Understanding the Sensitivity of the North Atlantic Subpolar Overturning in Different Resolution Versions of HadGEM3‐GC3.1
Bibliographic record
Abstract
Abstract The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the global climate but is not simulated consistently across models or model resolutions. Here, we use a hierarchy of the global coupled model HadGEM3‐GC3.1, with ocean resolutions of 1°, ¼°, and 1/12°, to evaluate the subpolar AMOC and its sensitivity to horizontal resolution. In line with observations, the models show that the mean overturning and surface forced water mass transformation (SFWMT) are concentrated in the eastern subpolar gyre rather than in the Labrador Sea. However, the magnitude of the overturning along the OSNAP line at medium and high resolutions is 25% and 40% larger than in the observations, respectively. This disagreement in overturning strength is noted for both OSNAP East and OSNAP West, and is mainly due to anomalously large SFWMT rather than anomalously large interior mixing or overflow transport from the Nordic Seas. Over the Labrador Sea, the intensification of SFWMT with resolution is explained by a combination of two main biases. Anomalously warm surface water enhances heat loss and reduces the extension of marginal sea ice, which increases the surface density flux over the boundary of the basin. A bias in salinity leads to anomalously dense surface water that shifts the outcropping area of the AMOC isopycnal and results in intense dense water formation along the boundary of the basin at medium and high resolutions. Thus, our analysis sheds light on a range of model biases responsible for large overturning over the Labrador Sea in climate models.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".