A glacial systems model configured for large ensemble analysis of Antarctic deglaciation
Bibliographic record
Abstract
Abstract. This article describes the Memorial University of Newfoundland/Penn State University (MUN/PSU) glacial systems model (GSM) that has been developed specifically for large-ensemble data-constrained analysis of past Antarctic Ice Sheet evolution. Our approach emphasizes the introduction of a large set of model parameters to explicitly account for the uncertainties inherent in the modelling of such a complex system. At the core of the GSM is a 3-D thermo-mechanically coupled ice sheet model that solves both the shallow ice and shallow shelf approximations. This enables the different stress regimes of ice sheet, ice shelves, and ice streams to be represented. The grounding line is modelled through an analytical sub-grid flux parameterization. To this dynamical core the following have been added: a heavily parameterized basal drag component; a visco-elastic isostatic adjustment solver; a diverse set of climate forcings (to remove any reliance on any single method); tidewater and ice shelf calving functionality; and a new physically motivated, empirically-derived sub-ice-shelf melt (SSM) component. To assess the accuracy of the latter, we compare predicted SSM values against a compilation of published observations. Within parametric and observational uncertainties, computed SSM for the present-day ice sheet is in accord with observations for all but the Filchner ice shelf. The GSM has 31 ensemble parameters that are varied to account (in part) for the uncertainty in the ice physics, the climate forcing, and the ice–ocean interaction. We document the parameters and parametric sensitivity of the model to motivate the choice of ensemble parameters in a quest to approximately bound reality (within the limits of 31 parameters).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".