Sizing the largest ocean waves using the SWOT mission
Bibliographic record
Abstract
Winds generate waves over the oceans with a wide range of properties. The largest wave heights and periods are important parameters in the design of marine structures. Extreme waves also play an outsize role in air-sea fluxes and coastal dynamics, and leave imprints on seismic and sediment records. Rare events have so far escaped measurements, with few wave heights from satellite altimeters exceeding 16 m, and no associated measurement of wave periods. Here, we use swells radiated from storms to reveal long wave periods within the storms, and their generation mechanism. Swells are resolved in the Surface Water and Ocean Topography (SWOT) satellite sea level measurements. Patterns of increasing swell wavelength and decreasing swell height away from storms are consistent with a nonlinear transfer of energy from short to long period waves. We propose an updated parametric shape for wave spectra in storms that aligns with SWOT swell measurements. It reduces energy levels by a factor of 20 at 1.2 to 1.4 times the peak period compared to commonly used spectral shapes and allows estimation of storm wave periods from swell heights. Consistent with less extreme conditions, the peak period generally increases with wave height. This was particularly verified for the largest storm peak period of 20.2 [Formula: see text] 0.6 s, obtained for the event with the largest significant wave height 19.7 [Formula: see text] 0.3 m measured by altimeters. These observations of long period swells should have a wide range of applications from coastal dynamics to seismology.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".