Storm surge contributions to flood hazards on Canada's Atlantic Coast
Bibliographic record
Abstract
Abstract A numerical hydrodynamic model was used to simulate the generation and evolution of storm surges in Atlantic Canada in response to synoptic‐scale surface wind and atmospheric pressure fields. The modelling was conducted as part of a broader initiative to support community‐scale inundation modelling and coastal flood risk assessment for communities located in the Acadian Peninsula region of New Brunswick. The 44 largest storm surge events on record at a tide gauge proximate to the region of interest were simulated using the numerical model. Initially, a comparison between simulated storm surges and peak non‐tidal residuals from tide gauge records showed relatively poor agreement, producing an R2 value of 0.403. Model skill was improved by incorporating the influence of sea ice cover on air‐sea momentum transfer in the hydrodynamic model, and improved correlation with measured residuals was obtained by adding estimates of wave set‐up to the predicted storm surges, ultimately resulting in an R2 value of 0.803. The results of the simulations provided a basis for identifying distinct regional factors affecting storm surges and water level residuals and demonstrated conditions where wave set‐up and sea ice cover play an important role in contributing to extreme high water levels.
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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 | 0.001 | 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".