Solar system

Abstract:

Larger-than-Earth exoplanets are sculpted by strong stellar irradiation, but it is unknown whence they originate. Two propositions are that they formed with rocky interiors and hydrogen-rich envelopes (‘gas-dwarfs’), or with bulk compositions rich in water-ices (‘water-worlds’) . Multiple observations of super-Earth L 98-59 d have revealed its low bulk-density, consistent with substantial volatile content alongside a rocky/metallic interior, and recent JWST spectroscopy evidences a high mean molecular weight atmosphere. Its density and composition make it a waymarker for disentangling the processes which separate super-Earths and sub-Neptunes across geological timescales. We simulate the possible pathways for L 98-59 d from birth up to the present day using a comprehensive evolutionary modelling framework. Emerging from our calculations is a novel self-limiting mechanism between radiative cooling, tidal heating, and mantle rheology, which we term the 'radiation-tide-rheology feedback'. Coupled numerical modelling yields self-limiting tidal heating estimates that are up to two orders of magnitude lower than previous calculations, and yet are still large enough to enable the extension of primordial magma oceans to Gyr timescales. Our analysis indicates that the planet formed with a large amount (>1.8 mass%) of sulfur and hydrogen, and a chemically-reducing mantle; inconsistent with both the canonical gas-dwarf and water-world scenarios. A thick atmosphere and tidal heating sustain a permanent deep magma ocean, allowing the dissolution and retention of volatiles within its mantle. Transmission features can be explained by in-situ photochemical production of SO2 in a high-molecular weight H2-H2S background. These results subvert the emerging gas-dwarf vs. water-world dichotomy of small planet categorisation, inviting a more nuanced classification framework. We show that interactions between planetary interiors and atmospheres shape their observable characteristics over billions of years.

Abstract:

Introduction: Understanding surface temperatures on airless planetary bodies is crucial for interpreting thermal observations and constraining surface properties. We present TEMPEST (Thermal Evolution Model for Planetary Environment Surface Temperatures), a modular, open-source Python model that simulates diurnal and non-periodic thermal evolution on irregular bodies. Unlike traditional 1D periodic solvers, TEMPEST handles transient heating events such as eclipses, non-synchronous rotations such as tumbling asteroids, and seasonal variations. Key capabilities include surface roughness modelling via hemispherical craters, multiple thermal conduction schemes, and modular scattering using lookup tables (LUTs). TEMPEST has been used to analyse data from the Lucy mission and has been validated against the well-established Spencer 1D thermal model, thermprojrs [1].Figure 1: TEMPEST allows the user to select a facet to view any of its time varying properties including insolation, temperature and radiance. The diurnal temperature curves (right) are those of the corresponding outlined facets selected by the user in the interactive pane (left).Methods: TEMPEST calculates surface temperatures by solving a surface energy balance that includes solar flux, thermal emission, vertical heat conduction, and (optionally) radiative self-heating. Figure 1 shows the user interface once the model has completed a run. Key components include:Thermal solvers: Includes a standard 1D periodic conduction scheme influenced by the widely used thermprojrs [1] and a non-equilibrium solver, designed for better performance and stability in non-periodic cases. Scattering treatments: Utilises precomputed LUTs for various scattering laws (e.g., Lambertian, Lommel-Seeliger). This structure allows users to incorporate empirical bi-directional reflectance function (BRDF) data (e.g., from goniometer measurements of lunar regolith) or test the impact of different scattering assumptions, which can be particularly important for investigating the temperature of shadowed regions, as shown in Figure 2. The modularity also facilitates user modification for specific research needs. Surface roughness: Implemented via hemispherical sub-facet craters with adjustable rim angle to match roughness with a specified RMS slope angle. Non-periodic and time-dependent conditions: Supports time-dependent boundary conditions, including periodic scenarios such as eclipses and seasonal variations due to orbital eccentricity, as well as non-periodic cases including tumbling rotation, endogenic heating, and, or other user-defined transient heating scenarios. Designed for efficient parallel execution, the model runs effectively on multi-core personal computers and can efficiently simulate shape models with tens of thousands of facets. It has also been deployed on high-performance computing clusters for larger-scale models on the order of 1 million facets. Input configuration files are simple and flexible, allowing integration into larger analysis pipelines.Figure 2: An example insolation curve from a 1666 facet model of the bilobate comet 67P. The effects of scattered light can be seen either side of the main peak, this is particularly important for permanently shadowed regions. The selected facet is shown with a blue outline; sunlight direction is shown with a yellow arrow.Results: We validated TEMPEST by comparing temperature time series with Spencer’s 1D model thermprojrs [1] under idealised conditions, showing consistent results – see Figure 3. Applied to high-resolution shape models of 67P/Churyumov-Gerasimenko and 101955 Bennu, the model produces detailed temperature maps that reflect the significant influence of self-shadowing and local geometry, quantifying, for example, the temperature reduction in shadowed craters. Non-periodic simulations have been run to explore rotational transitions and eclipse effects, enabling new modes of comparison with observational datasets. The modular scattering and roughness components offer a powerful way to assess how sub-resolution scale parameters impact apparent thermal inertia and surface radiative behaviour. TEMPEST is already being used to interpret thermal data from recent missions, including Lucy, and can be adapted for upcoming datasets from targets like those of Comet Interceptor and Europa Clipper.Figure 3: TEMPEST shows good agreement with ‘industry standard’ thermophysical models in 1 dimension.TEMPEST is open-source and available at:github.com/duncanLyster/TEMPEST/Acknowledgement: This work was made possible by support from the UK Science and Technology Facilities Council. References:[1] Spencer, J.R., Lebofsky, L.A., and Sykes, M.V., 1989. Systematic biases in radiometric diameter determinations. Icarus, 78(2), pp.337-354.[2] Lyster, D., Howett, C., & Penn, J. (2024). Predicting surface temperatures on airless bodies: An open-source Python tool. EPSC Abstracts, 18, EPSC2024-1121.[3] Lyster, D.G., Howett, C.J.A., Spencer, J.R., Emery, J.P., Byron, B., et al. (2025). Thermal Modelling of the Flyby of Binary Main Belt Asteroid (152830) Dinkinesh by NASA’s Lucy Mission. Submitted to EPSC Abstracts, 2025.

