Characterization of double diffusive convection steps and heat budget in the deep Arctic Ocean
Bibliographic record
Abstract
In this paper, we explore the hydrographic structure and heat budget in the deep Canada Basin by using data measured with McLane-Moored-Profilers (MMP), bottom pressure recorders (BPR), and conductivity-temperature-depth (CTD) profilers. Upward from the bottom, a homogeneous bottom layer and its overlaying double diffusive convection (DDC) steps are well identified at Mooring A ( 75 degrees N,150 degrees W). We find that the deep water is in weak diapycnal mixing because the effective diffusivity of the bottom layer is approximate to 1.8x10-5m2s-1, while that of the other steps is approximate to 10-6m2s-1. The vertical heat flux through the DDC steps is evaluated by using different methods. We find that the heat flux ( 0.1-11mWm-2) is much smaller than geothermal heating ( approximate to 50mWm-2). This suggests that the stack of DDC steps acts as a thermal barrier in the deep basin. Moreover, the temporal distributions of temperature and salinity differences across the interface are exponential, whereas those of heat flux and effective diffusivity are found to be approximately lognormal. Both are the result of strong intermittency. Between 2003 and 2011, temperature fluctuations close to the sea floor were distributed asymmetrically and skewed toward positive values, which provide a direct observation that geothermal heating was transferred into the ocean. Both BPR and CTD data suggest that geothermal heating and not the warming of the upper ocean is the dominant mechanism responsible for the warming of deep water. As the DDC steps prevent vertical heat transfer, geothermal heating is unlikely to have a significant effect on the middle and upper Arctic Ocean.
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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) | 0.000 | 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".