Chemistry of (exo)planetary atmospheres

Over the past two decades, the study of exoplanets has revealed a remarkable diversity beyond our Solar System. Advances in observational techniques have enabled scientists to probe the atmospheres of a small fraction of the more than 5,500 known exoplanets, analysing their spectroscopic features to infer physical properties (such as dynamics, pressure, and temperature) and chemical compositions (including molecular abundances). Although atmospheric characterization remains slow, current data indicate that exoplanet atmospheres are highly diverse and often unexpected in their chemistry. The James Webb Space Telescope (JWST), launched in 2022, has significantly enhanced our ability to study these atmospheres by capturing data at high spectral resolution across a broad wavelength range. Importantly, JWST can investigate the transition zone between rocky planets and gas giants and assess the most promising terrestrial exoplanets for habitability. This could bring us closer to detecting signs of life beyond Earth.
The Exeter Exoplanet Theory Group (EETG) within the Astrophysics department has been developing sophisticated multi-dimensional numerical models to better understand the key physical and chemical processes in exoplanetary atmospheres. These models help interpret JWST's latest findings and improve predictions of atmospheric behaviour. Their modelling framework includes the Met Office Unified Model (UM), a state-of-the-art 3D atmospheric model incorporating advanced radiative transfer and chemistry simulations. This research project involves enhancing multi-dimensional chemical models to improve interpretations of high-resolution exoplanetary observations, with a focus on photochemistry.
Students involved in these projects will gain expertise in programming, high-performance computational modelling, and atmospheric science. They will work as part of a diverse team exploring exoplanet atmospheres through various approaches, including radiative transfer, climate modelling, and dynamics. While training will be provided, candidates should have experience in programming and hold a degree in Mathematics, Physics, or Natural Sciences. A background in Chemistry is beneficial but not required.