Impacts of Extratropical Transition on Tropical Cyclone Tornadoes
Bibliographic record
Abstract
The impact of extratropical transition (ET) on tropical cyclone (TC) tornadoes is not fully understood with no prior tornado climatologies for ET cases. Hence, this study investigates how ET impacts tornadoes and convective-scale environments within TCs using multidecadal tornado and radiosonde data from North Atlantic TCs. This study divides ET into three phases: tropical (i.e., pre-ET), transition (i.e., during ET), and extratropical (i.e., post-ET). These results show that the largest portion of tornadoes occur before and during ET, with the greatest frequencies during ET. As TCs undergo and complete ET, tornadoes tend to shift geographically north and east, farther south or more strongly downshear right relative to the TC center, occur later in the day, and are more likely to be associated with greater damage. Evaluation of radiosondes showed that the downshear right quadrant of the TC is frequently the most favorable for tornado production, having the best combination of entrainment CAPE (ECAPE) and storm-relative helicity (SRH) values. Specifically, the downshear right quadrant shows slower decreases in ECAPE (associated with large-scale cooling/drying) and increased low-level shear/SRH through ET, relative to quadrants left of the deeptropospheric (i.e.., 850-200-hPa) vertical wind shear vector. These results have ramifications for the physical model and prediction of ET-related TC evolution, both in terms of their environment and subsequent hazard production Suggested Reviewers:
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".