Greenland ice sheet contribution to sea level rise during the last interglacial period: a modelling study driven and constrained by ice core data
Bibliographic record
Abstract
Abstract. As pointed out by the forth assessment report of the Intergovernmental Panel on Climate Change, IPCC-AR4 (Meehl et al., 2007), the contribution of the two major ice sheets, Antarctica and Greenland, to global sea level rise, is a subject of key importance for the scientific community. By the end of the next century, a 3–5 °C warming is expected in Greenland. Similar temperatures in this region were reached during the last interglacial (LIG) period, 130–115 ka BP, due to a change in orbital configuration rather than to an anthropogenic forcing. Ice core evidence suggests that the Greenland ice sheet (GIS) survived this warm period, but great uncertainties remain about the total Greenland ice reduction during the LIG. Here we perform long-term simulations of the GIS using an improved ice sheet model. Both the methodologies chosen to reconstruct palaeoclimate and to calibrate the model are strongly based on proxy data. We suggest a relatively low contribution to LIG sea level rise from Greenland melting, ranging from 0.7 to 1.5 m of sea level equivalent, contrasting with previous studies. Our results suggest an important contribution of the Antarctic ice sheet to the LIG highstand.
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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) | 0.001 | 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 | 0.000 |
| 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".