How to disentangle composition, clouds, and thermal structure in JWST retrievals

[JasonUS]

I'm an astrophysics graduate student working on modeling transmission spectroscopy data from JWST to characterize exoplanet atmospheres, specifically for a few hot Jupiters, but I'm struggling to disentangle the degeneracies between atmospheric composition, cloud/haze properties, and thermal structure in my retrievals. Even with the incredible data quality, different model assumptions can produce equally good fits with wildly different interpretations regarding metallicity or the presence of biosignature gases. For researchers in the field, what are the current best practices and computational tools for robust atmospheric retrieval? How are you incorporating new chemical networks and cloud microphysics models to reduce these uncertainties, and what observational priorities for future telescope time do you think are most critical to move beyond simple detections to truly comparative exoplanetology?

[Avery90]

You're right—let's lay out concrete, usable guidance for robust atmospheric retrieval with JWST-quality data.