Simulating the Holocene climate evolution at northern high latitudes using a coupled atmosphere-sea ice-ocean-vegetation
Bibliographic record
Abstract
Abstract The response of the climate at high northern latitudes to slowly changing external forcings was stud-ied in a 9,000-year long simulation with the coupled atmosphere-sea ice-ocean-vegetation model ECBilt-CLIO-VECODE. Only long-term changes in insolation and atmospheric CO2and CH4 content were prescribed. The experiment reveals an early optimum (9–8 kyr BP) in most regions, followed by a 1–3C decrease in mean annual temperatures, a reduction in summer precipita-tion and an expansion of sea-ice cover. These results are in general agreement with proxy data. Over the conti-nents, the timing of the largest temperature response in summer coincides with the maximum insolation differ-ence, while over the oceans, the maximum response is delayed by a few months due to the thermal inertia of the oceans, placing the strongest cooling in the winter half year. Sea ice is involved in two positive feedbacks (ice-albedo and sea-ice insulation) that lead regionally to an amplification of the thermal response in our model (7C cooling in Canadian Arctic). In some areas, the tundra-taiga feedback results in intensified cooling dur-ing summer, most notably in northern North America. The simulated sea-ice expansion leads in the Nordic Seas to less deep convection and local weakening of the overturning circulation, producing a maximum winter temperature reduction of 7C. The enhanced interaction between sea ice and deep convection is accompanied by increasing interannual variability, including two marked decadal-scale cooling events. Deep convection intensifies in the Labrador Sea, keeping the overall strength of the thermohaline circulation stable throughout the experi-ment. 1
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".