Variability due to climate and chemistry in observations of oxygenated Earth-analogue exoplanets

TL;DR

This study uses Earth System Models and spectral simulations to analyze how climate variability, chemistry, and observational factors influence the detection of oxygen and water features in Earth-like exoplanets' atmospheres.

Contribution

It demonstrates the impact of climate and chemical variability on exoplanet spectral observations and assesses telescope capabilities for detecting atmospheric features.

Findings

Inter-annual and short-term climate variations affect spectral flux by factors of up to 5 and 20.

High-throughput coronagraphs like HabEx improve detection of variability.

Spectral feature signals depend non-linearly on atmospheric O₂ levels.

Abstract

The Great Oxidation Event was a period during which Earth's atmospheric oxygen (O$_2$) concentrations increased from $\sim 10^{-5}$ times its present atmospheric level (PAL) to near modern levels, marking the start of the Proterozoic geological eon 2.4 billion years ago. Using WACCM6, an Earth System Model, we simulate the atmosphere of Earth-analogue exoplanets with O$_2$ mixing ratios between 0.1% and 150% PAL. Using these simulations, we calculate the reflection/emission spectra over multiple orbits using the Planetary Spectrum Generator. We highlight how observer angle, albedo, chemistry, and clouds affect the simulated observations. We show that inter-annual climate variations, as well short-term variations due to clouds, can be observed in our simulated atmospheres with a telescope concept such as LUVOIR or HabEx. Annual variability and seasonal variability can change the planet's reflected flux (including the reflected flux of key spectral features such as O$_2$ and H$_2$O) by up to factors of 5 and 20, respectively, for the same orbital phase. This variability is best observed with a high-throughput coronagraph. For example, HabEx (4 m) with a starshade performs up to a factor of two times better than a LUVOIR B (6 m) style telescope. The variability and signal-to-noise ratio of some spectral features depends non-linearly on atmospheric O$_2$ concentration. This is caused by temperature and chemical column depth variations, as well as generally increased liquid and ice cloud content for atmospheres with O$_2$ concentrations of $<$1% PAL.