An Investigation of Tropical Cyclone Development Pathways as an Indicator of Extratropical Transition
Bibliographic record
Abstract
A significant fraction of tropical cyclones develop in baroclinic environments, following tropical cyclogenesis “pathways” that are characterized by dynamical processes often associated with higher latitudes. This study investigates whether such storms are more likely to undergo subsequent extratropical transition than those that develop in more typical, non-baroclinic environments. We consider tropical cyclones globally in the period 1979-2011 using best-track datasets, and define the genesis pathway of each storm using McTaggart-Cowan's classification: non-baroclinic, low-level baroclinic, trough-induced, weak and strong tropical transition. In each basin, we analyze the total number and the fraction of storms that underwent extratropical transition, their seasonality, and storm tracks, according to their genesis pathways. The relationship between the pathways and extratropical transition is statistically significant in the North Atlantic and Western North Pacific, where the strong tropical transition and the trough-induced pathways have a significantly greater extratropical fraction compared to all other pathways, respectively. Latitude, longitude and environmental factors such as sea surface temperature and vertical shear were further analyzed to explore whether storms in these pathways happen to be in environments conducive to extratropical transition, or whether a “memory” of the genesis pathway persists throughout the storm life cycle. After controlling for genesis latitude, the relationship between the strong tropical transition and trough induced pathways, and extratropical transition occurrence remains statistically significant, implying a lasting effect from the pathway on the probability of an eventual extratropical transition.
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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 | 0.000 | 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".