Storm Surge and Surface Waves in a Shallow Lagoonal Estuary during the Crossing of a Hurricane
Bibliographic record
Abstract
Tropical cyclones deliver intense winds that can generate some of the most severe surface wave and storm surge conditions in the coastal ocean. Hurricane Irene (2011) crossed a large, shallow lagoonal estuarine system in North Carolina, causing flooding and erosion of the adjacent low-lying coastal plain and barrier islands. This event provided an opportunity to improve understanding of the estuarine response to strong and rotating wind forcing. Observations from acoustic sensors in subestuaries and water-level elevation measurements from a network of pressure sensors across the system are presented. Data are examined with two modeling techniques: (1) a simple numerical approach using a momentum balance between the wind stress, flow acceleration, pressure gradient, and bottom friction that gives insight into temporal variability in water levels through the passage of the storm; and (2) an advanced hydrodynamic model based on the full shallow water fluid momentum equations, coupled to a spectral surface wave model that accounts for the spatially varying bathymetry and wind field. The results indicate that both wind-generated surface waves and the wind-driven storm surge are important contributors to the total water surface elevations that induce flooding along estuarine shorelines under strong hurricane forcing.
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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) | 0.001 | 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".