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Record W2122376411 · doi:10.1175/2010jas3500.1

On the Dynamics of Two-Dimensional Hurricane-like Concentric Rings Vortex Formation

2010· article· en· W2122376411 on OpenAlexaff
Yosvany Martinez, Gilbert Brunet, M. K. Yau

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsMcGill UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsEyeRossby waveVorticityTropical cycloneVortexPotential vorticityPhysicsRADIUSVortex ringGeologyConcentricMechanicsMeteorologyAtmospheric sciencesGeometryMathematics

Abstract

fetched live from OpenAlex

Abstract Despite the fact that asymmetries in hurricanes (e.g., spiral rainbands, polygonal eyewalls, and mesovortices) have long been observed in radar and satellite imagery, many aspects of their dynamics remain unsolved, particularly in the formation of the secondary eyewall. The underlying associated dynamical processes need to be better understood to advance the science of hurricane intensity forecasting. To fill this gap, a simple 2D barotropic “dry” model is used to simulate a hurricane-like concentric rings vortex. The empirical normal mode (ENM) technique, together with Eliassen–Palm (EP) flux calculations, are used to isolate wave modes from the model datasets to investigate their impact on the changes in the structure and intensity of the simulated hurricane-like vortex. From the ENM diagnostics, it is shown that asymmetric disturbances outside a strong vortex ring with a large vorticity skirt may relax to form concentric rings of enhanced vorticity that contain a secondary wind maximum. The fact that the critical radius for some of the leading modes is close to the location where the secondary ring of enhanced vorticity develops suggests that a wave–mean flow interaction mechanism based on vortex Rossby wave (VRW) dynamics may explain important dynamical aspects of concentric eyewall genesis (CEG).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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

Citations36
Published2010
Admission routes1
Has abstractyes

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