Terminating the Last Interglacial: The Role of Ice Sheet-Climate Feedbacks in a GCM Asynchronously Coupled to an Ice Sheet Model
Bibliographic record
Abstract
Climatic deterioration in northeastern Canada following the last interglacial resulted in the formation and abrupt expansion of the Laurentide Ice Sheet. However, the physical mechanisms leading to rapid ice sheet expansion are not well understood. Here, we report on experiments using an ice sheet model asychronously coupled to a GCM to investigate the role of ice sheet-climate feedbacks in terminating the last interglacial period. In agreement with simpler models, our experiments indicate that a specific type of ice-albedo feedback, the small ice cap instability, is the dominant process controlling rapid expansion of the Laurentide Ice Sheet. As ice elevations increase in northeastern Canada, a stationary wave forms and strengthens over the Laurentide Ice Sheet, which acts to hinder further expansion of the ice margin and reduce the effect of the small ice cap instability. The sensitivity of these feedbacks to ice topography results in a reduction in simulated ice volume when the communication interval between the GCM and ice sheet model is lengthened, since this permits larger gains in ice elevation between GCM updates and bias the simulation towards a stronger stationary wave feedback. Our shortest communication interval (500 years) leads to a Laurentide ice volume of 6 million km3 in 10 kyrs, which is less then ice volume estimates based on the geological record, but is a substantial improvement over previous GCM studies. We discuss potential improvements to the asynchronous coupling scheme that would more accurately resolve ice-sheet climate feedbacks, potentially leading to greater simulated ice volume.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".