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Record W2795967153 · doi:10.1175/jpo-d-17-0160.1

Extraction of Potential Energy from Geostrophic Fronts by Inertial–Symmetric Instabilities

2018· article· en· W2795967153 on OpenAlexafffund
Nicolas Grisouard

Bibliographic record

VenueJournal of Physical Oceanography · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsGeostrophic windIsopycnalRichardson numberRossby numberFrontogenesisGeologyInertial waveStratification (seeds)Hydrostatic equilibriumRossby radius of deformationBalanced flowMechanicsPotential vorticityPhysicsBaroclinityTurbulenceClimatologyVorticityMesoscale meteorologyVortexOceanography

Abstract

fetched live from OpenAlex

Abstract Submesoscale oceanic density fronts are structures in geostrophic and hydrostatic balance, which are prone to inertial and/or symmetric instabilities. We argue in this article that drainage of potential energy from the geostrophic flow is a significant source of their growth. We illustrate our point with two-dimensional Boussinesq numerical simulations of oceanic density fronts on the f plane. A set of two-dimensional initial conditions covers the submesoscale portion of a three-dimensional parameter space consisting of the Richardson and Rossby numbers and a measure of stratification or latitude. Because we let the lateral density gradient decay with depth, the parameter space map is nontrivial, excluding low-Rossby, low-Richardson combinations. Dissipation and the presence of boundaries select a growing mode of inertial–symmetric instability consisting of flow cells that disturb isopycnal contours. Systematically, these isopycnal displacements correspond to a drainage of potential energy from the geostrophic fronts to the ageostrophic perturbations. In the majority of our experiments, this energy drainage is at least as important as the drainage of kinetic energy from the front. Various constraints, some physical, some numerical, make the energetics in our experiments more related to inertial rather than symmetric instabilities. Our results depend very weakly on the Richardson number and more on the Rossby number and relative stratification.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Citations25
Published2018
Admission routes2
Has abstractyes

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