Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model
Bibliographic record
Abstract
Abstract. This study examines the interactions between the Northern Hemisphere ice sheets and the ocean during the last glacial period. We explore the consequences of an ocean subsurface warming on ice sheet dynamics and the associated feedbacks, using the climate model of intermediate complexity iLOVECLIM coupled with the ice sheet model GRISLI. Our study shows that amplified oceanic basal melt rates lead to significant freshwater release from both increased calving and basal melt fluxes. Inland, dynamic thinning occurs over the Eurasian and Iceland ice sheets, leading to destabilization, while the coasts of Greenland and the eastern part of the Laurentide ice sheet are thickening. There, the increased oceanic basal melt rates lead to a reduction in the thickness of the ice shelves and the ice flow at the grounding line, resulting in upstream accumulation. Nevertheless, the influx of fresh water temporarily increases sea-ice extent, reduces convection in the Labrador Sea, weakens the Atlantic meridional overturning circulation, lowers surface temperatures in the Northern Hemisphere and increases the subsurface temperatures in the Nordic Seas. The release of cold and fresh water leads to a decrease in ice sheet discharge (negative feedback) for the Greenland and Eurasian ice sheets. The Laurentide ice sheet is rather stable due to low background temperatures and salinity at shelf drafts in the Baffin Bay and Labrador Sea in the model. Still, we show that we are able to trigger a grounding line retreat by imposing ad-hoc oceanic melt rates (10 m/yr). However, continental ice loss stops as soon as we halt the perturbation. This study emphasizes the complex feedback mechanisms at the ocean-ice sheet interface, stressing the necessity for more accurately constrained model results to enhance our understanding of past changes and the predictions of future ice sheet behaviour and sea level rise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".