Bibliographic record
Abstract
This thesis examines effects of wave-current interactions (WCIs) on surface gravity waves and ocean currents over the eastern Canadian coastal and shelf waters using a coupled wave-circulation numerical model. The coupled model consists of a three-dimensional (3D) circulation model and a third-generation wave model. Comparisons of model results with in-situ oceanographic observations made with buoys and ADCPs and remote sensing measurements from satellites and high frequency (HF) radars demonstrate that the inclusion of WCIs in the coupled model significantly improves the model performance in simulating ocean waves, currents and hydrography over coastal and shelf waters, particularly during extreme weather events. The important WCI mechanisms on the 3D ocean currents examined in this study include the 3D wave force, breaking wave-induced mixing, and wave-induced vertical Reynolds stress. The research results demonstrate that the vortex force formulation, with a separation of the 3D wave force into conservative (vortex force and Bernoulli head) and non-conservative (breaking wave-induced acceleration) contributions, performs better than the radiation stress formulation in simulating the wave-induced 3D ocean currents over coastal waters under hurricane conditions. Furthermore, the 3D wave force and breaking wave-induced mixing are found to improve the model performance in simulating the storm-induced sea surface temperature changes. The research results also demonstrate that the wave-induced vertical Reynolds stress is an important process for transferring the wind momentum to the water column in addition to the turbulent Reynolds stress. The important WCI mechanisms on surface gravity waves during storm events include the relative wind effect, current-induced convergence and refraction, which collectively result in different wave responses on the two sides of the storm track. Significant wave modulations by the hurricane-induced near-inertial currents and semidiurnal tidal currents are also demonstrated based on analyses of both observations and numerical model results. Tidal modulations in the Gulf of Maine are mainly due to the strong horizontal gradients of tidal currents near the mouth of the Gulf, resulting in great effects of current-induced convergence, refraction and wavenumber shift. In addition, the current-enhanced dissipation becomes important during high winds by reducing the magnitude of the tidal modulation.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".