Attributing Recent Variability in the Subpolar AMOC to Surface Buoyancy Forcing
Bibliographic record
Abstract
Abstract Variability in the Atlantic Meridional Overturning Circulation (AMOC) on interannual to multidecadal timescales can primarily be linked to the strength of deep-water formation in the Subpolar North Atlantic, where surface buoyancy forcing transforms light surface waters to the dense waters of the southward-flowing lower-limb of the AMOC. In a water mass transformation (WMT) 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 Subpolar North Atlantic (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. To further partition dense waters contributing to the AMOC, the SFOC is longitudinally partitioned into an East component, comprising the Irminger/Iceland basins, and a West component, comprising the Labrador Sea. Interannual and multidecadal changes in the dominant location of deep-water formation in the Subpolar North Atlantic are thus elucidated. The analysis provides transport estimates complementary to those obtained with observations from the RAPID array since 2004, and OSNAP array since 2014, revealing that recent (post-2014) domination of overturning in the Eastern Subpolar Gyre may be transient.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".