Impact of Langmuir Turbulence, Wave Breaking, and Stokes Drift on Upper Ocean Dynamics Under Hurricane Conditions
Bibliographic record
Abstract
Abstract Ocean surface gravity waves can modulate the upper ocean circulation and vertical mixing through air‐sea interactions, wave breaking, Coriolis‐Stokes forcing, Langmuir turbulence and the grid resolved vortex force. However, the roles of these wave induced processes remain uncertain under hurricane conditions. This study examines the impact of these surface wave associated dynamics on the turbulent kinetic energy (TKE), thermal structure and currents in the upper ocean under idealized hurricane forcing using a coupled wave‐circulation model. Eight experiments were conducted with hurricanes moving at three translational speeds. The simulations include two fully coupled experiments and five additional coupled experiments in which wave effects are selectively disabled. All coupled experiments are compared with a baseline circulation simulation. Consistent with previous studies, our results indicate that Langmuir turbulence has the biggest impact on upper ocean currents, temperature and TKE during hurricanes. However, all considered wave effects contribute to vertical mixing and the two‐way fully coupled experiment differs the most from the baseline experiment. The combined wave effects reduce the surface currents by over 0.8 m/s in the front two quadrants of the slow hurricane and enhance the cold wake and near‐surface cooling by as much as 0.6°C, predominantly to the right of the storm track. The wave contributions to the cooling are inversely related to the hurricane translational speed, although their contributions to currents and TKE are correlated with hurricane translational speed. SST differences can alter the latent heat flux driving hurricanes, suggesting that wave dynamics should be included in hurricane forecast models.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".