Abstract TRAPPIST-1 e is one of a few habitable zone exoplanets that is amenable to characterization in the near term. In this study our motivations are both scientific and technical. Our technical goal is to establish a multimodel sparse sampled ensemble approach for coherently exploring large unconstrained parameter spaces typical in exoplanet science. Our science goal is to determine relationships that connect observations to the underlying climate across a large parameter space of atmospheric compositions for TRAPPIST-1 e. We consider atmospheric compositions of N 2 , CO 2 , CH 4 , and H 2 O, with water clouds and photochemical hazes. We use a 1D photochemical model, a 3D climate model, and a transmission spectral model, filtered through a quasi−Monte Carlo sparse sampling approach applied across atmospheric compositions. While clouds and hazes have significant effects on the transmission spectra, CO 2 and CH 4 can be potentially detected in ≤10 transits for certain compositional and climate states. Colder climates have better prospects for characterization, due to being relatively dry and having fewer clouds, permitting transmission observations to probe more deeply into their atmospheres. CH 4 volume mixing ratios of ≥10 −3 trigger strong antigreenhouse cooling, where near-IR absorption simultaneously creates an inversion in the stratosphere and reduces the stellar radiation reaching the planet surface. In such cases, interpreting the disk-averaged emission and albedo at face value can yield misleading conclusions, as here low albedo and high thermal emission are associated with cold planets. Future work will use our sparse sampling approach to explore broader parameter spaces and other observationally amenable exoplanets.
Wolf et al. (2025) studied this question.