Zachary Burr | Searcharxiv

arXiv2026

Retrieving the Red Edge on Earth-like Planets with Heterogeneous Clouds and Surfaces

The detection and characterization of potentially habitable exoplanets is one of the chief goals of astrophysics for the coming decades. Imaging in reflected light is well suited for characterizing Earth-like planets, as much can be learned about these planets in this wavelength range (i.e., ~0.3-2 μm). Several studies have been conducted to determine the abilities and limitations of reflectance spectroscopy, but most previous studies assumed a homogeneous atmospheric and surface composition. Here we investigate how heterogeneities in the atmosphere and surface of an Earth-like planet impact retrieval results. We extend the ExoReL retrieval framework to include a step function for retrieving wavelength varying surface albedo. We then use it to retrieve on visible-to-near-infrared spectra of realistic 3D Earth models with different surface features in view and varying cloud types/distributions synthesized with the Planetary Spectrum Generator. Including the ability to fit for wavelength dependent albedo mitigates degeneracies that arise when using 1D models to analyze 3D planets, and we recover an Earth-like planet in all cases. We detect surface albedo steps at ~0.7 and ~1.1 μm despite clouds, both when significant lands are in view and when the spectra are averaged to account for a longer integration time. Our findings support the application of the vegetation red edge as a biosignature in the context of the Habitable Worlds Observatory. This study highlights the importance of considering a range of-particularly wavelength-dependent-surface albedos when using reflectance spectroscopy to characterize Earth-like exoplanets.

astro-ph.EP↗

arXiv2025

Effects of planetary mass uncertainties on the interpretation of the reflectance spectra of Earth-like exoplanets

Atmospheric characterization of Earth-like exoplanets through reflected light spectroscopy is a key goal for upcoming direct imaging missions. A critical challenge in this endeavor is the accurate determination of planetary mass, which may influence the measurement of atmospheric compositions and the identification of potential biosignatures. In this study, we used the Bayesian retrieval framework ExoReL$^\Re$ to investigate the impact of planetary mass uncertainties on the atmospheric characterization of terrestrial exoplanets observed in reflected light. Our results indicate that precise prior knowledge of the planetary mass can be crucial for accurate atmospheric retrievals if clouds are present in the atmosphere. When the planetary mass is known within 10\% uncertainty, our retrievals successfully identified the background atmospheric gas and accurately constrained atmospheric parameters together with clouds. However, with less constrained or unknown planetary mass, we observed significant biases, particularly in the misidentification of the dominant atmospheric gas. For instance, the dominant gas was incorrectly identified as oxygen for a modern-Earth-like planet or carbon dioxide for an Archean-Earth-like planet, potentially leading to erroneous assessments of planetary habitability and biosignatures. These biases arise because, the uncertainties in planetary mass affect the determination of surface gravity and atmospheric scale height, leading the retrieval algorithm to compensate by adjusting the atmospheric composition. Our findings emphasize the importance of achieving precise mass measurements-ideally within 10\% uncertainty-through methods such as extreme precision radial velocity or astrometry, especially for future missions like the Habitable Worlds Observatory.

astro-ph.EP↗