Last Glacial Maximum ice sheet impacts on North Atlantic climate variability: The importance of the sea ice lid
Bibliographic record
Abstract
Abstract Last Glacial Maximum (LGM) ICE‐5G (VM2), ICE‐6G (VM5a), and Paleoclimate Modelling Intercomparison Project Phase 3 ice sheet reconstructions are employed in high‐resolution coupled climate model simulations to investigate the changes they induce in North Atlantic climate variability. An initial ICE‐5G (VM2) experiment develops a rapid increase of sea ice extent once a thermal threshold is exceeded in this multimillennial simulation. Subpolar sea ice concentration and thickness are found to be strongly impacted by topographically induced downstream thermal effects from the Laurentide Ice Sheet in each of the reconstructions. However, in the two additional LGM perturbation experiments, the modeled changes in sea ice area are sufficiently similar to the LGM ICE‐5G (VM2) experiment to lead to an equilibrium Atlantic Meridional Overturning Circulation strength that is also reduced by the same ~40% from preindustrial even though we find significant variation among the models in the deep convection regions of the subpolar glacial North Atlantic. Model‐predicted sea ice concentrations in this critical region exceed those based upon multiproxy reconstructions, and we trace these significant differences to the intensity of the interannual variability of sea ice cover predictions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".