Methane precipitation in ice giant atmospheres

Astronomy & Astrophysics EDP Sciences (2025)

Authors:

D Toledo, Pascal Rannou, Patrick Irwin, Bruno de Batz de Trenquelléon, Michael Roman, Victor Apestigue, Ignacio Arruego, Margarita Yela

Abstract:

<jats:p>Voyager-2 radio occultation measurements have revealed changes in the atmospheric refractivity within a 2-4 km layer near the 1.2-bar level in Uranus and the 1.6-bar level in Neptune. These changes were attributed to the presence of a methane cloud, consistent with the observation that methane concentration decreases with altitude above these levels, closely following the saturation vapor pressure. However, no clear spectral signatures of such a cloud have been detected thus far in the spectra acquired from both planets. We examine methane cloud properties in the atmospheres of the ice giants, including vertical ice distribution, droplet radius, precipitation rates, timescales, and total opacity, employing microphysical simulations under different scenarios. We used a one-dimensional (1D) cloud microphysical model to simulate the formation of methane clouds in the ice giants. The simulations include the processes of nucleation, condensation, coagulation, evaporation, and precipitation, with vertical mixing simulated using an eddy-diffusion profile (K_eddy). Our simulations show cloud bases close to 1.24 bars in Uranus and 1.64 bars in Neptune, with droplets up to 100 μm causing high settling velocities and precipitation rates (∼370 mm per Earth year). The high settling velocities limit the total cloud opacity, yielding values at 0.8 μm of ∼0.19 for Uranus and ∼0.35 for Neptune, using K_ eddy = 0.5 m^2 s^-1 and a deep methane mole fraction (μ_CH_4) of 0.04. In addition, lower K_ eddy or μ_CH_4 values result in smaller opacities. Methane supersaturation is promptly removed by condensation, controlling the decline in μ_CH_4 with altitude in the troposphere. However, the high settling velocities prevent the formation of a permanent thick cloud. Stratospheric hazes made of ethane or acetylene ice are expected to evaporate completely before reaching the methane condensation level. Since hazes are required for methane heterogeneous nucleation, this suggests either a change in the solid phase properties of the haze particles, inhibiting evaporation, or the presence of photochemical hazes.</jats:p>

Clouds and Ammonia in the Atmospheres of Jupiter and Saturn Determined From a Band‐Depth Analysis of VLT/MUSE Observations

Journal of Geophysical Research E: Planets American Geophysical Union 130:1 (2025)

Authors:

Patrick GJ Irwin, Steven M Hill, Leigh N Fletcher, Charlotte Alexander, John H Rogers

Lunar thermal mapper ground testing calibration data

University of Oxford (2025)

Abstract:

Ground test data from the Lunar Thermal Mapper instrument. Described in Bowles et al. 2025 submitted to JGR Planets.

Small Satellites for Lunar Optical and Thermal Imaging.

Curran Associates (2025) 846-855

Authors:

Steve Eckersley, Nicolò Bernardini, Jonathan Friend, Gavin Johnston, Abigail Harvey, Steven Knox, Alex Da Silva Curiel, Ben Hooper, Martin Sweeting, Neil Bowles, Eloy De Lera Acedo, David Bacon, Will Grainger

archNEMESIS: An Open-Source Python Package for Analysis of Planetary Atmospheric Spectra

Journal of Open Research Software Ubiquity Press 13:1 (2025) 10

Authors:

Juan Alday, Joseph Penn, Patrick Irwin, Jonathon Mason, Jingxuan Yang, Jack Dobinson

Abstract:

ArchNEMESIS is an open-source Python package developed for the analysis of remote sensing spectroscopic observations of planetary atmospheres. It is based on the widely used NEMESIS radiative transfer and retrieval tool, which has been extensively used for the investigation of a wide variety of planetary environments. The main goal of archNEMESIS is to provide the capabilities of its Fortran-based predecessor, keeping or exceeding the efficiency in the calculations, and benefitting from the advantages Python tools provide in terms of usability and portability. ArchNEMESIS enables users to compute synthetic spectra for a wide variety of planetary atmospheres, supporting multiple spectral ranges, viewing geometries (e.g., nadir, limb, and solar occultation), and radiative transfer scenarios, including multiple scattering. Furthermore, it provides tools to fit observed spectra and retrieve atmospheric and surface parameters using both optimal estimation and nested sampling retrieval schemes. The code, stored in a public GitHub repository under a GPL-v3.0 license, is accompanied by detailed documentation available at https://archnemesis.readthedocs.io/.