The North Atlantic mean state in eddy-resolving coupled models: a multimodel study
Bibliographic record
Abstract
Abstract. Ocean mesoscale structures, which are parameterized in standard resolution models, play an important role in featuring global ocean dynamics. Here we study the effects of increasing model ocean resolution to eddy-resolving scales on the representation of the North Atlantic mean state, by comparing an ensemble of four HighResMIP coupled historical simulations with nominal ocean resolutions of at least 1/10° – corresponding to the models CESM1-CAM5-SE-HR, EC-Earth3P-VHR, HadGEM3-GC31-HH, and MPI-ESM1-2-ER – to a baseline of 39 Coupled Model Intercomparison Project phase 6 (CMIP6) simulations at coarser resolution. Despite a warm and salty bias at the surface, we find generally improved vertical stratification in the Labrador (LS) and western Irminger Seas (IS) in the high resolution ensemble, leading to stronger deep water convection in that region, in closer agreement with observations. Both the overturning and barotropic circulations of the North Atlantic present significant improvements in the eddy-resolving models: the Atlantic Meridional Overturning Circulation (AMOC) is weaker than for lower resolution models and closer to RAPID observations; the paths, strength, and structure of the Gulf Stream (GS), North Atlantic Current (NAC), and subpolar gyre (SPG) are also improved, resulting into reduced surface temperature and salinity biases north of Cape Hatteras (NCH) and in the Central North Atlantic (CNA).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".