Global Abyssal Mixing Inferred from Lowered ADCP Shear and CTD Strain Profiles
Bibliographic record
Abstract
Abstract Internal wave–wave interaction theories and observations support a parameterization for the turbulent dissipation rate ɛ and eddy diffusivity K that depends on internal wave shear 〈Vz2〉 and strain 〈ξz2〉 variances. Its latest incarnation is applied to about 3500 lowered ADCP/CTD profiles from the Indian, Pacific, North Atlantic, and Southern Oceans. Inferred diffusivities K are functions of latitude and depth, ranging from 0.03 × 10−4 m2 s−1 within 2° of the equator to (0.4–0.5) × 10−4 m2 s−1 at 50°–70°. Diffusivities K also increase with depth in tropical and subtropical waters. Diffusivities below 4500-m depth exhibit a peak of 0.7 × 10−4 m2 s−1 between 20° and 30°, latitudes where semidiurnal parametric subharmonic instability is expected to be active. Turbulence is highly heterogeneous. Though the bulk of the vertically integrated dissipation ∫ɛ is contributed from the main pycnocline, hotspots in ∫ɛ show some correlation with small-scale bottom roughness and near-bottom flow at sites where strong surface tidal dissipation resulting from tide–topography interactions has been implicated. Average vertically integrated dissipation rates are 1.0 mW m−2, lying closer to the 0.8 mW m−2 expected for a canonical (Garrett and Munk) internal wave spectrum than the global-averaged deep-ocean surface tide loss of 3.3 mW m−2.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".