Directional Dynamics of Fog: Irreversibility and Causal Coupling with Turbulence
Bibliographic record
Abstract
Abstract Fog prediction remains challenging because the physical processes governing its life cycle evolve across time scales and do not follow reversible or stationary dynamics. Using high‐frequency visibility observations from Sable Island, Canada, this study analyzes fog intensity and turbulent kinetic energy (TKE) for their time irreversibility and causal relations. Fog intensity exhibits temporal asymmetry in all stages, while TKE remains nearly reversible. The lead–lag structure between the two variables is stage dependent: TKE leads fog intensity during formation, the coupling becomes symmetric during the mature phase, and fog intensity leads TKE during dissipation. Notably, during fog formation, the strength of fog's intrinsic irreversibility increases linearly with the strength of its causal linkage to TKE, revealing that fog initiation is governed by a directional sequence of turbulence–moisture interactions. These findings demonstrate that fog is a non‐equilibrium, time‐asymmetric system, and that capturing its stage‐dependent directionality is required for enhanced fog prediction.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".