Abstract:

We present observations and analysis of Neptune’s atmosphere from JWST, providing new constraints on hydrocarbon abundances, cloud properties, and temperature structure across the planet’s disk.  JWST observed Neptune in June 2023 (program1249) as part of the Solar System Guaranteed Time Observations (GTO). Integral field spectroscopy (IFS) with the Near-Infrared Spectrograph (NIRSpec) and the Mid-Infrared Instrument/Medium Resolution Spectrometer (MIRI/MRS) were combined to provide nearly simultaneous and continuous spatial and spectral data between 1.66 and 28.70 microns.We show how wavelengths sensitive to the atmospheric temperatures reveal a structure consistent with Voyager [1] and ground-based imaging [2,3], with a sharply defined warm polar vortex. In contrast, wavelengths sensitive to stratospheric hydrocarbons (namely acetylene and ethane) show a marked enhancement in the northern winter hemisphere.Finally, we examine the distribution and vertical structure of clouds in context of the temperature and chemical structure. Scattered light in NIRSpec observations indicate variable discrete clouds extend to pressures of roughly 50 mbar at the northernmost latitudes and south pole. [1] Conrath, B. J., F. M. Flasar, and P. J. Gierasch. "Thermal structure and dynamics of Neptune's atmosphere from Voyager measurements." Journal of Geophysical Research: Space Physics 96, no. S01 (1991): 18931-18939.[2] Fletcher, Leigh N., Imke de Pater, Glenn S. Orton, Heidi B. Hammel, Michael L. Sitko, and Patrick GJ Irwin. "Neptune at summer solstice: zonal mean temperatures from ground-based observations, 2003–2007." Icarus 231 (2014): 146-167.[3] Roman, Michael T., Leigh N. Fletcher, Glenn S. Orton, Thomas K. Greathouse, Julianne I. Moses, Naomi Rowe-Gurney, Patrick GJ Irwin et al. "Subseasonal variation in Neptune’s mid-infrared emission." The Planetary Science Journal 3, no. 4 (2022): 78.

Abstract:

