Scale Interactions in Turbulence for Mountain Blowing Snow
Bibliographic record
Abstract
Abstract Blowing snow particle transport responds to wind motions across many length and time scales. This coupling is nonlinear by nature and complicated in atmospheric flows where eddies of many sizes are superimposed. In mountainous terrain, wind flow descriptions are further complicated by topographically influenced or enhanced flows. To improve the current understanding and modeling of blowing snow transport in complex terrain, statistically significant timing and frequencies of wind–snow coupling were identified in high-frequency observations of surface blowing snow and near-surface turbulence from a mountain field site in the Canadian Rockies. Investigation of the mechanisms influencing near-surface, high-frequency turbulence and snow concentration fluctuations provided strong evidence for amplitude modulation from large-scale motions. The large-scale atmospheric motions modulating near-surface turbulence and snow transport were then compared to specific quadrant analysis structures recently identified as relevant for outdoor blowing snow transport. The results suggest that large atmospheric structures modulate the amplitude of high-frequency turbulence and modify turbulence statistics typically used to model blowing snow. Additionally, blowing snow was preferentially redistributed under the footprint of these same sweep motions, with both low- and high-frequency coherence increasing in their presence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".