Extratropical storm inundation testbed: Intermodel comparisons in Scituate, Massachusetts
Bibliographic record
Abstract
[1] The Integrated Ocean Observing System Super-regional Coastal Modeling Testbed had one objective to evaluate the capabilities of three unstructured-grid fully current-wave coupled ocean models (ADCIRC/SWAN, FVCOM/SWAVE, SELFE/WWM) to simulate extratropical storm-induced inundation in the US northeast coastal region. Scituate Harbor (MA) was chosen as the extratropical storm testbed site, and model simulations were made for the 24–27 May 2005 and 17–20 April 2007 (“Patriot's Day Storm”) nor'easters. For the same unstructured mesh, meteorological forcing, and initial/boundary conditions, intermodel comparisons were made for tidal elevation, surface waves, sea surface elevation, coastal inundation, currents, and volume transport. All three models showed similar accuracy in tidal simulation and consistency in dynamic responses to storm winds in experiments conducted without and with wave-current interaction. The three models also showed that wave-current interaction could (1) change the current direction from the along-shelf direction to the onshore direction over the northern shelf, enlarging the onshore water transport and (2) intensify an anticyclonic eddy in the harbor entrance and a cyclonic eddy in the harbor interior, which could increase the water transport toward the northern peninsula and the southern end and thus enhance flooding in those areas. The testbed intermodel comparisons suggest that major differences in the performance of the three models were caused primarily by (1) the inclusion of wave-current interaction, due to the different discrete algorithms used to solve the three wave models and compute water-current interaction, (2) the criterions used for the wet-dry point treatment of the flooding/drying process simulation, and (3) bottom friction parameterizations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".