase of the ExoMars Trace Gas Orbiter (TGO) mission began on 21st April 2018, and since then the NOMAD suite of 3 spectrometers [1] has acquired around 100 million spectra, primarily of the Martian atmosphere and surface. These cover ultraviolet-visible and infrared wavelengths with different observation geometries. The 3 spectrometers are:1) Solar Occultation (SO): 2.2-4.3 µm (2,300-4,600 cm-1), spectral resolution 0.1-0.23 cm-1 [2].2) Limb, Nadir and Occultation (LNO): 2.2-3.8 µm (2,600-4,600 cm-1), spectral resolution 0.15-0.28 cm-1 [2], operating primarily in nadir viewing mode.3) Ultraviolet-Visible (UVIS): 200-650 nm (15,000-50,000 cm-1), spectral resolution 1.2-1.7 nm [3], operating in solar occultation, nadir and limb viewing modes. Together, the spectrometers are able to map the vertical distributions and/or column densities (where appropriate) of many properties and constituents of the Martian atmosphere, including H2O [4] and HDO [5], CO [6], O3 [7], HCl [8], dust/aerosol particle size [9], CO2 and H2O clouds [10], CO2 temperature and pressure [11], dayglow [12] and nightglow [13] emissions, surface ice/frost [14], plus the reflectance properties of Phobos and Deimos [15]. Also, stringent detection limits can be placed on other gases that have not yet been detected, e.g. CH4 [16]. Calibrated NOMAD spectra and derived climatologies are available to the scientific community in multiple sources, for example: the ESA Planetary Science Archive, Europlanet’s VESPA portal, and many online authors’ repositories. Likewise, modelling tools (for example the NASA Goddard Planetary Spectrum Generator), calibration routines, observation planning information and nadir footprints exist online, are available in journal articles, or can be found on the NOMAD website at nomad.aeronomie.be. Work is ongoing to consolidate all the available datasets and tools, including python code to find and plot online datasets, forward-model the SO and LNO spectrometers, and to understand the instrument and associated uncertainties, which we will describe here. Also, documentation regarding recent calibration improvements will be highlighted and made available online for the community. References[1] Vandaele, A.C., et al; NOMAD, an integrated suite of three spectrometers for the ExoMars Trace Gas mission: technical description, science objectives and expected performance. (2018) Space Sc. Rev. 214, 80. https://doi.org/10.1007/s11214-018-0517-2[2] Liuzzi G., et al; Methane on Mars: New insights into the sensitivity of CH4 with the NOMAD/ExoMars spectrometer through its first in-flight calibration. (2019) Icarus 321, 671-690. https://doi.org/10.1016/j.icarus.2018.09.021[3] Willame, Y., et al; Calibration of the NOMAD-UVIS data. (2022) Planet. Space Sci., 218, 105504. https://doi.org/10.1016/j.pss.2022.105504[4] Hendrick, F., et al; New Climatology of Martian Water Vapor Column Abundance Derived from NOMAD LNO Nadir Observations Over Martian Years 34–38. (2026) J. Geophys. Res. Planets. https://doi.org/10.1029/2025JE009592 [5] Villanueva, G., et al; The deuterium isotopic ratio of water released from the Martian caps as measured with TGO/NOMAD. (2022) Geophys. Res. Lett., 49(12). https://doi.org/10.1029/2022GL098161[6] Modak, A., et al; Martian Atmospheric CO Vertical Profiles From NOMAD Observations During the First Year of TGO Operations. (2023) J. Geophys. Res. Planets. https://doi.org/10.1029/2022JE007282[7] Mason, J. P., et al; Climatology and Diurnal Variation of Ozone Column Abundances for 2.5 Mars Years as Measured by the NOMAD-UVIS Spectrometer. (2024) J. Geophys. Res. Planets. https://doi.org/10.1029/2023JE008270[8] Aoki S., et al; Annual appearance of hydrogen chloride on Mars and a striking similarity with the water vapor vertical distribution observed by TGO/NOMAD. (2021) Geophys. Res. Letters 48(11). https://doi.org/10.1029/2021gl092506[9] Flimon, Z., et al; Aerosol Climatology on Mars as Observed by NOMAD UVIS on ExoMars TGO in Journal of Geophysical Research: Planets. (2025) J. Geophys. Res. Planets. https://doi.org/10.1029/2024JE008303[10] Liuzzi, G., et al; First Detection and Thermal Characterization of Terminator CO2 Ice Clouds with ExoMars/NOMAD. (2021) Geophys. Res. Letters 48(2). https://doi.org/10.1029/2021gl095895[11] Trompet, L., et al; Carbon dioxide retrievals from NOMAD-SO on ESA’s ExoMars Trace Gas Orbiter and temperature profiles retrievals with the hydrostatic equilibrium equation. II. Temperature variabilities in the mesosphere at Mars terminator. (2023) J. Geophys. Res. Planets. https://doi.org/10.1029/2022JE007279[12] Soret, L., et al; The Martian oxygen green line dayglow: response to solar activity. (2025) Icarus. https://doi.org/10.1016/j.icarus.2025.116707[13] Gérard, J.-C., et al; Observation of the Mars O2 visible nightglow by the NOMAD spectrometer onboard the Trace Gas Orbiter. (2023) Nature Astron. https://doi.org/10.1038/s41550-023-02104-8[14] Valantinas, A., et al; Evidence for transient morning water frost deposits on the Tharsis volcanoes of Mars. (2024) Nature Geoscience. https://doi.org/10.1038/s41561-024-01457-7[15] Mason, J. P., et al; Ultraviolet and Visible Reflectance Spectra of Phobos and Deimos as Measured by the ExoMars-TGO/NOMAD-UVIS Spectrometer. (2023) J. Geophys. Res. Planets. https://doi.org/10.1029/2023JE008002[16] Knutsen, E.W., et al; Comprehensive Investigation of Mars Methane and Organics with ExoMars/NOMAD. (2021) Icarus 257. https://doi.org/10.1016/j.icarus.2020.1142

