The effect of noise on the stability of convection in a conceptual model of the North Atlantic subpolar gyre
Bibliographic record
Abstract
Abstract. The North Atlantic subpolar gyre (SPG) plays a fundamental role in the Atlantic ocean circulation by providing an important connection between the subtropical Atlantic and the Arctic. It is driven by both wind and density differences that are, in part, caused by convection in the Labrador Sea. Through this deep convection site, the SPG is also linked to the AMOC. There is considerable evidence that this area of convection may diminish or shift in a changing climate. For this reason, the convection in the SPG is considered a tipping point. Here, we extensively study a conceptual model of the SPG to characterize the stability of convection in the gyre. The bifurcation structure of this model is analyzed in order to identify bistable parameter regions. For a range of gyre salinity and freshwater forcing levels the gyre is found to have both convective and non-convective states. Furthermore, noise-induced transitions between convective and non-convective states are possible for a wide range of parameter values. Convection in the SPG becomes increasingly unstable as the gyre salinity decreases and the freshwater forcing increases. However, convection never fully stops and can always restart after a period of no convection. This indicates that, at least in this conceptual model, a collapse of convection in the SPG does not have to be permanent.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".