Near‐Inertial Wave Propagation in the Deep Canadian Basin: Turning Depths and the Homogeneous Deep Layer
Bibliographic record
Abstract
Abstract The internal wave climate in the deep Arctic Ocean, away from the shelves, is quiet because the ice cover shields the ocean from wind energy input, and tidal amplitudes are small. Hence, mixing due to internal wave breaking is small. The shrinking Arctic sea ice cover, however, exposes more open ocean areas to energy transfer by wind. Consequently, more energetic near‐inertial internal waves (NIWs) may carry energy to the bottom, potentially enhancing deep mixing. In the deep Canadian Basin, weakly stratified layers with local buoyancy frequencies smaller than the wave frequency may prevent NIW propagation to the seafloor. We estimate the distribution of these near‐inertial turning depths from temperature and salinity data of the years 2005–2014. Near‐inertial turning depths are ubiquitous in the deep Canadian Basin at ∼2,750 m depth, between 100 and 1,200 m above the bottom. A deep homogeneous layer below 3,300 m is characterized by small squared buoyancy frequencies N 2 ∼ 0 with locally unstable layers ( N 2 < 0). The turning depths reflect NIWs and hence limit their contribution to deep mixing, but the waves create an evanescent perturbation with exponentially decreasing amplitude that can interact with the bathymetry, especially above slopes and ridges where the height of the turning depths above the seafloor is small. After reflection, the main part of the wave energy is trapped between turning depths and the surface, so that a potential increase of wave energy input mainly affects mixing of mid‐depth water masses like the Atlantic Water.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".