Introduction: Due to Uranus’ weak thermal radiance, the thermal and compositional structures of its atmosphere have remained poorly characterised. Here, using the unprecedented sensitivity of JWST's MIRI and NIRSpec instruments, we present an analysis of Uranus' spatially resolved spectrum spanning the near- and mid-infrared, revealing how temperatures, composition, and clouds vary across the planet's northern hemisphere.Observations: JWST observed Uranus on 8--9 January 2023 (program1248) as part of the Solar System Guaranteed Time Observations (GTO). Integral field spectroscopy (IFS) with the Near-Infrared Spectrograph (NIRSpec) and the Mid-Infrared Instrument/Medium Resolution Spectrometer (MIRI/MRS) were combined to provide nearly simultaneous and continuous spatial and spectral data between 1.66 and 28.70 microns.Temperatures: The nearly continuous spectral coverage offered by the combination of NIRSpec and MIRI provide constraints on the temperature structure from the stratosphere down to several bars. The average temperature-pressure vertical profile is largely consistent with that determined from Spitzer [1], but the spatially resolved JWST reveal how these temperatures vary with latitude in the stratosphere and cloud layer for the first time [2]. They also suggest the possibility of a sub-adiabatic cloud layer.Chemistry: Our radiative transfer analysis of MIRI-MRS spectra 1) provide new constraints on minor species in Uranus’ stratosphere and 2) reveals how various hydrocarbons vary as a function of latitude. The observed distributions are indicative of a combination of seasonal photochemistry [3] and dynamical processes, as we will briefly discuss.Clouds and hazes: Finally, we briefly examine the vertical cloud structure and its latitudinal variation as sensed by NIRSpec data. The data reveal the opacity of Uranus clouds and hazes spanning the transition from scattered sunlight to thermal emission for the first time. The overall vertical structure suggested by these new data largely agrees with that of prior work [3,4,5], but a comparison between observed and model spectra reveal interesting discrepancies and possibly a need for additional sources of opacity. [1] Orton, G.S., Fletcher, L.N., Moses, J.I., Mainzer, A.K., Hines, D., Hammel, H.B., Martin-Torres, F.J., Burgdorf, M., Merlet, C., Line, M.R.: Mid-infrared spectroscopy of uranus from the spitzer infrared spectrometer: 1. determination of the mean temperature structure of the upper troposphere and stratosphere. Icarus 243, 494–513 (2014)[2] Roman, M.T., Fletcher, L.N., Orton, G.S., Rowe-Gurney, N., Irwin, P.G.: Uranus in northern midspring: persistent atmospheric temperatures and circulations inferred from thermal imaging. The Astronomical Journal 159(2), 45 (2020)[3] Moses, J.I., Fletcher, L.N., Greathouse, T.K., Orton, G.S., Hue, V.: Seasonal stratospheric photochemistry on uranus and neptune. Icarus 307, 124–145 (2018)[4] Sromovsky, L.A., Karkoschka, E., Fry, P.M., Pater, I., Hammel, H.B.: The methane distribution and polar brightening on uranus based on hst/stis, keck-nirc2, and irtf/spex observations through 2015. Icarus 317, 266–306 (2019)189[5] Irwin, P.G., Teanby, N.A., Fletcher, L.N., Toledo, D., Orton, G.S., Wong, M.H.,Roman, M.T., Perez-Hoyos, S., James, A., Dobinson, J.: Hazy blue worlds:A holistic aerosol model for uranus and neptune, including dark spots[6] Roman, M.T., Banfield, D., Gierasch, P.J.: Aerosols and methane in the ice giant atmospheres inferred from spatially resolved, near-infrared spectra: I. uranus, 2001–2007. Icarus 310, 54–76 (2018)

Abstract:

