BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN

Abstract We deploy a newly generated set of geometric albedo spectral grids to examine the detectability of methane (CH 4 ) in the reflected-light spectrum of an Earth-like exoplanet at visible and near-infrared (NIR) wavelengths with a future exoplanet imaging mission. By quantifying the detectability as a function of signal-to-noise ratio (SNR) and molecular abundance, we can constrain the best methods of detection with the high-contrast space-based coronagraphy slated for the next-generation telescopes such as the Habitable Worlds Observatory. We used 25 bandpasses between 0.8 and 1.5 μ m. The abundances range from a modern-Earth level to an Archean-Earth level, driven by abundances found in available literature. We constrain the optimal 20%, 30%, and 40% bandpasses based on the effective SNR of the data, and investigate the impact of spectral confusion between CH 4 and H 2 O on the detectability of each one. We find that a modern-Earth level of CH 4 is not detectable, while an Archean-Earth level of CH 4 would be detectable at all SNRs and bandpass widths. Crucially, we find that CH 4 detectability is inversely correlated with H 2 O abundance, with the required SNR increasing as H 2 O abundance increases, while H 2 O detectability depends on CH 4 abundance and the selected observational wavelength, implying that any science requirements for the characterization of Earth-like planet atmospheres in the visible–NIR should consider the abundances of both species in tandem.

Authors

Publication Details

Journal
The Astronomical Journal
Published
2024-12-24
DOI
https://doi.org/10.3847/1538-3881/ad9729
Citations
2
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.57
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article

BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN

Vincent Kofman, Gerónimo Villanueva, Chris Stark, Natasha Latouf et al.
2 citations
The Astronomical Journal
Atmospheric and Environmental Gas Dynamics
0.57
article

BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN

Vincent Kofman, Gerónimo Villanueva, Chris Stark, Natasha Latouf, Avi M. Mandell, Michael Dane Moore, Michael D. Himes
article en
2 citations

Abstract

Abstract We deploy a newly generated set of geometric albedo spectral grids to examine the detectability of methane (CH 4 ) in the reflected-light spectrum of an Earth-like exoplanet at visible and near-infrared (NIR) wavelengths with a future exoplanet imaging mission. By quantifying the detectability as a function of signal-to-noise ratio (SNR) and molecular abundance, we can constrain the best methods of detection with the high-contrast space-based coronagraphy slated for the next-generation telescopes such as the Habitable Worlds Observatory. We used 25 bandpasses between 0.8 and 1.5 μ m. The abundances range from a modern-Earth level to an Archean-Earth level, driven by abundances found in available literature. We constrain the optimal 20%, 30%, and 40% bandpasses based on the effective SNR of the data, and investigate the impact of spectral confusion between CH 4 and H 2 O on the detectability of each one. We find that a modern-Earth level of CH 4 is not detectable, while an Archean-Earth level of CH 4 would be detectable at all SNRs and bandpass widths. Crucially, we find that CH 4 detectability is inversely correlated with H 2 O abundance, with the required SNR increasing as H 2 O abundance increases, while H 2 O detectability depends on CH 4 abundance and the selected observational wavelength, implying that any science requirements for the characterization of Earth-like planet atmospheres in the visible–NIR should consider the abundances of both species in tandem.

The Astronomical JournalVol. 169(1)
Openalex Percentile: Top 31%
Atmospheric and Environmental Gas Dynamics
0.57
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BARBIE. Bayesian Analysis for Remote Biosignature Identification on exoEarths. III. Introducing the KEN — Vincent Kofman, Gerónimo Villanueva, et al. · The Astronomical Journal (2024) | TGRS Research Map | TGRS