The impacts of climate change on tropical-to-extratropical transitions in the North Atlantic Basin
Bibliographic record
Abstract
Abstract. As tropical cyclones migrate toward mid-latitudes, they can transform into extratropical cyclones, a process known as extratropical transition. In the North Atlantic Basin, nearly half of hurricanes undergo this transition. After transitioning, these storms can reintensify, posing significant threats to populations and infrastructure along the eastern coast of North America. While the impacts of climate change on hurricanes have been extensively studied, there remain uncertainties about its effects on extratropical transitions. This study aims to assess how climate change affects the frequency, location, intensity, and duration of these transitions. To achieve this, high-resolution regional simulations from an atmospheric regional climate model, based on the Representative Concentration Pathways 8.5 (RCP8.5) emissions scenario, were used to compare two 30-year periods: the present (1990–2019) and the end of the century (2071–2100). The results indicate a projected decrease in the number of tropical hurricanes, with no significant change in extratropical transition rates. September and October continue to be the primary months for extratropical transitions. However, the season's peak appears to have shifted from September to October, suggesting that large-scale environmental conditions may become more favourable for extratropical transitions in October in the future. Although a poleward shift in the maximum intensity of tropical hurricanes is detected, the average latitude of the transitions does not change. Our findings suggest that transitioning storms will be more intense in the future, despite a less baroclinic atmosphere, due to a stronger contribution from latent heat transfer. However, the risk of reintensification after transition is not expected to increase.
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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 | 0.000 | 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 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".