The Nature of Eddy Kinetic Energy in the Labrador Sea: Different Types of Mesoscale Eddies, Their Temporal Variability, and Impact on Deep Convection
Bibliographic record
Abstract
Abstract Oceanic eddies are an important component in preconditioning the central Labrador Sea (LS) for deep convection and in restratifying the convected water. This study investigates the different sources and impacts of eddy kinetic energy (EKE) and its temporal variability in the LS with the help of a 52-yr-long hindcast simulation of a 1/20° ocean model. Irminger Rings (IR) are generated in the West Greenland Current (WGC) between 60° and 62°N, mainly affect preconditioning, and limit the northward extent of the convection area. The IR exhibit a seasonal cycle and decadal variations linked to the WGC strength, varying with the circulation of the subpolar gyre. The mean and temporal variations of IR generation can be attributed to changes in deep ocean baroclinic and upper-ocean barotropic instabilities at comparable magnitudes. The main source of EKE and restratification in the central LS are convective eddies (CE). They are generated by baroclinic instabilities near the bottom of the mixed layer during and after convection. The CE have a middepth core and reflect the hydrographic properties of the convected water mass with a distinct minimum in potential vorticity. Their seasonal to decadal variability is tightly connected to the local atmospheric forcing and the associated air–sea heat fluxes. A third class of eddies in the LS are the boundary current eddies shed from the Labrador Current (LC). Since they are mostly confined to the vicinity of the LC, these eddies appear to exert only minor influence on preconditioning and restratification.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".