Solar system

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.

Abstract:

The radiative heat balance of Uranus has long been a mystery amongst the solar system giant planets. Jupiter, Saturn and Neptune all emit much more power thermally (Pout) than they absorb from the Sun (Pin) with Pout/Pin having values of 1.7 to 2.6. This shows that all three planets retain a considerable amount of heat left over from formation, which they are still slowly radiating away into space. In stark contrast, Uranus appears to be unexpectedly cold. Measurements made by Voyager-2 determined a radiative heat balance ratio of only Pout/Pin = 1.06 ± 0.08 (Pearl et al. 1990), which is consistent (to within error) with Uranus being in thermal equilibrium with the Sun and thus, perhaps, having no heat of formation left over at all. Meanwhile, Voyager-2 determined a radiative heat balance ratio for Neptune of Pout/Pin = 2.61 ± 0.28 (Pearl and Conrath, 1991), which is the largest ratio determined for any of the giant planets.How can the radiative heat balance ratios of Uranus and Neptune, the solar system’s ‘Ice Giants’ be so different? And is Uranus really in thermal equilibrium with the Sun, with no internal heat of formation left over? To answer this last question, we have performed a modelling study (Irwin et al., 2025) using our NEMESIS radiative transfer tool (Irwin et al., 2008) and a newly developed ‘holistic’ atmospheric model of the aerosol structure in Uranus’s atmosphere, based upon observations made by HST/STIS, Gemini/NIFS and IRTF/SpeX from 2000 – 2009 (Irwin et al., 2022). Taking our fitted aerosol structure and extrapolating our calculations to all wavelengths, we have made a new estimate of the bolometric geometric albedo of Uranus during the period 2002 – 2009 of p* = 0.249. The bolometric geometric albedo is the fraction of sunlight reflected by the planet back towards an observer in line with the Sun, but to determine heat balance we need to calculate the bolometric Bond Albedo, which is the fraction of sunlight incident on the planet that is scattered into all directions. With our holistic aerosol model and NEMESIS, we can calculate the appearance of Uranus to an observer at any phase angle from the Sun, and integrating these modelled curves over all phase angles we can calculate the phase integral, q, which relates the geometric albedo, p, to the Bond albedo, A, through the relation A = pq.From this modelling we determine a bolometric (i.e., integrated over all wavelengths) phase integral of 𝑞∗ = 1.36, and thus a bolometric Bond albedo of 𝐴∗ = 0.338 for the period 2002 – 2009. However, to determine the overall radiative heat balance of Uranus, we first need to account for the seasonal variation in 𝐴∗, which changes significantly during Uranus’s year due to the formation of a polar ‘hood’ of haze over the summer pole, which becomes thicker and more observable near the solstices. In addition, in terms of energy balance, we also need to account for the fact that the incident sunlight at Uranus varies significantly during its eccentric (e = 0.046) orbit about the Sun by ±10%. Also, since Uranus is significantly oblate and has high polar inclination, there is a small, but significant difference in its projected area towards the Sun between solstice and equinox, which affects the total power of sunlight received by the planet.To estimate the orbital-average bolometric Bond albedo and radiative heat balance we used a simple seasonal model, developed by Irwin et al. (2024) to be consistent with the disc-integrated blue and green magnitude data from the Lowell Observatory from 1950 – 2016 (Lockwood, 2019). Taking all hood thickness/visibility, distance and projected area effects into account, we model how Uranus’s reflectivity and heat budget vary during its orbit and determine a new orbital-mean average value for the bolometric Bond albedo of 𝐴∗ = 0.349 ± 0.016 and estimate the orbital-average mean absorbed solar flux to be  𝑃in = 0.604 ± 0.027 W m−2. Assuming the outgoing thermal flux to be 𝑃out = 0.693 ± 0.013 W m−2, previously determined from Voyager 2 observations, we arrive at a new estimate of Uranus’s average heat flux budget of Pout/Pin = 1.15 ± 0.06. We find, however, that there is considerable variation of the radiative heat balance with time due mainly to Uranus’s orbital eccentricity, which leads Pout/Pin to vary from 1.03 near perihelion, to 1.24 near aphelion. We conclude that although Pout/Pin is still considerably smaller than for the other giant planets, Uranus is not in thermal equilibrium with the Sun.References. Irwin et al. (2008) DOI:10.1016/j.jqsrt.2007.11.006; Irwin et al. (2022) DOI: 10.1029/2022JE007189; Irwin et al. (2024) DOI: 10.1093/mnras/stad3761;Irwin et al. (2025) DOI: 10.48550/arXiv.2502.18971; Lockwood (2019) DOI: 10.1016/j.icarus.2019.01.024; Pearl et al. (1990) DOI:  10.1016/0019-1035(90)90155-3; Pearl and Conrath (1991) DOI: 10.1029/91JA01087; Wenkert (2023) DOI: 10.17189/T2R8-RK88

