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Record W3006606917

Enhanced turbulence associated with the diurnal jet in the ocean surface boundary layer

2016· article· en· W3006606917 on OpenAlexaff
Graig Sutherland, L. Marié, G. P. Reverdin, Kai H. Christensen, Göran Broström, Brian Ward

Bibliographic record

VenueAGUOS · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsDiurnal cycleStratification (seeds)Atmospheric sciencesTurbulenceDiurnal temperature variationWind shearWind stressBoundary layerEnvironmental scienceSurface layerWind speedClimatologyGeologyOceanographyMeteorologyMechanicsPhysicsMaterials scienceLayer (electronics)
DOInot available

Abstract

fetched live from OpenAlex

AbstractDetailed observations of the diurnal jet, a surface intensification of the wind-driven current associated with the diurnal cycle of sea surface temperature (SST), were obtained during August and September 2012 in the subtropical Atlantic. A diurnal increase in SST of 0.2° to 0.5°C was observed, which corresponded to a diurnal jet of 0.15 m s−1. The increase in near-surface stratification limits the vertical diffusion of the wind stress, which in turn increases the near-surface shear. While the stratification decreased the turbulent dissipation rate e below the depth of the diurnal jet, there was an observed increase in e within the diurnal jet. The diurnal jet was observed to increase the near-surface shear by a factor of 5, which coincided with enhanced values of e. The diurnal evolution of the Richardson number, which is an indicator of shear instability, is less than 1, suggesting that shear instability may contribute to near-surface turbulence. While the increased stratification due to the diu...

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 score0.008
Threshold uncertainty score0.420

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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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