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Record W4300099911 · doi:10.3402/tellusa.v17i3.9152

Numerical studies of frontal motion in the atmosphere-I

2012· article· en· W4300099911 on OpenAlexfundno aff
Akira Kasahara, Eugene Isaacson, J. J. Stoker

Bibliographic record

VenueTellus A Dynamic Meteorology and Oceanography · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsnot available
FundersCourant Institute of Mathematical Sciences, New York UniversityDivision of Mathematical SciencesYork University
KeywordsGeostrophic windFront (military)Warm frontFrontogenesisCold frontMechanicsAtmosphere (unit)GeologyBoundary layerMeteorologyPhysicsAtmospheric sciences

Abstract

fetched live from OpenAlex

The motion of frontal disturbances in the atmosphere is studied by the numerical solution of differential equations based upon a two-layer model of an incompressible fluid on a rotating earth. The density of each layer is assumed to be constant. The upper and lower fluids correspond respectively to warm and cold air. In this first attempt, only the motion of the lower cold air layer is studied by assuming, in effect, that the dynamics of the perturbations in the upper warm air layer can be neglected. The numerical study of this simple mechanical model shows that even though thermodynamic processes have been ignored, the occlusion process, characteristic for warm and cold fronts, develops from an initially sinusoidal frontal pattern. Two cases of different initial conditions are examined. Case A: Only the east-west component of wind velocity is initially geostrophic. Case B: Both east-west and north-south components are initially geostrophic. In both cases, computations indicate that the cold front propagates faster than the warm front and that a relatively strong mass convergence zone appears behind the cold front only. This fact suggests the occurrence of severe storms associated with cold fronts, but not with warm fronts in the atmosphere. The numerical method developed here to calculate the movement of the front is based on following the motion of the material “particles” at the front. This method has applications to the numerical solution of a certain class of hydrodynamic flow problems in which the entire boundary of the domain of integration is not given a priori, but must be determined (so-called free-boundary problems).

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.658
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.231
Teacher spread0.221 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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