Estimation of extreme sea levels over the eastern continental shelf of North America
Bibliographic record
Abstract
[1] This study presents distributions of extreme sea levels over the eastern continental shelf of North America (ECSNA) associated with storm surges and tidal surface elevations produced by a 2-D ocean circulation model for the period 1979–2010. The 2-D circulation model is driven by atmospheric and tidal forcing. The large-scale atmospheric forcing is the wind stress and sea level atmospheric pressures extracted from NCEP (National Centers for Environmental Prediction) Climate Forecast System Reanalysis (CFSR) fields at 6 h intervals. A parameterized vortex is inserted into the CFSR fields to better represent the atmospheric forcing associated with a tropical storm or hurricane. The tidal forcing includes specification of tides at model open boundaries and tide generating potential at each model grid. The model performance is assessed using observed sea levels over the ECSNA. The simulated surface elevations driven by the atmospheric force are used to estimate the 50 year return level of extreme sea levels associated with storm surges over the ECSNA using an extremal analysis. The potential regions of the ECSNA to be threatened by severe storm surges are presented. The extreme total sea levels due to tides and storm surges are also estimated using the Monte Carlo method from model results. Regions over the ECSNA experiencing severe 50 year extreme total sea levels due to the storm surges and tides are similar to those regions of 50 year extreme surge-induced elevations, but with much higher extreme values.
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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".