Tide‐surge interaction off the east coast of Canada and northeastern United States
Bibliographic record
Abstract
Sea level observations and a dynamical model are used to investigate tide‐surge interaction in the coastal waters off the east coast of Canada and northern USA. The study is motivated in part by the need to improve operational forecasts of total water level and coastal flooding. Two statistical methods are used to search for evidence of tide‐surge interaction in hourly sea level records from 23 coastal locations. The methods are based on comparison of the statistical properties of the sea level residuals (observed sea level minus tide) occurring at different stages of the tidal cycle. While recognizing the limitations of such an approach, it is concluded that tide‐surge interaction does occur in the Northumberland Strait which is located in the southern Gulf of St. Lawrence. Results for the Gulf of Maine and Bay of Fundy are less conclusive. A dynamical model is also used to quantify tide‐surge interaction in the study region and to identify its physical causes. Tide‐surge interaction in the model is strongest in the Northumberland Strait where the amplitude of the effect can reach 20 cm during and following strong storm surge events. This is large enough to be of practical significance in terms of flood forecasting. A series of sensitivity experiments with the model shows that the nonlinear parameterization of bottom stress is the principal contributor to tide‐surge interaction.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".