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Record W125820996 · doi:10.82308/50966

Numerical study of a tornado-like vortex in a supercell storm

2008· article· en· W125820996 on OpenAlexafffund
Jorge Ruben Santos

Bibliographic record

VenueeScholarship@McGill (McGill) · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsMcGill University
FundersCanadian Foundation for Climate and Atmospheric SciencesMcGill University
KeywordsTornadoSupercellStormMeteorologyMesocycloneEyeVortexGeologyComputer scienceGeographyTelecommunications

Abstract

fetched live from OpenAlex

Recent observations and numerical simulations have significantly improved our understanding of tornadic storms. However, our knowledge of tornado-genesis remains rudimentary. Necessary atmospheric conditions favoring the formation of tornadoes in supercell storms are known, but sufficient conditions remain elusive. The underlying reason is that the processes involved in environment-storm and storm-tornado interactions are not fully understood, as numerical models in the past lacked sufficient resolution to resolve these interactions satisfactorily. In this thesis, an attempt is made to fill this gap by performing a multi-grid high resolution simulation of a supercell storm spawning a tornado-like vortex. Four grids, with grid sizes of 600 m, 200 m, 70 m, and 30 m, are used to allow explicit simulation of storm-tornado interactions. Diagnostic analysis of the modeling results allows an investigation of the origin of rotation at both the storm scale and the tornado scale. The simulation results showed that the origin of vertical rotation at storm scale during the early stage of storm development is due to tilting of the horizontal vorticity in the environment. This so called mesocyclone then further strengthens by the mechanism of stretching and Dynamic Pipe Effect and descends downwards. During the time of mesocyclone intensification, incipient surface vertical vortices form along the outflow boundary created by the rear flank downdraft due to the process of horizontal shear instability. One of the surface vortices experiences an initial exponential growth in its vorticity by interacting with the descending mesocyclone and merging with multiple smaller satellite vortices. The tornado-like vortex (TLV) which forms has a maximum horizontal wind of 103 m s-1 and a minimum central pressure of 927 hPa. Vorticity budgets of the mesocyclone and the TLV are computed to assess quantitatively the importance of various processes for rotation. Sensitivity experiments were also performed to determine the effect of varying the environmental conditions on the mesocyclone and surface vorticity. It was found that as the low-level vertical shear of the environmental wind increases, the mesocyclone intensifies and favors the intensification of near surface vorticity. The presence of drier layers in the upper and middle troposphere eventually produces a weaker mesocyclone and weaker outflow boundaries. On the other hand, inclusion of the ice phase processes produces a stronger mesocyclone and more intense outflow boundaries to enhance the intensification of near surface vorticity.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.226
Teacher spread0.189 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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