Abstract:

Introduction: The Lucy mission's first asteroid flyby provided a unique and unexpected opportunity to study a binary asteroid system up close. Originally expected to encounter a single target, Dinkinesh, the discovery of its small, tidally locked moon, Selam, introduced additional opportunity and complexity to the interpreting flyby observations [1]. We present thermal modelling of the binary system, quantifying how the presence of Selam influenced radiance measurements and indicating its possible impact on thermal inertia estimates. Thermal inertia (TI) offers insight into surface properties such as grain size and regolith structure. Determining the TI of Dinkinesh adds to our understanding of small S-type asteroids and enables comparison within a binary, potentially revealing differences driven by tidal effects or surface evolution.Methods: We modelled the flyby geometry and instrument measurements using the new TESBY (Thermal Emissions Spectrometer flyBY) module of TEMPEST (the Thermophysical Equilibrium Model for Planetary Environment Surface Temperatures) [2] to simulate the thermal radiance of both bodies and assess their combined effect on interpretation of data from the Lucy Thermal Emission Spectrometer (L’TES) instrument [3].The Thermal Model: Dinkinesh and its satellite, Selam, were modelled in TEMPEST. A stereo-photogrammetric shape model is available for the primary target – Dinkinesh [4], with ~2 m lateral and ~0.5 m vertical resolution, covering ~60% of the surface. This shape model was downsampled to a dimensionally accurate model with 1266 facets with a resolution of ~35 m. A sphere of representative diameter (230 m [1]) was used for the satellite Selam.Figure 1: TESBY visualization of flyby. Global view of the flyby trajectory (left), and the FOV of the instrument (centre), with corresponding L’LORRI image for comparison [1] taken 0.54 minutes before closest approach (right). Input is the TEMPEST [5] result for the shape model of Dinkinesh, and representative diameter sphere for Selam. Parameters used: solar distance = 2.19 AU, rotation periods = 3.74 hours (Dinkinesh) and 52.7 hours (Selam) [1] thermal inertia (provisional) = 40 J m-2 s-1/2 K-1, geometric albedo = 0.27Flyby geometry: Building on the TEMPEST framework, the TESBY module is given the geometry information for the flyby and the thermal data from TEMPEST. Based on the 7.3 mrad Field-of-View (FOV) of the L’TES instrument [3] TESBY produces simulated radiance measurements by computing a weighted sum of blackbody curves from each visible facet, based on its temperature, projected area, and emission angle. Matching these modelled radiances to the instrument data allows us to fit for the thermal inertia of the asteroid. A complicating factor in this study is that the sensitivity of L’TES is not uniform across its FOV, including this effect in the model is the subject of ongoing work.Figure 2: Preliminary modelled radiance results (blue line) compared to L’TES observation (red) using the same model settings as Fig. 1. Scaled radiances (dotted line) are also provided (see main text for more information).Results: An example of the currently predicted model radiance is given by Figure 2. As it shows, there is a notable offset between the predicted and observed radiances. Accounting for the position of the targets in the L’TES FOV is expected to resolve the observed discrepancy in absolute radiance levels. However, as the scaled model shows, the predicted radiances are able to capture the shape of the L’TES radiance.We find that due to the slower rotation rate of Selam, the maximum surface temperatures on the satellite can be as much as 25 K higher than those on Dinkinesh (Fig. 1), meaning that despite the small size (lobe diameter of only 230 m, compared with 790 m for Dinkinesh [1]), the contribution to measured radiance is significant. This effect is highlighted by investigation of the integrated radiances of the targets throughout the flyby (Fig. 3), where the entry and exit of Selam within the FOV is visible, as well as the dip in integrated radiance while Selam is partially eclipsed by Dinkinesh. Our results demonstrate the importance of considering the full system in flyby analysis, informing techniques for similar encounters in the future. This work highlights how the thermal signature of even a small secondary body can significantly impact observations, shaping our understanding of asteroid surface properties and thermal environments.Continued analysis will focus on the use of TEMPEST/TESBY to constrain the thermal inertia of this binary asteroid from L’TES flyby observations.  Figure 3: Variation in integrated wavelength for Dinkinesh (target, blue), Selam (satellite, red) and combined effect (green). Radiances were integrated over the 200–1500 cm⁻¹ spectral range. The results show that despite its small size, Selam makes a significant difference to the spectral radiance, particularly at shorter wavelengths. The dip in combined spectral radiance at observations 3315-3320 is due to Selam being eclipsed by Dinkinesh.The thermal model code 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] Levison, H.F., Marchi, S., Noll, K.S. et al. A contact binary satellite of the asteroid (152830) Dinkinesh. Nature 629, 1015–1020 (2024).[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] Christensen, P. R., et al. The Lucy Thermal Emission Spectrometer (L’TES) Instrument, Space Sci. Rev. (2023)[4] Preusker, F. et al. (2024). Shape Model of Asteroid (152830) Dinkinesh from Photogrammetric Analysis of Lucy’s Frame Camera L’LORRI. 55th Lunar and Planetary Science Conference, Abstract #1903.[5] Lyster, D., Howett, C., & Penn, J. (2025). TEMPEST: A Modular Thermophysical Model for Airless Bodies with Support for Surface Roughness and Non-Periodic Heating. Submitted to EPSC Abstracts, 2025

