Self-consistency of the regolith hypothesis for the mid-Pleistocene Transition
Bibliographic record
Abstract
Is the regolith hypothesis consistent with the physics of glacial removal of mechanically weak surface material? The mid-Pleistocene transition (MPT) from small 40 kyr glacial cycles to large, abruptly terminating 100 kyr ones represents a major climate system reorganization for which a clear understanding is lacking. A leading mechanism for this transition is a stabilization of ice sheets due to a shift to higher friction substrate. The Pleistocene saw the removal of deformable regolith -- laying bare hard higher-friction bedrock that would help preserve regional ice during warm interstadials. This is the regolith hypothesis. The removal of regolith by Pleistocene ice sheets remains poorly constrained. To date, only models with a forced change in area of regolith cover or 1D flow line models with simplistic sediment transport have been used to probe the role of regolith in the MPT. It is therefore unclear if the appropriate amount of regolith removal can occur within the time-frame of the MPT. To properly test the hypothesis, at least three components are required: capable model, observational constraint, and a probe of uncertainties. A capable model must explicitly represent relevant processes in a fully coupled self-consistent manner. We have therefore configured a state of the art 3D glacial systems model (GSM). The GSM incorporates a state-of-the-art fully coupled sediment production/transport model, subglacial hydrology, visco-elastic glacial isostatic adjustment, 3D thermomechanically coupled hybrid shallow ice/shallow shelf ice dynamics, and internal climate solution from an energy balance model. The model generates sediment by quarrying and abrasion, and both subglacial and englacial sediment transport. The subglacial hydrology model employs a linked-cavity system with a flux based switch to tunnel drainage, giving dynamic effective pressure needed for realistic sediment and sliding processes. The coupled model is driven only by prescribed atmospheric CO2 and orbitally derived insolation. The required observational constraints include present-day regolith distribution and inferred Pleistocene ice volume from proxy records. The final component is a large ensemble of full Pleistocene simulations that probe both initial regolith distribution uncertainties and model parametric uncertainties. We present the results of such an ensemble, examining both rates of computed regolith removal and changes in ice volume cycling across the MPT interval.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".