A global ensemble-based comparison of the last two glacial inceptions with LCice 2.0
Bibliographic record
Abstract
What determines the character of glacial inceptions? Does the spatio-temporal pattern of ice nucleation and expansion vary much between Late Pleistocene glacial inceptions? According to various benthic del18O stacks, the MIS 7 interglacial was the most anomalous in character of the last 4 interglacials. Key differences include a weaker interglacial state and an initial fast inception interrupted by a return to a similar and extended interglacial state. These anomalies of MIS 7 along with temporal proximity arguably make the last two glacial inceptions the best test case for addressing our opening questions. As part of a larger project to generate and analyze a data-constrained ensemble of fully coupled ice/climate transient simulations for the last two complete glacial cycles, herein we present initial results comparing the last two glacial inceptions (MIS 7 and 5d). We are using a new version of the fully coupled ice/climate model LCice. LCice now simulates all 4 paleo ice sheet complexes with hybrid shallow-shelf and shallow-ice physics. It has already been shown to capture northern hemispheric ice sheet growth and subsequent retreat consistent with inferences from global mean sea level proxies (Bahadory et al, 2019). Orbital and greenhouse gas changes are the only external forcings applied to the model. A 300 member ensemble probes parametric uncertainties in both the 3D Glacial Systems Model and LoveClim (Atmosphere/Ocean/Vegetation) components of LCice. Our presentation will compare the evolution and relative phasing of all 4 paleo ice sheets, and associated changes in the rest of the modelled climate system.
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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) | 0.001 | 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".