Cloud and Haze Parameterization in Atmospheric Retrievals: Insights from Titan's Cassini Data and JWST Observations of Hot Jupiters

Context: Before JWST, telescope observations were not sensitive enough to constrain the nature of clouds in exo-atmospheres. Recent observations, however, have inferred cloud signatures as well as haze-enhanced scattering slopes motivating the need for modern inversion techniques and a deeper understanding of the JWST information content. Aims: We aim to investigate the information content of JWST exoplanet spectra. We particularly focus on designing an inversion technique able to handle a wide range of cloud and hazes. Methods: We build a flexible aerosol parameterization within the TauREx framework, enabling us to conduct atmospheric retrievals of planetary atmospheres. The method is evaluated on available Cassini occultations of Titan. We then use the model to interpret the recent JWST data for the prototypical hot Jupiters HAT-P-18 b, WASP-39 b, WASP-96 b, and WASP-107 b. In parallel, we perform complementary simulations on controlled scenarios to further understand the information content of JWST data and provide parameterization guidelines. Results: Our results use free and kinetic chemistry retrievals to extract the main atmospheric properties of key JWST exoplanets, including their molecular abundances, thermal structures, and aerosol properties. In our investigations, we show the need for a wide wavelength coverage to robustly characterize clouds and hazes-which is necessary to mitigate biases arising from our lack of priors on their composition-and break degeneracies with atmospheric chemical composition. With JWST, the characterization of clouds and hazes might be difficult due to the lack of simultaneous wavelength coverage from visible to mid-infrared by a single instruments and the likely presence of temporal variability between visits (from e.g., observing conditions, instrument systematics, stellar host variability, or planetary weather).