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Record W4221054772 · doi:10.5194/egusphere-egu22-8185

3D Climate modelling of TRAPPIST-1 c with a Venus-like atmosphere: large-scale circulation and observational prospects

2022· preprint· en· W4221054772 on OpenAlexaff
Diogo Quirino, Gabriella Gilli, T. Navarro, Martin Turbet, Thomas J. Fauchez, Pedro Machado

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsMcGill University
Fundersnot available
KeywordsExoplanetAtmosphere (unit)PhysicsRADIUSVenusAstrobiologyObservableAstronomyPlanetAtmosphere of VenusAtmospheric sciencesEnvironmental scienceMeteorology

Abstract

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In recent years, several Earth-sized exoplanets have been detected in short-period orbits of a few Earth days, around low-mass stars [1]. Despite their small size compared to gas giants, their close-in orbits combined with the small radius of the host star compared to our Sun’s make these worlds the best targets for atmospheric characterisation among rocky exoplanets. These worlds have stellar irradiation levels that can be several times that of the Earth, suggesting that a Venus-like climate is more likely [2]. Thus, the atmosphere of our neighbouring planet Venus presents a relevant case to address observational prospects. The recent launch of the James Webb Space Telescope will advance the atmosphere and climate characterisation of nearby rocky exoplanets, with the support of upcoming ground-based observatories and space telescopes, such as the ESA/Ariel mission, scheduled for launch in 2029. The interpretation of the observables produced by these missions: reflectance, thermal emission and transmission spectra will need support from modelling studies of exoplanetary atmospheres. In particular, 3D Global Climate Models (GCMs) are critical for interpreting the observable signal’s modulations, as they provide synthetic top-of-the-atmosphere fluxes that can be disk-integrated as a function of the orbital phase. The spatial and temporal variability of these fluxes reflect the atmospheric variability of the simulated temperature and wind fields and provide insight over the large-scale circulation. In this work, we used the Generic-GCM, developed at the Laboratoire de Météorologie Dynamique for exoplanet and paleoclimate studies [3, 4, 5], which includes a 3D dynamical core, common to all terrestrial planets, a planet-specific physical core, and an up-to-date generalised radiative transfer routine for variable atmospheric compositions. We present the results of modelling highly irradiated rocky exoplanets orbiting an M-dwarf star, using a Venus-like atmosphere as a possible framework for the atmospheric conditions of TRAPPIST-1 c. We assumed synchronous rotation, zero eccentricity and obliquity, and a Venus-like atmosphere with 92-bar surface pressure and a radiatively active Venus-type global cloud cover. The results indicate an eastward shift of the peak thermal emission away from the sub-stellar point, suggesting an advection of warm air masses caused by a superrotation equatorial jet. References: [1] Gillon et al. 2017. Nature. 542. [2] Kane et al. 2018. ApJ. 869. [3] Forget & Leconte, 2014. Phil. Trans R. Soc. A372. [4] Turbet et al. 2016. A&A. 596. A112. [5] Wordsworth et al. 2011. ApJL. 733. L48. Acknowledgements: This work is supported by Fundação para a Ciência e a Tecnologia (FCT) through the research grants UIDB/04434/2020, UIDP/04434/2020, P-TUGA PTDC/FIS-AST/29942/2017.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.221
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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