Early Holocene Laurentide Ice Sheet deglaciation causes cooling in the high-latitude Southern Hemisphere through oceanic teleconnection
Bibliographic record
Abstract
[1] The impact of the early Holocene Laurentide Ice Sheet (LIS) deglaciation on the climate at Southern Hemisphere high latitudes is studied in three transient simulations performed with a global climate model of the coupled atmosphere-ocean-vegetation system. Considering the LIS deglaciation, we quantify separately the impacts of the background meltwater fluxes and the changes in topography and surface albedo. In our model, the meltwater input into the North Atlantic results in a substantial weakening of the Atlantic meridional overturning circulation, associated with absence of deep convection in the Labrador Sea. Northward ocean heat transport by the Atlantic Ocean is reduced by 28%. This weakened ocean circulation leads to cooler North Atlantic Deep Water (NADW). Upwelling of this cool NADW in the Southern Ocean results in reduced surface temperatures (by 1°C to 2°C) here between 9 and 7 ka compared to an experiment without LIS deglaciation. Poleward of the polar front zone, this advective teleconnection between the Southern and Northern hemispheres overwhelms the effect of the “classical” bipolar seesaw mechanism. These results provide an explanation for the relatively cold climatic conditions between 9 and 7 ka reconstructed in several proxy records from Southern Hemisphere high latitudes, such as Antarctic ice cores.
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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 | 0.000 | 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 | 0.000 | 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".