Internal Tide Generation in Semienclosed Ocean Basins
Bibliographic record
Abstract
Abstract When they interact with topography in the presence of stratification, astronomically driven barotropic tides lose part of their energy to internal tides. Many numerical and observational studies on internal tide generation have focused on either generation at ocean ridges and isolated topographical features or generation at the open coast but not in semienclosed basins. Because of their long wavelengths, potentially comparable to horizontal basin scales, internal tides may be resonant with natural basin modes, which could explain previous observations of large-amplitude internal tides in some basins. Yet, what is an appropriate basin geometry to elicit a resonant response is poorly understood. Vertical stratification and its interaction with coastal bathymetry are likely to have a significant impact on the generation and dynamics of internal waves. Here, we conduct a series of idealized 3D numerical simulations of semienclosed, continuously vertically stratified rotating basins with shelf bathymetry along the perimeter of the basin. We force these basins with a periodic barotropic coastal Kelvin wave to investigate under what physical characteristics of a basin are resonant baroclinic modes generated. Through our parameter sweep, we identify relevant nondimensional parameters that can be used to find characteristics of a basin resonant to a particular frequency. An important result from this study is that, in the presence of basin shelf bathymetry, coupling between basin modes and coastal trapped waves strongly modifies the dynamics of the resonant response.
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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 | 0.001 | 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".