Migration of the Shear Margins at Thwaites Glacier: Dependence on Basal Conditions and Testability Against Field Data
Bibliographic record
Abstract
Abstract Projections of global sea level depend sensitively on whether Thwaites Glacier, Antarctica, will continue to lose ice rapidly. Prior studies have focused primarily on understanding the evolution of ice velocity and whether the reverse‐sloping bed at Thwaites Glacier could drive irreversible retreat. However, the overall ice flux to the ocean and the possibility of irreversible retreat depend not only on the ice speed but also on the width of the main ice trunk. Here, we complement prior work by focusing specifically on understanding whether the lateral boundaries of the main ice trunk, termed shear margins, might migrate over time. We hypothesize that the shear margins at Thwaites Glacier will migrate on a decadal timescale in response to continued ice thinning and surface steepening. We test this hypothesis by developing a depth‐averaged, thermomechanical free‐boundary model that captures the complex topography underneath the glacier and solves for both the ice velocity and for the position of the shear margins. We find that both shear margins are prone to migration in response to ice thinning with basal strength and surface slope steepening determining their relative motion. We construct four end‐member cases of basal strength that represent different physical properties governing friction at the glacier bed and present two cases of ice thinning to contrast the effects of surface steepening and ice thinning. We test our model by hindcasting historic data and discuss how data from ongoing field campaigns could further be used to test our model.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".