Wind drag in oil spilled ocean surface and its impact on wind-driven circulation
Bibliographic record
Abstract
Abstract The drag coefficient is a key parameter to quantify the wind stress over the ocean surface, which depends on the ocean surface roughness. During oil spill events, oil slicks cover the ocean surface and thus change the surface roughness by suppressing multi-scale ocean surface waves, and the drag coefficient is changed. This change has not been included in the current ocean circulation models. In this study, such change in sea surface roughness is studied by satellite remote sensing via synthetic aperture radar (SAR) data to quantify the changes in the wind effect over the oil-covered ocean surface. The concept of effective wind speed is introduced to quantify the wind work on the ocean. We investigate its influence on the wind-driven Ekman current at the ocean surface. Using observations from the Deepwater Horizon oil spill (2010) as an example, we find that the presence of oil can result in an effective wind speed of 50%~100% less than the conventional wind speed, causing overestimates by 75%~100% in the wind driven Ekman current. The effect of such bias on oil trajectory predictions is also discussed. Our results suggest that it is important to consider the effect of changes in the drag coefficient over oil-contaminated areas, especially for large-scale oil spill situations.
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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 | 0.001 |
| 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) | 0.001 | 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".