Advancing global hindcast of extreme sea levels: Insights from a 65-year study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Extreme sea levels (ESLs) are a leading cause of coastal hazards. Assessing risks and associated impacts requires reliable ESL statistics. These are typically derived from long but sparsely available tide-gauge records or through records obtained from long hindcasts. Here we present a 65-year global hindcast of hourly total sea levels that dynamically includes contributions from storm surges, tides, changes in water density (or baroclinicity) and their interactions. Evaluation shows good agreement between modelled and available observed sea levels, including extremes driven by extratropical and tropical cyclones. Significant improvements over other simulations result from our efforts in addressing underestimated reanalysis winds and incorporating baroclinicity, both of which have been overlooked in other global studies. The improvements can translate into reductions of return periods for given critical levels by decades. We therefore provide improved global estimates of ESL. In a first step toward developing seasonal forecast of flood risk, we also quantified ENSO-induced ESL modulations. The modulations show coherent spatial variabilities, consistent with ENSO-induced changes in the atmosphere and ocean. We also highlight the relevance of the often-overlooked neutral phase in regions where both El Niño and La Niña may suppress sea level variabilities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it