The Impact of Waves on Surface Currents
Bibliographic record
Abstract
Ocean models usually estimate surface currents without explicit modeling of the ocean waves. To consider the impact of waves on surface currents, here a wave model is used in a modified Ekman layer model, which is imbedded in a diagnostic ocean model. Thus wave effects, for example, Stokes drift and wave-breaking dissipation, are explicitly considered in conjunction with the Ekman current, mean currents, and wind-driven pressure gradient currents. It is shown that the wave effect on currents is largest in rapidly developing intense storms, when wave-modified currents can exceed the usual Ekman currents by as much as 40%. A large part of this increase in velocity can be attributed to the Stokes drift. Reductions in momentum transfer to the ocean due to wind input to waves and enhancements due to wave dissipation are each of the order 20%–30%. Model results are compared with measurements from the Labrador Sea Deep Convection Experiment of 1997.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".