The impact of ocean waves on spray stress and surface drag coefficient
Bibliographic record
Abstract
Purpose The behaviors of sea surface drag coefficient should be well understood for an accurate hurricane prediction. The speed of wind has been applied to characterize the spray production; however, this could result in inaccurate spray productions compared to the experimental or field data if the influence of wave state is not considered. This paper aims to integrate a new sea spray generation function, described by windsea Reynolds number, into the spray momentum flux formula to calculate the spray momentum. Design/methodology/approach On the basis of this spray momentum, this study proposes the new formulas of spray stress and drag coefficient when the wind speed is high. Findings Results of the revised formulas show that wave status had significant effects on the spray stress and sea surface drag coefficient. Also, wave age was found to be an important parameter that affects the drag coefficient. The drag coefficient decreased with the increasing wave age. Comparison between this study’s theoretical and observation values of drag coefficient shows that the study results are close to the measured values. Research limitations/implications The research findings can enhance the understanding of the behaviors of sea surface drag for an accurate hurricane prediction. Originality/value A new sea spray generation function, described by windsea Reynolds number, is integrated into the spray momentum flux formula to calculate the spray momentum. On the basis of this spray momentum, this study proposes the new formulas of spray stress and drag coefficient when the wind speed is high.
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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 | 0.001 | 0.001 |
| 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".