Categorization of High‐Wind Events and Their Contribution to the Seasonal Breakdown of Stratification on the Southern New England Shelf
Bibliographic record
Abstract
Abstract High‐wind events predominantly cause the rapid breakdown of seasonal stratification on the continental shelf by the end of October. In particular the timing of events leads to considerable interannual variability in the stratification breakdown with a standard deviation of 15 days. Although previous studies have shown how coastal stratification depends on local wind‐forcing characteristics, the locally observed ocean forcing has not yet been linked to regional atmospheric weather patterns that determine the local wind characteristics. Establishing such a connection is a necessary first step toward examining how an altered atmospheric forcing due to climate change affects coastal ocean conditions. Here, we propose a categorization scheme for high‐wind events that links atmospheric forcing patterns with changes in stratification. We apply the scheme to the Southern New England shelf utilizing observations from the Ocean Observatories Initiative Coastal Pioneer Array (2015–2022). Impactful wind forcing patterns occur predominantly during early fall, have strong downwelling‐favorable winds, and are primarily of two types: (a) Cyclonic storms that propagate south of the continental shelf causing anticyclonically rotating winds, and (b) persistent large‐scale high‐pressure systems over East Canada causing steady north‐easterly winds. These patterns are associated with opposite temperature and salinity contributions to destratification, implying differences in the dominant processes driving ocean mixing based on a high‐wind pattern's overall strength and wind direction steadiness. The high‐wind event categorization scheme allows a transition from solely focusing on local wind forcing to considering realistic atmospheric weather patterns when investigating their impact on stratification in the coastal ocean.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".