Interaction of Superinertial Waves with Submesoscale Cyclonic Filaments in the North Wall of the Gulf Stream
Bibliographic record
Abstract
Abstract High-resolution, nearly Lagrangian observations of velocity and density made in the North Wall of the Gulf Stream reveal banded shear structures characteristic of near-inertial waves (NIWs). Here, the current follows submesoscale dynamics, with Rossby and Richardson numbers near one, and the vertical vorticity is positive. This allows for a unique analysis of the interaction of NIWs with a submesoscale current dominated by cyclonic as opposed to anticyclonic vorticity. Rotary spectra reveal that the vertical shear vector rotates primarily clockwise with depth and with time at frequencies near and above the local Coriolis frequency f. At some depths, more than half of the measured shear variance is explained by clockwise rotary motions with frequencies between f and 1.7f. The dominant superinertial frequencies are consistent with those inferred from a dispersion relation for NIWs in submesoscale currents that depends on the observed aspect ratio of the wave shear as well as the vertical vorticity, baroclinicity, and stratification of the balanced flow. These observations motivate a ray tracing calculation of superinertial wave propagation in the North Wall, where multiple filaments of strong cyclonic vorticity strongly modify wave propagation. The calculation shows that the minimum permissible frequency for inertia–gravity waves is mostly greater than the Coriolis frequency, and superinertial waves can be trapped and amplified at slantwise critical layers between cyclonic vortex filaments, providing a new plausible explanation for why the observed shear variance is dominated by superinertial waves.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".