The impact of model resolution on the North Atlantic response to anthropogenic aerosols
Bibliographic record
Abstract
Abstract. A set of novel, idealised, single-forcing experiments were performed to isolate the impact of anthropogenic sulphur dioxide emissions on North Atlantic SST variability. The medium-resolution (60 km atmosphere, 0.25° ocean) and low-resolution (135 km atmosphere, 1° ocean) of the HadGEM3-GC3.1 model were used to investigate the impact of resolution on the forced response. The SST response at both resolutions is timescale dependent: a fast, large-scale surface cooling is followed by a slow, ocean-driven warming responses. Warming of the sub-polar North Atlantic is due to a strengthening of the Atlantic Meridional Overturning Circulation (AMOC) and is stronger at the medium resolution. This difference is related to surface density fluxes across the subpolar North Atlantic. The growth of Labrador Sea ice is stronger at low-resolution which inhibits air-sea interaction and reduces surface buoyancy forcing, leading to a weaker AMOC response. There is also evidence of a stronger AMOC positive feedback involving salt-advection at medium-resolution. These results show that the large-scale North Atlantic response to external forcing can be sensitive to regional differences, such as model climatology of Labrador Sea ice and its response to aerosol cooling.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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".