Measurements of shoaling internal waves and turbulence in an estuary
Bibliographic record
Abstract
Abstract The shoaling of horizontally propagating internal waves may represent an important source of mixing and transport in estuaries and coastal seas. Including such effects in numerical models demands improvements in the understanding of several aspects of the energetics, especially those relating to turbulence generation, and observations are needed to build this understanding. To address some of these issues in the estuarine context, we undertook an intensive field program for 10 days in the summer of 2008 in the St. Lawrence Estuary. The sampling involved shore‐based photogrammetry, ship‐based surveys, and an array of moorings in the shoaling region that held both conventional and turbulence‐resolving sensors. The measurements shed light on many aspects of the wave shoaling process. Wave arrivals were generally phase‐locked with the M2 tide, providing hints about far‐field forcing. In the deeper part of the study domain, the waves propagated according to the predictions of linear theory. In intermediate‐depth waters, the waves traversed the field site perpendicularly to isobaths, a pattern that continued as the waves transformed nonlinearly. Acoustic Doppler velocimeters permitted inference of the turbulent energetics, and two main features were studied. First, during a period of shoaling internal waves, turbulence dissipation rates exceeded values associated with tidal shear by an order of magnitude. Second, the evolving spectral signatures associated with a particular wave‐shoaling event suggest that the turbulence is at least partly locally generated. Overall, the results of this study suggest that parameterizations of wave‐induced mixing could employ relatively simple dynamics in deep water, but may have to handle a wide suite of turbulence generation and transport mechanisms in inshore regions.
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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 | 0.000 |
| 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 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".