Quantifying the contribution of surface buoyancy forcing to recent subpolar AMOC variability
Bibliographic record
Abstract
<!--!introduction!--> In the subpolar North Atlantic (SPNA), interannual to multidecadal variability in the Atlantic Meridional Overturning Circulation (AMOC) is primarily attributed to surface buoyancy forcing. Here, warm surface waters arriving via the Gulf Stream and North Atlantic Current undergo an intense loss of heat and freshwater to the atmosphere, and are thus transformed to cold and dense waters which subsequently sink and are returned southward at depth. Quantifying the contribution of surface buoyancy forcing to AMOC variability is essential for modelling how the AMOC will respond to predicted warming and freshening at high latitudes. In a water mass transformation framework, fields of surface density and surface density flux from the GODAS ocean reanalysis are used to construct the surface-forced overturning circulation (SFOC) streamfunction for the SPNA (48-65°N) in an operational assimilation over 1980-2020. Computed and plotted in latitude-density space, the SFOC reconstruction compares favourably with the corresponding AMOC, computed from GODAS currents. We thus conclude that subpolar AMOC variability is largely explained by changing air-sea heat and freshwater fluxes controlling water mass transformation across the region. We further highlight the changing relative influences of water mass transformation in the eastern and western subpolar gyre, by partitioning SFOC longitudinally into an East component (5-43 °W) comprising the Irminger and Iceland basins, and a West component (43-60 °W) comprising the Labrador Sea. Our analysis demonstrates that interannual to multidecadal SFOC variability is dominated by changing water mass transformation in the western subpolar gyre. This challenges a shifting consensus that highlights the eastern subpolar gyre as dominant in driving the AMOC across subpolar latitudes.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".