Possible Atmospheric Water Vapor Contribution from Martian Swiss Cheese Terrain
Bibliographic record
Abstract
Abstract Mars’s south polar residual cap (SPRC) is a several-meters-thick CO2 ice cap with a variety of features, including quasi-circular depressions known as “Swiss cheese” that may expose underlying water ice. Swiss cheese pits have been suggested as a source for the observation of unusually high water vapor during the southern summer of Mars Year (MY) 8 (1969). To evaluate this hypothesis, we map the current extent of Swiss cheese pits to estimate the contribution to atmospheric water vapor from sublimation from the pits. We use data from the Mars Reconnaissance Orbiter Context Camera to map individual features and use the Mars Climate Sounder to obtain surface temperatures to estimate areas of exposed water ice to infer the amount of water vapor sublimated under typical south polar summer atmospheric conditions. We find that there is a negligible impact on atmospheric water vapor from sublimation with the current coverage and temperatures of Swiss cheese terrain (0.2% of the SPRC at an average of ∼161 K). At current typical temperatures, complete removal of residual CO2 from 99% of the SPRC would be required to sublimate enough water vapor to reproduce the MY 8 observation. However, a modest increase in temperature (∼20 K) could lead to a dramatic increase in sublimation rate, such that only water ice over 2.6% of the SPRC area would recreate the MY 8 observation. >180 K surface water ice has been observed on Mars, but such temperatures are likely transient at the south pole over the past ∼30 Mars years.
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 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 | 0.001 | 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) | 0.001 | 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".