Titan’s entire stratosphere is in superrotation (Flasar et al. 2005) and appears to rotate about an axis offset from its solid body rotation axis by around 4o (Achterberg et al. 2008). The stratospheric tilt axis has been estimated previously through temperature measurements (Achterberg et al. 2011; 2008), composition retrievals (Sharkey et al. 2020; Teanby 2010), and by analysis of stratospheric haze (Kutsop et al. 2022; Roman et al. 2009; Snell and Banfield 2024; Vashist et al. 2023) and a polar cloud (West et al. 2016). Despite this, the mechanism causing the tilt is not well understood. This challenge is further heightened as Titan General Circulation Models (GCMs) are yet to resolve a tilt consistent with observations (e.g., Lombardo and Lora (2023a; 2023b)).Understanding the cause of Titan’s stratospheric tilt may provide insight into the underlying dynamics that drive superrotation in Titan’s atmosphere and the behaviour of superrotating atmospheres in general. Furthermore, due to the strength of Titan’s zonal winds, the offset of the stratospheric rotation axis may have a significant effect on the atmospheric descent of the upcoming Dragonfly mission to Titan. Thus, improved constraints on the tilt axis may better inform the landing site calculations for Dragonfly.We determine the evolution of Titan’s stratospheric tilt axis over 13 years (Ls = 293—93o), which spans almost half a Titan year. The tilt was determined by inspecting zonal symmetry in the (i) thermal and (ii) composition structure of Titan’s stratosphere. These two independent methods probe different latitude regions. We use infrared observations acquired by the Composite Infrared Spectrometer (CIRS) (Flasar et al. 2004; Jennings et al. 2017; Nixon et al. 2019) instrument onboard the Cassini spacecraft, which toured the Saturn system from 2004 to 2017. We use nadir CIRS observations acquired at a low apodised spectral resolution (FWHM∼13.5–15.5 cm−1). This data set provides excellent spatial coverage of Titan’s middle atmosphere throughout the Cassini mission and achieves the best horizontal spatial resolution of any of the CIRS observations. Despite the subtle and often blended spectral features in these data, Wright et al. (2024) show that they can be reliably forward modelled. Vertical profiles of temperature and gas volume mixing ratios (VMRs) are estimated from CIRS FP3/4 spectra using the Non-linear Optimal Estimator for MultivariatE Spectral AnalySIS (NEMESIS) radiative transfer and retrieval code (Irwin et al. 2008). The observations probe pressure levels of ~10—10-3 mbar in Titan’s atmosphere, with peak contributions at around 1 mbar. These data enable us to reveal Titan’s stratospheric thermal and composition structure in the highest meridional resolution to date and facilitate an independent study of the tilt offset of Titan’s stratosphere.We find that the tilt axis in the mid-latitudes (from (i)) and the equatorial region (from (ii)) are in good agreement, which supports the theory that Titan’s entire stratosphere is tilted relative to its solid body (Achterberg et al. 2008). In addition to this, we present the best evidence yet that the pointing direction of Titan’s stratospheric tilt axis is constant in the inertial reference frame (Wright et al. in press), consistent with previous studies (Achterberg et al. 2011; Kutsop et al. 2022; Sharkey et al. 2020; Snell and Banfield 2024). The tilt azimuth is determined to be 121± 7o West of the sub-solar point at Titan’s northern spring equinox (Ls = 0o). Put another way, the pointing direction of the tilt axis would appear constant to an observer looking down on the Solar System.In addition, we present new evidence that the magnitude of Titan’s stratospheric tilt axis may have a seasonal dependence, oscillating between values of approximately 2o to 10o with a period similar in length to half a Titan year. If this pattern is real, it suggests that the tilt of Titan’s stratosphere is impacted by seasonal forcing, even though the direction of the tilt remains constant.Fig 1: Schematic showing the direction of Titan’s stratospheric tilt axis from Wright et al. (in press). Titan and Saturn are shown at some example times in their orbit. The tilt direction is determined to be approximately constant in the inertial reference frame, that is, fixed with respect to the Titan-Sun vector at northern spring equinox (Ls = 0◦). The approximate size of the tilt magnitude, β, is indicated by font size. References:Achterberg, R. K., et al. 2008. Icarus 197 (2): 549–55. https://doi.org/10.1016/j.icarus.2008.05.014.Achterberg, R. K., et al. 2011. Icarus 211 (1): 686–98. https://doi.org/10.1016/j.icarus.2010.08.009.Flasar, F. M., et al. 2005. Science 308 (5724): 975–78. https://doi.org/10.1126/science.1111150.Flasar, F. M., et al. 2004. Space Science Reviews 115 (1–4): 169–297. https://doi.org/10.1007/s11214-004-1454-9.Irwin, P.G.J., et al. 2008. Journal of Quantitative Spectroscopy and Radiative Transfer 109 (6): 1136–50. https://doi.org/10.1016/j.jqsrt.2007.11.006.Jennings, D. E., et al. 2017. Applied Optics 56 (18): 5274. https://doi.org/10.1364/AO.56.005274.Kutsop, N. W., et al. 2022. The Planetary Science Journal 3 (5): 114. https://doi.org/10.3847/PSJ/ac582d.Lombardo, N. A., and J. M. Lora. 2023a. Journal of Geophysical Research: Planets 128 (12): e2023JE008061. https://doi.org/10.1029/2023JE008061.Lombardo, N. A., and Juan M. Lora. 2023b. Icarus 390 (January):115291. https://doi.org/10.1016/j.icarus.2022.115291.Nixon, C. A., et al. 2019. The Astrophysical Journal Supplement Series 244 (1): 14. https://doi.org/10.3847/1538-4365/ab3799.Roman, M. T., et al. 2009. Icarus 203 (1): 242–49. https://doi.org/10.1016/j.icarus.2009.04.021.Sharkey, J., et al. 2020. Icarus 337 (February):113441. https://doi.org/10.1016/j.icarus.2019.113441.Snell, C., and D. Banfield. 2024. The Planetary Science Journal 5 (1): 12. https://doi.org/10.3847/PSJ/ad0bec.Teanby, N. A. 2010. Faraday Discussions 147:51. https://doi.org/10.1039/c001690j.Vashist, Aadvik S, et al. 2023. The Planetary Science Journal 4 (6): 118. https://doi.org/10.3847/PSJ/acdd05.West, R. A., et al. 2016. Icarus 270 (May):399–408. https://doi.org/10.1016/j.icarus.2014.11.038.Wright, L., et al. 2024. Experimental Astronomy 57 (2): 15. https://doi.org/10.1007/s10686-024-09934-y.Wright, L., et al. in press. The Planetary Science Journal. https://doi.org/10.3847/PSJ/adcab3.