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Record W2306464933 · doi:10.1175/jas-d-15-0237.1

On the Dynamics of the Formation of the Kelvin Cat’s-Eye in Tropical Cyclogenesis. Part II: Numerical Simulation

2016· article· en· W2306464933 on OpenAlexafffund
Ali Asaadi, Gilbert Brunet, M. K. Yau

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsEnvironment and Climate Change CanadaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsPotential vorticityMechanicsDiabaticZonal and meridionalConvectionCyclogenesisNonlinear systemJet (fluid)Perturbation (astronomy)VortexAtmospheric sciencesVorticityClassical mechanicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract A shallow-water model is used to study the role of critical layers in tropical cyclogenesis. Forced and unforced problems of disturbances on a parabolic jet associated with weak basic-state meridional potential vorticity (PV) gradients, leading to Kelvin cat’s-eye formation around the jet axis, are first investigated. Numerical simulations with various initial disturbance magnitudes and structures suggest that the results of previous studies can be extended to the next level of complexity toward the more realistic atmosphere. The model is therefore initialized using an observed jet profile obtained from the reanalysis data presented in Part I of this study. For this asymmetric marginally stable basic-state profile, unforced (free) and forced linear integrations show spatial contraction of the perturbation structures in the meridional direction, similar to what occurred in experiments on the parabolic jet. Nonlinear free simulations highlight the role of nonlinear processes in redistributing PV within the critical-layer region. However, they do not yield a realistic time scale for the formation of the cat’s-eye. By including diabatic heating as a mass sink term to represent convective PV generation, the nonlinear forced simulation is found to produce a realistic time scale for cat’s-eye formation, and confirms the analytical solution of τeτQ ~ O(ε−1) obtained in Part I. These results highlight the synergic role of the dynamical mechanisms, including wave breaking and PV redistribution within the nonlinear critical layer characterized by weak PV gradients and the thermodynamical mechanisms such as convectively generated PV anomalies in the cat’s-eye formation in tropical cyclogenesis.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2016
Admission routes2
Has abstractyes

Explore more

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