Pursuing Truth: Improving Retrievals on Mid-Infrared Exo-Earth Spectra with Physically Motivated Water Abundance Profiles and Cloud Models

TL;DR

This study demonstrates that using physically motivated water and cloud models in atmospheric retrievals significantly improves the accuracy of exo-Earth characterization from mid-infrared spectra, aiding future habitable planet detection.

Contribution

It introduces and validates physically motivated water and cloud models in retrieval frameworks, enhancing the accuracy of exo-Earth spectral analysis.

Findings

Physically motivated models outperform simpler assumptions.

Accurate estimates of planetary properties are achievable with improved models.

Detection of biosignatures like CH4 is feasible at R=100.

Abstract

Atmospheric retrievals are widely used to constrain exoplanet properties from observed spectra. We investigate how the common nonphysical retrieval assumptions of vertically constant molecule abundances and cloud-free atmospheres affect our characterization of an exo-Earth (an Earth-twin orbiting a Sun-like star). Specifically, we use a state-of-the-art retrieval framework to explore how assumptions for the $\mathrm{H_2O}$ profile and clouds affect retrievals. In a first step, we validate different retrieval models on a low-noise simulated 1D mid-infrared (MIR) spectrum of Earth. Thereafter, we study how these assumptions affect the characterization of Earth with the Large Interferometer For Exoplanets (LIFE). We run retrievals on LIFE mock observations based on real disk-integrated MIR Earth spectra. The performance of different retrieval models is benchmarked against ground truths derived from remote sensing data. We show that assumptions for the $\mathrm{H_2O}$ abundance and clouds directly affect our characterization. Overall, retrievals that use physically motivated models for the $\mathrm{H_2O}$ profile and clouds perform better on the empirical Earth data. For observations of Earth with LIFE, they yield accurate estimates for the radius, pressure-temperature structure, and the abundances of $\mathrm{CO_2}$, $\mathrm{H_2O}$, and $\mathrm{O_3}$. Further, at $R=100$, a reliable and bias-free detection of the biosignature $\mathrm{CH_4}$ becomes feasible. We conclude that the community must use a diverse range of models for temperate exoplanet atmospheres to build an understanding of how different retrieval assumptions can affect the interpretation of exoplanet spectra. This will enable the characterization of distant habitable worlds and the search for life with future space-based instruments.