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Record W4394755413 · doi:10.1029/2023jd040614

ERA5‐Based Significant Tornado Environments in Canada Between 1980 and 2020

2024· article· en· W4394755413 on OpenAlexafffundabout
John Hanesiak, Mateusz Taszarek, David H. Walker, Chun‐Chih Wang, Daniel Betancourt

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvective available potential energyTornadoWind shearStormSevere weatherClimatologySupercellTroposphereConvective storm detectionConvectionEnvironmental scienceAtmospheric sciencesRadiosondeGeologyMeteorologyGeographyWind speed

Abstract

fetched live from OpenAlex

Abstract This study uses ERA5 close‐proximity soundings and associated convective parameters to characterize significant tornadic storm (F/EF2+) environments between 1980 and 2020 in parts of Canada. It is shown that ERA5 convective parameters are suitable to represent observed parameters, based on radiosonde comparisons. Results indicate that the eastern Canadian Prairies have nearly double the lifted condensation level with higher level of free convection compared to eastern Canada (southern Ontario/Quebec). Eastern Canada has more a humid boundary layer and free troposphere that can lead to warmer cold pools, favoring tornadogenesis. Central Canada (Manitoba) has the largest mixed‐layer (ML) convective available potential energy (CAPE) mainly due to a combination of regional differences in low level moisture and steeper mid‐level lapse rates in western Canada. Central continental U.S. and Canadian regions appear to have the highest (most negative) convective inhibition, leading to more explosive initiation. Mean bulk wind shear and storm relative helicity (SRH) increases from west to east, with eastern regions being significantly larger. The supercell composite and significant tornado parameters are generally less than U.S. magnitudes, particularly in western Canada, and would require recalibration for more practical use in Canada. Overall, western Canada significant tornadic storms are associated with more low‐level looping hodographs and dominated by thermodynamic influences compared to larger wind influences in eastern regions. This is likely due to more spring, late summer, and autumn events that typically have well‐developed synoptic systems (stronger wind shear) with overall less buoyant energy in eastern regions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.281
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations9
Published2024
Admission routes3
Has abstractyes

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