Shear instability in the St. Lawrence Estuary, Canada: A comparison of fine‐scale observations and estuarine circulation model results
Bibliographic record
Abstract
A three‐dimensional numerical model was used to predict the timing and the location of shear instabilities in the St. Lawrence Estuary. This model suggests that significant mixing occur during flood tides in the upper estuary. This mixing is associated with a strong bottom density current made of the cold Gulf of St. Lawrence intermediate waters flowing under the St. Lawrence mixed surface waters. Guided by these results, a field experiment was undertaken in summer 1997 to verify this and to document the conditions that favor the development of instabilities. The instabilities were found as predicted and documented from acoustic imaging, current profiler, and density measurements. The instabilities first develop in the form of wavelike disturbances before they break, like Kelvin‐Helmholtz instabilities. The unstable waves have wavelength of ≈140–150 m and extend vertically between 10 and 25 m. The fine‐scale observations of the semidiurnal evolution of the vertical structure of currents and density at the experimental site are compared with the numerical results. The model reproduces accurately the tidal variability of the currents but underestimates by a factor of 2 the amplitude of the density fluctuations. The general patterns of the shear squared S2 and the buoyancy frequency squared N2 are reasonably well reproduced by the model, but their intensities are ≈2 times smaller than the observations. This difference is attributed to the limited vertical resolution of the model at the pycnocline. However, the modeled Richardson numbers, Ri ≡ N2S−2, are reasonably well reproduced and appeared to be useful for the prediction of instabilities in such a complex environment.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".