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Record W2990573264 · doi:10.1175/jpo-d-18-0265.1

Measurements of Enhanced Near-Surface Turbulence under Windrows

2019· article· en· W2990573264 on OpenAlexafffundabout
Seth Zippel, Ted Maksym, Malcolm E. Scully, Peter Sutherland, Dany Dumont

Bibliographic record

VenueJournal of Physical Oceanography · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsUniversité du Québec à Rimouski
FundersAgence Nationale de la RechercheCentre National d’Etudes SpatialesMarine Environmental Observation Prediction and Response NetworkAndrew W. Mellon Foundation
KeywordsAdvectionTurbulenceAtmospheric sciencesTurbulence kinetic energyFlux (metallurgy)DissipationGeologyEnvironmental sciencePhysicsMechanicsMaterials science

Abstract

fetched live from OpenAlex

Abstract Observations of waves, winds, turbulence, and the geometry and circulation of windrows were made in a shallow bay in the winter of 2018 outside of Rimouski, Québec. Water velocities measured from a forward-looking pulse-coherent ADCP mounted on a small zodiac show spanwise (cross-windrow) convergence, streamwise (downwind) velocity enhancement, and downwelling in the windrows, consistent with the view that windrows are the result of counterrotating pairs of wind-aligned vortices. The spacing of windrows, measured with acoustic backscatter and with surface imagery, was measured to be approximately twice the water depth, which suggests an aspect ratio of 1. The magnitude and vertical distribution of turbulence measured from the ADCP are consistent with a previous scaling and observations of near-surface turbulence under breaking waves, with dissipation rates larger and decaying faster vertically than what is expected from a shear-driven boundary layer. Measurements of dissipation rate are partitioned to within, and outside of the windrow convergence zones, and measurements inside the convergence zones are found to be nearly an order of magnitude larger than those outside with similar vertical structure. A ratio of time scales suggests that turbulence likely dissipates before it can be advected horizontally into convergences, but the advection of wave energy into convergences may elevate the surface flux of TKE and could explain the elevated turbulence in the windrows. These results add to a limited number of conflicting observations of turbulence variability due to windrows, which may modify gas flux, and heat and momentum transport in the surface boundary layer.

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 score0.370
Threshold uncertainty score0.394

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 head0.013
GPT teacher head0.220
Teacher spread0.206 · 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

Citations18
Published2019
Admission routes3
Has abstractyes

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