Wind-driven transport of fresh shelf water into the Labrador SeaBasin
Bibliographic record
Abstract
Abstract. The Labrador Sea is one of a small number of deep convection sites in the North Atlantic, that contribute to the meridional overturning circulation. Buoyancy is lost from surface waters during winter, allowing the formation of dense deep water. In the recent decades, mass loss from the Greenland ice sheet has accelerated, releasing freshwater into the high latitude North Atlantic. This and the enhanced Arctic freshwater export in the recent years have the potential to add buoyancy to the surface waters, slowing or suppressing convection in the Labrador Sea. However, the impact of freshwater on convection is dependent on whether or not it can escape the shallow, topographically-trapped boundary currents around Greenland and Labrador. Previous studies have estimated the transport of freshwater into the central Labrador Sea by focusing on the role of eddies. Here we use a Lagrangian approach, tracking particles in a global, eddy-permitting (1/12°) ocean model, to examine where and when freshwater enters the Labrador Sea basin in the surface 30 m. We find that most freshwater enters in the east (near the west coast of Greenland), consistent with previous expectations. Seasonally two peaks of freshening are observed. The first peak occurs in the spring and results from a large number of shelf water particles. The second peak, occurring in the fall, is due to the low salinity of the West Greenland current at this time of the year. We find that in these simulations surface wind-driven Ekman transport, rather than eddies, are responsible for the larger year-to-year variability in freshwater transport from the shelves to the central Labrador Sea.
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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 | 0.000 | 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) | 0.002 | 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".