Mars' atmosphere: The sister planet, our statistical twin
Bibliographic record
Abstract
Abstract Satellite‐based Martian reanalyses have allowed unprecedented comparisons between our atmosphere and that of our sister planet, underlining various similarities and differences in their respective dynamics. Yet by focusing on large scale structures and deterministic mechanisms they have improved our understanding of the dynamics only over fairly narrow ranges of (near) planetary scales. However, the Reynolds numbers of the flows on both planets are larger than 1011 and dissipation only occurs at centimetric (Mars) or millimetric scales (Earth) so that over most of their scale ranges, the dynamics are fully turbulent. In this paper, we therefore examine the high‐level, statistical, turbulent laws for the temperature, horizontal wind, and surface pressure, finding that Earth and Mars have virtually identical statistical exponents so that their statistics are very similar over wide ranges. Therefore, it would seem that with the exception of certain aspects of the largest scales (such as the role of dust in atmospheric heating on Mars, or of water in its various phases on Earth), that the nonlinear dynamics are very similar. We argue that this is a prediction of the classical laws of turbulence when extended to planetary scales and that it supports our use of turbulent laws on both planetary atmospheres.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".