Role of Resolved and Parameterized Eddies in the Labrador Sea Balance of Heat and Buoyancy
Bibliographic record
Abstract
Abstract Deep convection in the Labrador Sea is an important component of the global ocean ventilation. The associated loss of heat to the atmosphere from the interior of the sea is thought to be mostly supplied by mesoscale eddies, generated either remotely or as a result of convection itself—processes that are not resolved by low-resolution ocean climate models. The authors first employ a high-resolution (°) ocean model forced with high-resolution (33 km, 3 h) atmospheric fields to further elaborate on the role of mesoscale eddies in maintaining the balance of heat and buoyancy in the Labrador Sea. In general agreement with previous studies, it is found that eddies remove heat along the coast and supply it to the interior. Some of the eddies that are generated because of the barotropic instability off the west coast of Greenland are recaptured by the boundary current. In the region of deep convection, the convergence of heat and buoyancy by eddies significantly increases with the deepening of the winter mixed layer. In addition, the vertical eddy flux plays an important part in the heat budget of the upper Labrador Sea, accounting for up to half of the heat loss to the atmosphere north of 60°N. A low-resolution (1°) model with parameterized eddies is then applied to show that it does capture, qualitatively, the general structure of eddy buoyancy advection along the Labrador Current. However, the 1° model is deficient in this regard in the most eddy active region off the west coast of Greenland, although some improvements can be made by forcing it with the high-resolution atmospheric fields.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".