Prof. Patrick Irwin

Abstract:

The origin of the red colouration in Jupiter's Great Red Spot (GRS) is a long-standing question in planetary science. While several candidate chromophores have been proposed, no clear conclusions have been reached regarding its nature, evolution, or relationship to atmospheric dynamics. In this work, we perform microphysical simulations of the reddish haze over the GRS and quantify the production rates and timescales required to sustain it. Matching the previously reported chromophore column mass and effective radius in the GRS requires column-integrated injection fluxes in the range 1×10⁻¹²–7×10⁻¹² kg m⁻² s⁻¹, under low upwelling velocities in the upper troposphere (v<inf>trop</inf>≲1.5×10⁻⁴ m s⁻¹) and particle charges of at least 20 electrons/μm. Such rates exceed the mass flux that standard photochemical models of Jupiter currently supply via NH<inf>3</inf>–C<inf>2</inf>H<inf>2</inf> photochemistry at 0.1–0.2 bar, the most popular chromophore pathway in recent literature. We find a lower limit of 7 years on the haze formation time. We also assess commonly used size and vertical distribution parameterisations for the chromophore haze, finding that eddy diffusion prevents the long-term confinement of a thin layer and that the extinction is dominated by particles that can be represented by a single log-normal size distribution.

Abstract:

Abstract Previous analysis of Neptune’s atmosphere using near-infrared Gemini/NIFS observations found the strongest spectral signature of hydrogen sulphide (H2S) to be at the planet’s south pole. Conversely, analysis of microwave observations with ALMA in 2019 suggested a distribution of H2S that peaks in the midlatitudes and is strongly depleted towards the pole. We analyse near-infrared observations from VLT-SINFONI in 2018 and fit a parametrized cloud model to the data using nested sampling. By prescribing a latitudinally-varying methane (CH4) profile previously derived from visible light observations, we find general agreement with the microwave analysis, with an enhancement of H2S by a factor of ∼4 at the southern midlatitudes compared to polar latitudes. The stronger spectral signature at the pole is explained with a deeper cloud top, resulting in a higher cloud-top H2S column abundance in this region. Our results are indicative of deep upwelling at the midlatitudes, with downwelling at the pole and possibly near the equator.

Abstract:

The extreme conditions in Venus’s lower atmosphere make robust calibration of in situ observations challenging. Consequently, measurements from past entry probes provided mixed evidence regarding the existence of a near-surface particulate layer (NSPL). Although the Venera 11 (1978) and Venera 13 and 14 (1982) landers performed in situ spectrophotometric observations during descent, the original datasets were later lost. However, a subset has been reconstructed by digitising graphical outputs produced during the missions’ initial data-processing phase [1]. Following careful analysis to identify and mitigate errors and other artefacts, the reconstructed dataset retains the reliable downward-looking spectra acquired by the three landers from ~62 km altitude to the surface.Previous retrievals from the reconstructed Venera 13 indicated an NSPL centred at ~3.5–5 km, with particulate optical properties consistent with a basaltic composition [2]. Following the methodology of [2], we use NEMESIS, a radiative transfer and retrieval code [3], to perform near-surface retrievals from the reconstructed Venera 11 and Venera 14 datasets. The results from Venera 11, 13, and 14 retrievals are compared with reported detections and non-detections from other instruments on earlier in situ missions, to explore potential formation pathways for the NSPL in light of the combined observational record.References:[1] Ignatiev, N. I., Moroz, V. I., Moshkin, B. E., Ekonomov, A. P., Gnedykh, V. I., Grigor’ev, A. V., and Khatuntsev, I. V. Cosmic Research 35(1), 1–14 (1997).[2] Kulkarni, S. V., Irwin, P. G. J., Wilson, C. F., & Ignatiev, N. I. Journal of Geophysical Research: Planets, 130, e2024JE008728, (2025).[3] Irwin, P. G., Teanby, N. A., de Kok, R., Fletcher, L. N., Howett, C. J., Tsang, C. C., Wilson, C. F., Calcutt, S. B., Nixon, C. A., and Parrish, P. D. Journal of Quantitative Spectroscopy and Radiative Transfer 109(6), 1136–1150 (2008). 

Abstract:

To extract, or 'retrieve' atmospheric properties from the observed radiance spectra from a planetary atmosphere requires software that can generate the expected radiances from a guessed atmospheric model, compare the radiances with those measured, determine how the model should be updated to reduce any discrepancy between the modelled and observed radiances, and then iterate these steps until these differences are minimised. One such retrieval model is NEMESIS (Nonlinear optimal Estimator for MultivariatE Spectral analySIS), which was initially developed by myself and my colleagues in the 1990s, and which has since been continually updated and enhanced. NEMESIS has now been used in more than 300 papers retrieving atmospheric properties from observed thermal and solar-reflected radiance spectra from all the planetary atmospheres in our solar system and also some beyond. NEMESIS uses the Optimal Estimation framework for atmospheric retrievals and is written in FORTRAN. Recently, more Bayesian frameworks have become computationally possible and favoured, especially for exoplanetary retrievals where prior constraints are almost entirely absent. Hence, NEMESIS has recently been updated to Python (ArchNEMESIS), and combined with PyMultiNest to allow nested sampling retrievals that can better explore the degeneracy between different atmospheric properties. I will review how NEMESIS retrievals have improved our understanding of planetary atmospheres over the last 30 years and how the development of ArchNEMESIS has breathed new life into the NEMESIS/ArchNEMESIS project. 

Abstract:

The Lunar-Earth Gravitational Assist (LEGA) of 19-20 August 2024 marked the first in-flight opportunity beyond functional checks to perform MAJIS (Moons and Jupiter Imaging Spectrometer) observations on-board the ESA’s Jupiter Icy Moons Explorer (JUICE) spacecraft. This unique double flyby involved sequential close approaches to the Moon and Earth, offering an unprecedented configuration to evaluate MAJIS under high radiance, rapidly changing geometric, and operationally constrained conditions. A total of 24 hyperspectral image cubes were acquired (5 targeting the Moon and 19 the Earth) providing a dataset of approximately 7.5 Gbit. This work presents the primary goal of this observation campaign, which was to verify key aspects of MAJIS performance, including radiometric and spectral calibration, straylight behavior, geometric alignment, the use of onboard browse products, and interference tests with other JUICE instruments. This event also enabled assessment of thermal behavior and susceptibility to electromagnetic interference, and provided a first operational benchmark for MAJIS and a basis for refining future observation strategies and data analyses during JUICE’s cruise and science phases. In addition, despite limited spatial and temporal coverage of the observations, the analyses presented here and in a series of companion papers of the special issue “The first-ever lunar-Earth flyby: a unique test environment for JUICE” demonstrated the instrument’s ability to characterize mineralogical features on the Moon and atmospheric constituents on Earth. Observations include detection of mafic minerals (some associated to fresh excavated materials), thermal emission, and emissivity variations on the Moon at spatial scale of 100-200 m. Characterization of atmospheric absorption features, thermal brightness, icy cloud properties are captured for the Earth at km-scale and briefly discussed in the framework of the atmospheric biosignatures relevant to exoplanet habitability studies. Near-coincident acquisitions with other JUICE instruments and Earth-orbiting spectrometers provided valuable inter-calibration and cross-validation opportunities.