Isopycnal Lagrangian statistics from the North Atlantic Current RAFOS float observations
Bibliographic record
Abstract
One hundred isopycnal floats were tracked on the 27.2 and 27.5 σθ surfaces in the Newfoundland Basin (NFB) from July 1993 to July 1995 to study the current structure and exchanges of waters between the subtropical and subpolar gyres. The float‐mapped mean flow consists of weak flows in the NFB and a strong boundary current (the North Atlantic Current (NAC)), which separates from the boundary at the Northwest Corner, becoming a diffusive zonal drift. The NAC meanders are linked to topography and have similar patterns on the two isopycnals despite the fact that the upper layer velocities are twice as fast as the lower layer ones. Perturbation velocity from the mean is used to compute isopycnal turbulent dispersion and diffusivity. This large data set allows us to resolve a narrow mean NAC and results in a Gaussian turbulence. The turbulence approximately follows the classic Taylor dispersion theory. Integral timescales and length scales and turbulent isopycnal diffusivity are of 1.5–2.5 days, 20–30 km, and (1 − 7) × 103 m2 s−1, respectively. The timescale increases with depth and decreases with latitude, the length scale decreases with depth and longitude, and the diffusivity decreases with depth and from NAC to NFB. Compared to previous results from surface drifters and isobaric floats, our isopycnal statistics are more isotropic and agree better with the Taylor dispersion theory because (1) the mean velocity has a better resolution and (2) the isopycnal floats are better Lagrangian followers. The diffusivity scales better with the rms velocity and length scale than with the velocity variance and timescale.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".