A Multimodel Study of Sea Surface Temperature and Subsurface Density Fingerprints of the Atlantic Meridional Overturning Circulation
Bibliographic record
Abstract
Abstract The Atlantic meridional overturning circulation (AMOC) is an important component of the North Atlantic climate system. Here, simulations from 10 coupled climate models are used to calculate patterns of sea surface temperature (SST) and subsurface density change associated with decadal AMOC variability. The models are evaluated using observational constraints and it is shown that all 10 models suffer from North Atlantic Deep Water transports that are too shallow, although the biases are least severe in the Community Climate System Model, version 4 (CCSM4). In the models that best compare with observations, positive AMOC anomalies are associated with reduced Labrador Sea stratification and increased midocean (800–1800 m) densities in the subpolar gyre. Maximum correlations occur when AMOC anomalies lag Labrador Sea stratification and subsurface density anomalies by 2–6 yr and 0–3 yr, respectively. In all 10 models, North Atlantic warming follows positive AMOC anomalies, but the patterns and magnitudes of SST change are variable. A simple detection and attribution analysis is then used to evaluate the utility of Atlantic midocean density and Labrador Sea stratification indices for detecting changes to the AMOC in the presence of increasing CO 2 concentrations. It is shown that trends in midocean density are identifiable (although not attributable) significantly earlier than trends in the AMOC. For this reason, subsurface density observations could be a useful complement to transport observations made at specific latitudes and may help with the more rapid diagnosis of basin-scale changes in the AMOC. Using existing observations, it is not yet possible to detect a robust trend in the AMOC using either midocean densities or transport observations from 26.5°N.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".