Alternative viscous-plastic rheologies for the representation of fracture lines in high-resolution sea ice models
Bibliographic record
Abstract
Fracture lines dominate the dynamics of sea ice. They affect the ice mass balance and the heat transfer between the atmosphere and the ocean. Therefore, climate modeling and sea ice prediction require an accurate fracture representation. Most sea ice models use viscous-plastic (VP) rheologies to simulate sea ice internal stresses. One of the issues with these rheologies is that they overestimate the intersection angles between fracture lines, with consequences for the subsequent sea ice drift. In idealized experiments, we investigate the mechanisms linking VP rheologies and fracture angles and assess alternative rheologies for high-resolution modeling. Results show that the definition of the transition between viscous and plastic states is essential for the creation of sharp fracture lines. The fracture angles with Mohr-Coulomb yield curves agree with the Arthur fault orientation theory. Further, rheologies with Mohr-Coulomb yield curves or teardrop yield curves appear to reduce intersection angles. Finally, experiments show that these results are reproduced for different sea ice initial conditions. With rheologies that favor smaller intersection angles, sea ice models move a step closer to accurate sea ice dynamics at high-resolution.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".