Stratospheric Control of the Linkage between the AMOC and Atlantic Multidecadal Variability
Bibliographic record
Abstract
Abstract The ocean’s role in Atlantic multidecadal variability (AMV) remains intensely debated. The core issue is whether AMV, as an internal climate mode, is driven by variations in the Atlantic meridional overturning circulation (AMOC) or by atmospheric processes. Climate models exhibit a wide range of AMOC–AMV linkages, producing temporal correlations between 0.3 and 0.8, but no robust explanation for these differences exists. Here, using both multimodel intercomparison and perturbation experiments, we propose a dynamical mechanism relating the strength of AMOC–AMV linkage in climate models to stratospheric temperature. This mechanism includes 1) tropospheric midlatitude jet response to stratospheric mean-state temperature anomalies in midlatitudes and 2) resulting ocean surface density changes that alter the spatial structure of deep-water formation in the subpolar North Atlantic and hence AMOC–AMV connection. Specifically, colder stratospheric temperatures produce tighter linkage through a northward jet shift and a stronger AMOC, with enhanced deep-water formation in the Labrador and Irminger Seas relative to the Nordic seas. Models with a warm stratospheric bias tend to produce weaker linkage. Perturbation experiments imposing stratospheric cooling at mid- to high latitudes within two independent climate models support these conclusions. Furthermore, we find that models with stronger AMOC–AMV linkage predict a stronger North Atlantic “warming hole” and weaker twenty-first-century Arctic amplification. We conclude that these results have significant implications for climate prediction and projections.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".