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Record W4408095726 · doi:10.5539/esr.v14n1p18

Some Common Ingredients for Tornadogenesis Associated with Landfalling Tropical Cyclones Impinging on Frontal Boundaries

2025· article· en· W4408095726 on OpenAlexvenueno aff
Dicky Lee Armstrong, Yuh‐Lang Lin

Bibliographic record

VenueEarth Science Research · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsnot available
Fundersnot available
KeywordsTropical cycloneTornadoSevere weatherMeteorologyClimatologyGeologyGeographyStorm

Abstract

fetched live from OpenAlex

Landfalling Tropical Cyclones (TCs) may induce tornadoes, while less frequent than their midwestern counterparts, are still able to produce the damage potential leading to additional billion-dollar costs. This research seeks to find some common ingredients for tornadogenesis associated with landfalling TCs impinging on synoptic frontal boundaries, during which the TC’s circulation has been strongly affected on both the vorticity, upward velocity, and other surrounding environmental, convective, and tornadic parameters. This research found that by increasing the vorticity and vertical velocity associated with a cold frontal boundary, moving or stalled, and placing it into a moist convectively primed environment surrounding the TC increases the chance for a tornado outbreak to occur. The most frequent outbreaks occur when a cold frontal boundary has a direct interaction with the circulation of an approaching TC, such as seen in Hurricane Michael (2018) when it was moving through North Carolina (NC) Piedmont into the Virginian Coastal Plains. In this case, the vorticity, surface moisture, vertical velocity, and surface convergence are all observed to have modestly large increases leading to the environment conducive to tornadogenesis. This prefrontal environment also has an area of moderate to large Convectively Available Potential Energy (CAPE) with values over 500 J kg-1 as well as Potential Instability (PI) index with the vertical gradient of potential temperature (∂θ/∂z) becoming negative. Storms interacting with a stalled frontal boundary, such as Hurricane Florence (2018), also have this increase in vorticity though to a lesser extent. During the interaction with Florence vorticity peaked in southeast NC and northeast South Carolina associated with the outer band that was located near the stalled front. This area was in the favorable front right quadrant and experiencing a boost in CAPE from the flow of warm moist air off the Gulf Stream. The main driver of vorticity in this location was mainly due to the vertical vorticity stretching generated by the low-level flow convergence associated with the interaction of the flow around the TC and the stalled front, which occurred over the southern coastal areas of NC. In the case of tornado outbreaks not associated with a frontal boundary, such as Hurricane Allen (1980), the largest driver tends to be the TC itself with Allen strong vorticity advection, abundant moisture, and large CAPE, from the moist and unstable airstream from the Gulf of Mexico, into southern Texas, a region that is typically favorable for tornado development being near the crossroads of Tornado Alley and Dixie Alley (Klemp, 1987), a zone that frequently combines the conditions needed for tornadogenesis with hot dry air from the north and west meeting warm moist air from the south and east.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.341
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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