Variability of Internal Wave‐Driven Mixing and Stratification in Canadian Arctic Shelf and Shelf‐Slope Waters
Bibliographic record
Abstract
Abstract Our understanding of ocean mixing is challenged by its patchy, episodic nature and a scarcity of direct measurements, especially in the Arctic Ocean. In this study, we exploit a historical record of nearly 3,000 conductivity‐temperature‐depth profiles collected in the shelf and shelf‐slope waters of the Canadian Arctic Ocean from 2002 to 2016 to characterize the variability of 28,872 internal wave‐driven turbulent dissipation and mixing rate estimates from a finescale parameterization. We find that these estimates of wave‐driven dissipation rates and associated diapycnal diffusivities are generally low, but exhibit wide variability, each spanning several orders of magnitude. We further find that stratification plays a significant role in modulating the mixing rate both vertically and regionally within the study domain. Dissipation rate and diffusivity estimates display a weak seasonal cycle, but no evidence of statistically significant interannual trends over this period. Exceptionally large localized temporal variability appears to dominate other potential underlying patterns. The presence of strong upper ocean stratification combined with predominately weak dissipation rate estimates implies that many regions in the Canadian Arctic Ocean are likely in a molecular or buoyancy‐controlled mixing regime. Even when the concept of a turbulent‐enhanced diffusivity is potentially relevant, most turbulent heat flux estimates out of the Atlantic Water thermocline are smaller than the average value required to close the standardly assumed Arctic Ocean heat budget. In contrast, we find evidence for isolated occurrences of anomalously large heat fluxes, which may disproportionately contribute to the liberation of Atlantic Water heat toward the surface sea ice pack.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".