3D simulations of TRAPPIST-1e with varying CO2, CH4, and haze profiles
Bibliographic record
Abstract
ABSTRACT Using a 3D General Circulation Model, the Unified Model, we present results from simulations of a tidally locked TRAPPIST-1e with varying carbon dioxide CO2 and methane CH4 gas concentrations, and their corresponding prescribed spherical haze profiles. Our results show that the presence of CO2 leads to a warmer atmosphere globally due to its greenhouse effect, with the increase of surface temperature on the dayside surface reaching up to ∼14.1 K, and on the nightside up to ∼21.2 K. Increasing presence of CH4 first elevates the surface temperature on the dayside, followed by a decrease due to the balance of tropospheric warming and stratospheric cooling. A thin layer of haze, formed when the partial pressures of CH4 to CO2 (pCH4/pCO2) = 0.1, leads to a dayside warming of ∼4.9 K due to a change in the water vapour H2O distribution. The presence of a haze layer that formed beyond the ratio of 0.1 leads to dayside cooling. The haze reaches an optical threshold thickness when pCH4/pCO2 ∼ 0.4 beyond which the dayside mean surface temperature does not vary much. The planet is more favourable to maintaining liquid water on the surface (mean surface temperature above 273.15 K) when pCO2 is high, pCH4 is low, and the haze layer is thin. The effect of CO2, CH4, and haze on the dayside is similar to that for a rapidly rotating planet. On the contrary, their effect on the nightside depends on the wind structure and the wind speed in the simulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".