The Relative Influence of Atmospheric and Oceanic Model Resolution on the Circulation of the North Atlantic Ocean in a Coupled Climate Model
Bibliographic record
Abstract
Abstract It is often unclear how to optimally choose horizontal resolution for the oceanic and atmospheric components of coupled climate models, which has implications for their ability to make best use of available computational resources. Here we investigate the effect of using different combinations of horizontal resolutions in atmosphere and ocean on the simulated climate in a global coupled climate model (Alfred Wegener Institute Climate Model [AWI‐CM]). Particular attention is given to the Atlantic Meridional Overturning Circulation (AMOC). Four experiments with different combinations of relatively high and low resolutions in the ocean and atmosphere are conducted. We show that increases in atmospheric and oceanic resolution have clear impacts on the simulated AMOC, which are largely independent. Increased atmospheric resolution leads to a weaker AMOC. It also improves the simulated Gulf Stream separation; however, this is only the case if the ocean is locally eddy resolving and reacts to the improved atmosphere. We argue that our results can be explained by reduced mean winds caused by higher cyclone activity. Increased resolution of the ocean affects the AMOC in several ways, thereby locally increasing or reducing the AMOC. The finer topography (and reduced dissipation) in the vicinity of the Caribbean basin tends to locally increase the AMOC. However, there is a reduction in the AMOC around 45°N, which relates to the reduced mixed layer depth in the Labrador Sea in simulations with refined ocean and changes in the North Atlantic current pathway. Furthermore, the eddy‐induced changes in the Southern Ocean increase the strength of the deep cell.
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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 | 0.005 |
| 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 | 0.001 |
| 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".