The SOIR (Solar Occultation in InfraRed) spectrometer onboard Venus Express (VEx) collected high-resolution solar occultation spectra of the Venusian atmosphere from 2006 to 2014. SOIR combines an echelle grating with an Acousto-Optic Tunable Filter (AOTF), the latter enabling the rapid selection of diffraction orders across the 2.2 to 4.3 microns spectral range [1]. Accurate characterisation of the AOTF transfer function (TF) is essential as the TF directly impacts the spectral calibration and the accuracy of the atmospheric retrievals. The SOIR AOTF TF was characterised in-flight using dedicated calibration observations of the Sun, called miniscans, during which the AOTF driving radio frequency was stepped across defined frequency intervals centred on deep solar Fraunhofer lines. Because these solar lines are significantly narrower than the AOTF bandwidth, they provide an effective probe of the instrument response function. Early calibration work used 42 miniscans and approximately 250 solar lines distributed across the spectral range to derive the AOTF’s tuning relation and bandpass [2]. A subsequent study introduced a more advanced reconstruction approach based on the combined analysis of multiple solar lines and demonstrated that the SOIR AOTF TF could be approximated using a sum of five sinc2 functions with frequency-dependent coefficients [3]. A later investigation extended the calibration analysis to nearly 300 miniscans available at the time [4]. By the end of the mission in 2014, however, the complete SOIR archive contained nearly 500 miniscans. Although the analytical multi-sinc2 model reproduces the main lobe structure of the AOTF TF, discrepancies remain, particularly in the sidelobes and in spectral regions affected by order overlap. In addition, the partial exploitation of the complete SOIR miniscan archive leaves open questions regarding the variability of the TF across the spectral domain, its long-term evolution throughout the mission lifetime, and potential instrumental dependencies not yet detectable in previous analyses. This work introduces a probabilistic machine learning framework for the SOIR AOTF TF characterisation, with a particular focus on Gaussian Processes (GPs). GPs provide a flexible non-parametric framework well suited to heterogeneous, medium-sized calibration datasets, while naturally incorporating uncertainty estimation. The GP covariance structure can be physically informed, while the existing analytical model may be incorporated as a prior mean function, ensuring the framework remains grounded in instrument physics [5]. The objective is to investigate whether GP-based modelling can improve reconstruction of the TF shape, especially in the sidelobe regions, while also enabling the exploration of dependencies on wavelength, instrumental temperature, and observation epoch. The ongoing study aims to extend the analysis to the complete SOIR miniscan archive acquired over the full operational lifetime of the instrument. Preliminary developments of the GP framework and data preparation pipeline are underway. Initial results from the first application of GP-based AOTF TF modelling to SOIR calibration data will be presented. [1] Nevejans, D., Neefs, E., van Ransbeeck, E., Berkenbosch, S., Clairquin, R., de Vos, L., Moelans, W., Glorieux, S., Baeke, A., Korablev, O., Vinogradov, I., Kalinnikov, Y., Bach, B., Dubois, J-P., and Villard, E., “Compact high-resolution spaceborne echelle grating spectrometer with acousto-optical tunable filter based order sorting for the infrared domain from 2.2 to 4.3 μm”, Applied Optics, vol. 45, no. 21, pp. 5191-5206, 2006.[2] Mahieux, A., Berkenbosch, S., Clairquin, R., Fussen, D., Mateshvili, N., Neefs, E., Nevejans, D., Ristic, B., Vandaele, A. C., Wilquet, V., Belyaev, D., Fedorova, A., Korablev, O., Villard, E., Montmessin, F., and Bertaux, J-L., “In-flight performance and calibration of SPICAV SOIR onboard Venus Express”, Applied Optics, vol. 47, no. 13, pp. 2252-2265, 2008.[3] Mahieux, A., Wilquet, V., Drummond, R., Belyaev, D., Federova, A., and Vandaele, A. C., “A new method for determining the transfer function of an Acousto optical tunable filter”, Optics Express, vol. 17, no. 3, p. 2005, 2009.[4] Mahieux, A., “Inversion of infrared spectra recorded by the SOIR instrument on board Venus Express”, PhD Thesis, BIRA-IASB & ULB, Belgium, 2011.[5] Rasmussen, C. E. and Williams, C. K. I., Gaussian Processes for Machine Learning, MIT Press, 2006.