Past Warmth and Its Impacts During the Holocene Thermal Maximum in Greenland
Bibliographic record
Abstract
Higher boreal summer insolation in the early to middle Holocene drove thousands of years of summer warming across the Arctic. Modern-day warming has distinctly different causes, but geologic data from this past warm period hold lessons for the future. We compile Holocene temperature reconstructions from ice, lake, and marine cores around Greenland, where summer temperatures are globally important due to their influence on ice sheet mass balance, ocean circulation, and sea ice. Highlighting and accounting for some key issues with proxy interpretation, we find that much of Greenland experienced summers 3 to 5°C warmer than the mid-twentieth century in the early Holocene—earlier and stronger warming than often presumed. Warmth had dramatic consequences: Many glaciers disappeared, perennial sea ice retreated, plants and animals migrated northward, the Greenland Ice Sheet shrank rapidly, and increased meltwater discharge led to strong marine water stratification and enhanced winter sea ice in some areas. ▪ Summer air temperatures and open ocean temperatures around much of Greenland peaked in the early Holocene in response to elevated summer insolation. ▪ Peak summer air temperatures ranged from 3 to 5°C warmer than the mid-twentieth century in northwest and central Greenland to perhaps 1 to 2°C warmer in south Greenland. ▪ Many differences between records can be explained by proxy seasonality, ice sheet elevation changes, vegetation analogs and lags, and the nearshore effects of ice sheet meltwater. ▪ Early Holocene warmth dramatically affected glaciers and the Greenland Ice Sheet; meltwater discharge, nearshore ocean salinity, and sea ice; and diverse flora and fauna.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".