Abstract:

. IntroductionPerhaps one of the most fascinating ice-covered moons in our solar system is the Galilean satellite Europa. The successful launch of Europa Clipper has motivated the re-evaluation of our current knowledge of the Jovian moon -- specifically thermal measurements of the moon's surface, which may contain information about recent geologic activity. After the discovery of active plumes on Enceladus [1], similar phenomena were searched for on Europa [2]. While evidence of surface alteration -- such as troughs, ridges, chaos terrain, and the lack of prevalent craters -- indicate ongoing activity and a relatively young surface [3], the presence of plumes is still being debated. While no endogenic thermal anomalies have yet been observed on Europa's surface [4], we re-assess the thermal IR data from Galileo Orbiter's photopolarimeter-radiometer instrument (PPR) [5]. We perform a thermal analysis of the surface properties of Europa, including mapping the thermal inertia and albedo similar to what was done by Rathbun et al. [4], with a goal of extending thermal surface mapping beyond the previous 20% surface coverage. We also perform a sensitivity study of PPR in hotspot detection by determining the minimum detectable hotspot temperature across the surface of the moon and compare our results to previous work. 2. Data AnalysisWe use 29 PPR radiometry datasets taken during various orbits ranging from November 1996 to November 1999. Both narrow band and open filters were used, with a total wavelength range of 0.3-110 μm. We divide the surface into 3°x3° longitude/latitude grid cells and determine each cell's temperature at a given local time to produce diurnal temperature curves. To determine the thermal inertia and albedo, we fit a thermophysical model to each cell's diurnal curve using the Thermophysical Body Model Simulation Script (TEMPEST) [6] as our modelling tool. The best-fit diurnal curve is chosen by minimizing the reduced chi-squared of the model fit, while all data with χred2