Double Acceleration Effects of Closely Spaced Pairs of Ocean Fronts on High‐Wind Occurrence Frequency During Boreal Winter
Bibliographic record
Abstract
Abstract Previous studies have found that sea surface temperature (SST) fronts have significant impacts on high‐wind frequency. Strong winds over the mid‐latitude North Pacific and North Atlantic Oceans occur frequently downstream of SST fronts in boreal winter. An SST front can significantly increase the instability of the marine atmospheric boundary layer, which accelerates the wind on the warmer flank. This study uses satellite observations to examine the “double acceleration” effects of closely spaced paired fronts (with interfrontal distances of 300–1,000 km) on high‐wind occurrence frequency in the Pacific subarctic frontal zone east of Japan and over the Atlantic Ocean east of Newfoundland. During boreal winter each year, mean westerly winds frequently cross two or more closely spaced SST fronts, with probabilities of 85% over the North Pacific and 87% over the North Atlantic. Over the warmer flank of the first front, the average high‐wind occurrence frequency (wind speed) increases due to the vertical‐mixing mechanism. Downstream of the second front, average high‐wind occurrence frequency (wind speed) reaches maxima of ∼9% (11.5 m s−1) over the Pacific and ∼11.5% (12 m s−1) over the Atlantic. Stronger westerly winds lead to greater high‐wind frequency. The first front contributes to the observed high winds downstream of the second front due to little friction and suppression of upward vertical momentum transfer between paired fronts.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".