Effect of Subshelf Melt Variability on Sea Level Rise Contribution From Thwaites Glacier, Antarctica
Bibliographic record
Abstract
Modeling and observations suggest that Thwaites Glacier, West Antarctica, has begun unstable retreat. Concurrently, oceanographic observations have revealed substantial multiyear variability in the temperature of the ocean water driving retreat through melting of the ice shelf that restrains inland glacier flow. Using an ensemble of 72 ice‐sheet model simulations that include an idealized representation of ocean temperature variability, we find that variable ice‐shelf melting causes delays in grounding line retreat, mass loss, and sea level contribution relative to steady forcing. Modeled delays are up to 43 years after 500 years of simulation, corresponding to a 10% reduction in glacier mass loss. Delays are primarily caused by asymmetric melt forcing in the presence of variability. For the “warm cavity” conditions beneath Thwaites Ice Shelf, increases in access of warm, deeper water are unable to raise water temperatures in the cavity by much, whereas increases in access of significantly colder, shallow water reduce cavity water temperatures substantially. This leads to lowered mean melt rates under variable ocean temperature forcing. Additionally, about one quarter of the mass loss delay is caused by a nonlinear ice dynamic response to varying ice‐shelf thinning rate, which is amplified during the initial phases of unstable, bed‐topography‐driven retreat. Mass loss rates under variability differ by up to 50% from ensemble mean values at any given time. Our results underscore the need for taking climate variability into account when modeling ice sheet evolution and for continued efforts toward the coupling of ice sheet models to ocean and climate models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".