Mixed layer depth in the PMIP4 midHolocene simulations: comparison to new proxy data in North Atlantic deep convection regions
Bibliographic record
Abstract
The ocean mixed layer plays an important role in the climate system as it regulates energy fluxes at the ocean-atmosphere interface. Its representation in climate models is thus critical. Here, we evaluate the mixed layer depth (MLD) in 15 coupled global climate models used in the Paleoclimate Modelling Intercomparison Project 4 and compare them against dinocyst-based MLD reconstructions from the subpolar North Atlantic for the mid-Holocene (MH, 6000 years before present). We observe a large spread of MLD response to the MH forcings across the models in the present-day deep-water formation areas, highlighting the importance of model uncertainty. Most models fail to predict the direction of MLD change, and the ensemble mean does not align better with proxy data than individual models. Our analysis also suggests that deep-water formation in the Labrador Sea may be particularly vulnerable under a future scenario of global warming and ice sheet melting.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".