Application of SWAN model for storm generated wave simulation in the Canadian Beaufort Sea
Bibliographic record
Abstract
The wave model SWAN (Simulating WAves Nearshore) is implemented for the Canadian Beaufort Sea and storm generated waves are investigated through comparisons between in situ buoy observations and numerical simulations. Simulations are performed for four storms using the SWAN wave model. We specifically use SWAN's non-stationary and two-dimensional modes in a fine resolution nested domain within a coarse resolution domain. Two established whitecapping formulations in SWAN are examined; one is dependent on mean spectral wave steepness and the other is on local spectral steepness. Model simulations in the shallow fine resolution domain also consider the effects of bottom friction and nonlinear triad interactions. For the Beaufort Sea study area, wave simulations in which the white capping formulation is dependent on local spectral steepness are better than those where the dependency is on mean spectral steepness; however implementation of bottom friction term and triad mechanisms in the present study does not lead to any notable enhancement in the simulations.
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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 | 0.000 |
| 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".