Toward More Realistic Simulation and Prediction of Dust Storms on Mars
Bibliographic record
Abstract
Atmospheric dust is a more extreme modifier of weather and climate on Mars than water vapor is on Earth. Global dust storms enshroud Mars in a veil of dust for months and have major implications for past and present climate, geologic history, habitability, and exploration. Yet their mysterious origins mean we remain unable to realistically simulate or predict them. In this White Paper, we find that key Knowledge Gaps are: A. how dust is lifted; B. constraints on near-surface winds and boundary-layer processes; C. the distribution of mobile surface dust; and D. the key processes and feedbacks by which dust storms begin and evolve. To make progress in the next decade, we make four Recommendations in order of priority: #1. Properly accommodate a minimum payload of meteorological and aeolian sensors on future Mars surface missions; #2. Continue orbital monitoring of the evolving surface dust distribution; #3. Expand orbital measurements to include winds and full diurnal coverage; and #4. Continue orbital monitoring and add surface measurements of aerosols during dust storms.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".