Climate uncertainties caused by unknown land distribution on habitable M-Earths
Bibliographic record
Abstract
A planet's surface conditions can significantly impact its climate and habitability. In this study, we use the 3D general circulation model ExoPlaSim to systematically vary dayside land cover on a synchronously rotating, temperate rocky planet under two extreme and opposite continent configurations, in which either all of the land or all of the ocean is centred at the substellar point. We identify water vapour and sea ice as competing drivers of climate, and we isolate land-dependent regimes under which one or the other dominates. We find that the amount and configuration of land can change the planet's globally averaged surface temperature by up to 20K, and its atmospheric water vapour content by several orders of magnitude. The most discrepant models have partial dayside land cover with opposite continent configurations. Since transit spectroscopy may permit observations of M-dwarf planets' atmospheres, but not their surfaces, these land-related climate differences likely represent a limiting uncertainty in a given planet's climate, even if its atmospheric composition is known. Our results are robust to variations in atmospheric CO2 concentration, stellar temperature, and instellation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".