Ocean‐Only FAFMIP: Understanding Regional Patterns of Ocean Heat Content and Dynamic Sea Level Change
Bibliographic record
Abstract
Abstract There is large uncertainty in the future regional sea level change under anthropogenic climate change. Our study presents and uses a novel design of ocean general circulation model (OGCM) experiments to investigate the ocean's response to surface buoyancy and momentum flux perturbations without atmosphere‐ocean feedbacks (e.g., without surface restoring or bulk formulae), as part of the Flux‐Anomaly‐Forced Model Intercomparison Project (FAFMIP). In an ensemble of OGCMs forced with identical surface flux perturbations, simulated dynamic sea level (DSL) and ocean heat content (OHC) change demonstrate considerable disagreement. In the North Atlantic, the disagreement in DSL and OHC change between models is mainly due to differences in the residual (resolved and eddy) circulation change, with a large spread in the Atlantic meridional overturning circulation (AMOC) weakening (20–50%). In the western North Pacific, OHC change is similar among the OGCM ensemble, but the contributing physical processes differ. For the Southern Ocean, isopycnal and diapycnal mixing change dominate the spread in OHC change. In addition, a component of the atmosphere‐ocean feedbacks are quantified by comparing coupled, atmosphere‐ocean GCM (AOGCM) and OGCM FAFMIP experiments with consistent ocean models. We find that there is 10% more AMOC weakening in AOGCMs relative to OGCMs, since the extratropical North Atlantic SST cooling due to heat redistribution amplifies the surface heat flux perturbation. This component of the atmosphere‐ocean feedbacks enhances the pattern of North Atlantic OHC and DSL change, with relatively stronger increases and decreases in the tropics and extratropics, respectively.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".