Labrador Sea subsurface density as a precursor of multidecadal variability in the North Atlantic: a multi-model study
Bibliographic record
Abstract
Abstract. The subpolar North Atlantic (SPNA) is a region with prominent decadal variability that has experienced remarkable warming and cooling trends in the last few decades. These observed trends have been preceded by slow-paced increases and decreases in the Labrador Sea density (LSD), which are thought to be a precursor of large-scale ocean circulation changes. This article analyses the interrelationships between the LSD and the wider North Atlantic across an ensemble of coupled climate model simulations. In particular, it analyses the link between subsurface density and the deep boundary density, the Atlantic Meridional Overturning Circulation (AMOC), the subpolar gyre (SPG) circulation, and the upper-ocean temperature in the eastern SPNA. All simulations exhibit considerable multidecadal variability in the LSD and the ocean circulation indices, which are found to be interrelated. LSD is strongly linked to the strength of the subpolar AMOC and gyre circulation, and it is also linked to the subtropical AMOC, although the strength of this relationship is model-dependent and affected by the inclusion of the Ekman component. The connectivity of LSD with the subtropics is found to be sensitive to different model features, including the mean density stratification in the Labrador Sea, the strength and depth of the AMOC, and the depth at which the LSD propagates southward along the western boundary. Several of these quantities can also be computed from observations, and comparison with these observation-based quantities suggests that models representing a weaker link to the subtropical AMOC might be more realistic.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".