Timescale dependence of aeolian sand flux observations under atmospheric turbulence
Bibliographic record
Abstract
The transport of sand in saltation is driven by the persistently unsteady stresses exerted by turbulent winds. Based on coupled high‐frequency observations of wind velocity and sand flux on a desert dune during intermittent saltation, we show here how observations of saltation by natural winds depend significantly on the timescale and method used for determining shear stress and sand flux. The correlation between sand flux and excess shear stress (stress above a threshold value) systematically improves for longer averaging timescale, T , and is better for stress determined by the law‐of‐the‐wall versus the Reynolds stress method. Fitting parameters for the stress‐flux relationship do not converge with increasing T , which may be explained by the nonstationary nature of wind velocity statistics. We show how it may be possible, based on the scale‐dependent statistics of stress fluctuations, to rescale saltation flux predictions for wind observations made at different timescales. However, our observations indicate hysteresis and time lags in thresholds for initiation and cessation of saltation, which complicate threshold‐based approaches to predicting sediment transport at different timescales.
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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 | 0.000 |
| 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".