Diffusive vertical heat flux in the Canada Basin of the Arctic Ocean inferred from moored instruments
Bibliographic record
Abstract
Observational studies have shown that an unprecedented warm anomaly has recently affected the temperature of the Atlantic Water (AW) layer lying at intermediate depth in the Arctic Ocean. Using observations from four profiling moorings, deployed in the interior of the Canada Basin between 2003 and 2011, the upward diffusive vertical heat flux from this layer is quantified. Vertical diffusivity is first estimated from a fine‐scale parameterization method based on CTD and velocity profiles. Resulting diffusive vertical heat fluxes from the AW are in the range 0.1–0.2 W m−2 on average. Although large over the period considered, the variations of the AW temperature maximum yields small variations for the temperature gradient and thus the vertical diffusive heat flux. In most areas, variations in upward diffusive vertical heat flux from the AW have only a limited effect on temperature variations of the overlying layer. However, the presence of eddies might be an effective mechanism to enhance vertical heat transfer, although the small number of eddies sampled by the moorings suggest that this mechanism remains limited and intermittent in space and time. Finally, our results suggest that computing diffusive vertical heat flux with a constant vertical diffusivity of ∼2 × 10−6 m2 s−1 provides a reasonable estimate of the upward diffusive heat transfer from the AW layer, although this approximation breaks down in the presence of eddies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".