Is the AMOC connected across all latitudes?
Bibliographic record
Abstract
The Atlantic Meridional Overturning Circulation (AMOC) is fundamental for the northward transport of heat and the vertical transport of carbon from the surface to the deep ocean in the North Atlantic Ocean, influencing the climate at both local and global scales. However, the mechanisms underlying the AMOC variability are still poorly understood, because of the lack of long-term observations and the challenge of representing key processes in standard climate models. Furthermore, assumptions widely accepted for several decades have re-entered the debate in recent years, such as the AMOC meridional coherence and the role of deep convection in the Labrador Sea in driving the AMOC variability and deepwater formation. New modeling and observational studies suggest that the overturning variability is not coherent between subtropical and subpolar latitudes on interannual to decadal scales and that climate models systematically exaggerate the importance of the Labrador Sea, pointing toward other regions like the Irminger Sea and the Nordic Sea as better candidates for deepwater formation.In this study, we aim to critically assess the long-held notion of meridional coherence in the AMOC, using output from high- and very-high-resolution model simulations. Specifically, we investigate how the meridional coherence of the AMOC changes when increasing model resolution, via spectral analysis of the MPI-ESM1.2 control simulations with resolutions of 1°, 0.4°, and 0.1°. Preliminary analysis using lead-lag time correlations indicates a high correlation and meridional coherence between the AMOC strength and mixed layer depth variability in the Labrador Sea for the coarsest resolution. However, when increasing the resolution this relationship disappears, and the AMOC is instead better related to overflow changes in the Denmark Strait and in the Nordic Seas. Additionally, the meridional coherence of the AMOC becomes unclear.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".