The Contributions to Storm Tides in Pacific Northwest Estuaries: Tillamook Bay, Oregon, and the December 2007 Storm
Bibliographic record
Abstract
Cheng, T.K.; Hill, D.F., and Read, W., 2015. The contributions to storm tides in Pacific Northwest estuaries: Tillamook Bay, Oregon, and the December 2007 storm.The December 2007 storm, otherwise known as the Great Coastal Gale of 2007, was a series of extratropical cyclones that brought highly unprecedented wind speeds and precipitation to the Oregon and Washington coasts of the United States. A storm hindcast using the coupled Advanced Circulation (ADCIRC) and Simulating Waves Nearshore (SWAN) models was conducted within Tillamook Bay, Oregon, from 28 November to 5 December 2007. ADCIRC computes two-dimensional circulation forced by astronomic tides, streamflow, and storm surge, while SWAN solves the wave action density equations for radiation stresses. Modeled nontidal residuals were compared to observed data collected by the National Oceanic and Atmospheric Administration at the Garibaldi, Oregon, tide gauge station. The relative contributions of meteorological forcing, offshore waves, and streamflow to storm tides were next assessed at four locations of interest within and outside the estuary by conducting a set of model runs where each major process was omitted in turn. The dominant mechanism for storm tides in the estuary was offshore wave breaking. Streamflow, locally (in estuary) generated waves, and locally generated surge led to minor variations in storm tides in the estuary.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".