Using atmospheric model output to simulate the meteorological tsunami response to Tropical Storm Helene (2000)
Bibliographic record
Abstract
In the fall of both 1999 and 2000, unexpected “rapid tides” occurred along the coast of the Avalon Peninsula of Newfoundland. These rapid tides have been linked to the passing of Tropical Storm Jose (1999) and Tropical Storm Helene (2000) over the Grand Banks. Here we examine the dynamic ocean response to Tropical Storm Helene (2000) using a barotropic shallow water ocean model forced by atmospheric pressure and surface winds derived from a simulation of Helene using a dynamical model of the atmosphere. The ocean model is able to capture the main features of the observed response at the coast of Newfoundland as seen in the available tide gauge data. Results show that the simulated sea level response at the coast is driven by a combination of wind stress and atmospheric pressure forcing, the former generally dominating. An exception is Conception Bay, Newfoundland, where the response is captured mainly by atmospheric pressure forcing. Offshore near the edge of the Grand Banks, atmospheric pressure and wind stress forcing are equally important. The wind‐forced response depends on the divergence of the surface wind stress and hence on the structure of the storm in the atmospheric model simulation. Sensitivity studies show the importance of having a small time interval (on the order of minutes) at which the atmospheric forcing is supplied to the ocean model and show the importance of the location of the storm track.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".