Thermal Forcing of the Nocturnal Near Surface Environment by Martian Water Ice Clouds
Bibliographic record
Abstract
Abstract We explore the potential role of clouds in moderating the nighttime temperature within Gale crater, as observed by the Rover Environmental Monitoring Station (REMS) instrument suite aboard the Curiosity rover. Just prior to aphelion, the decreasing trend in minimum daily temperature within Gale slows down. We investigate if this is due to increased formation of twilight and nighttime clouds, re‐radiating heat and reducing atmospheric and surface cooling. While diurnal analysis of REMS temperatures shows brief atmospheric warmings of 3–5 K post‐sunset during the occurrence of these clouds, an absence of similar warmings in the ground temperature measurements make it unlikely that clouds are the primary source. Seasonally, however, clouds that persist overnight could cause a warming of daily minimum surface temperatures in the Ls∼20°–50° season. This period can serve as a baseline and allow the potential effects of clouds to be more clearly discerned in the REMS temperature measurements. For this season, and in the peak of the aphelion cloud belt season, our modeled atmospheric energy budget shows a nocturnal decay signature of downward IR reflected and re‐emitted flux consistent with the presence and impact of clouds. The expected approximate exponential decay of this flux post‐sunset is damped more heavily in cloudier seasons than less cloudy or dusty seasons, suggesting formation and thickening of ice clouds as atmospheric nighttime temperatures cool.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".