A systematic study of \ce{CO2} planetary atmospheres and their link to the stellar environment

• Published in: arXiv.org
• Main Authors: Petralia, A, Alei, E, Aresu, G, Locci, D, Cecchi-Pestellini, C, Micela, G, Claudi, R, Ciaravella, A
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 30.06.2020
• Subjects: Atmospheric circulation; Atmospheric composition; Atmospheric models; Atmospheric pressure; Carbon dioxide; Extrasolar planets; General circulation models; Mathematical models; Milky Way Galaxy; Ocean dynamics; Ocean models; Parameters; Physics - Earth and Planetary Astrophysics; Physics - Solar and Stellar Astrophysics; Planetary atmospheres; Planetary evolution; Radiative transfer; Three dimensional models
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2006.16650

The Milky Way Galaxy is literally teeming with exoplanets; thousands of planets have been discovered, with thousands more planet candidates identified. Terrestrial-like planets are quite common around other stars, and are expected to be detected in large numbers in the future. Such planets are the primary targets in the search for potentially habitable conditions outside the solar system. Determining the atmospheric composition of exoplanets is mandatory to understand their origin and evolution, as atmospheric processes play crucial roles in many aspects of planetary architecture. In this work we construct and exploit a 1D radiative transfer model based on the discrete-ordinates method in plane-parallel geometry. Radiative results are linked to a convective flux that redistributes energy at any altitude producing atmospheric profiles in radiative-convective equilibrium. The model has been applied to a large number (6250) of closely dry synthetic \ce{CO2} atmospheres, and the resulting pressure and thermal profiles have been interpreted in terms of parameter variability. Although less accurate than 3D general circulation models, not properly accounting for e.g., clouds and atmospheric and ocean dynamics, 1D descriptions are computationally inexpensive and retain significant value by allowing multidimensional parameter sweeps with relative ease.