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Record W2050584293 · doi:10.1029/2006jc004028

Observation and modeling of surface currents on the Grand Banks: A study of the wave effects on surface currents

2007· article· en· W2050584293 on OpenAlexaffabout
Charlotte Tang, William Perrie, Alastair D. Jenkins, Brendan DeTracey, Yan Hu, B. Toulany, Peter Smith

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsDrifterStokes driftSurface waveMomentum transferWind waveDragMechanicsOcean currentCurrent (fluid)PhysicsWave modelBreaking waveMeteorologyGeologyGeophysicsWave propagationClimatologyOpticsLagrangianOceanography

Abstract

fetched live from OpenAlex

We investigate the effects of surface waves on surface currents using surface drifter data from the Grand Banks and a coupled current‐wave‐drifter model. The theoretical basis of the study is Jenkins' theory of wave‐current interaction in which wind‐generated surface currents are modified by wind‐wave and wave‐current momentum transfers. The total surface current is the sum of the wave modified current, the Stokes drift and the tidal current. Jenkins' formulation was incorporated into the Princeton Ocean Model and applied to the Labrador Sea and the adjacent shelves. The wave energy spectrum from Wavewatch III was used to calculate the momentum transfer and the Stokes drift. A series of model experiments were conducted to simulate the drifter trajectories and examine the sensitivity of the simulations to model parameters. The results show that the Stokes drift is the dominant wave effect, which increases the surface drift speeds by 35% and veers the currents toward the wind directions. The net effect of wind‐to‐wave and wave‐to‐current momentum transfers reduces the surface speeds by a few percent. A statistical analysis of the model currents and drifter data shows that the inclusion of the wave effects improves the model simulations significantly. Model errors due to uncertainties in the model parameters including the eddy viscosity, wave spectrum, air drag of the drifters, and bottom friction are investigated. The model surface currents are shown to be most sensitive to the surface eddy viscosity and the wave energy spectra.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.291
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.078
GPT teacher head0.320
Teacher spread0.242 · 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

Citations48
Published2007
Admission routes2
Has abstractyes

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