Large Regional Differences in Antarctic Ice Shelf Mass Loss from Southern Ocean Warming and Meltwater Feedbacks
Bibliographic record
Abstract
Abstract. The increasing release of Antarctic meltwater represents one of the most profound, yet uncertain, consequences of global climate change. The absence of interactive ice sheets in state-of-the-art climate models prevents the direct calculation of ice-ocean feedbacks, leaving significant uncertainty in the global and regional consequences of meltwater discharge. This study leverages results from the Southern Ocean Freshwater Input from Antarctica (SOFIA) initiative to assess the ocean response to a 0.1 Sv meltwater perturbation and to infer the resulting feedback on ice shelf basal melting across 10 CMIP6 models. We analyze meltwater-induced temperature anomalies across distinct continental shelf regimes, compare them with SSP5-8.5 global warming-induced anomalies, and translate these into basal melt rates using a parameterization calibrated with a new observational climatology. Although the meltwater feedback is generally thought to amplify basal melting, our results demonstrate large regional differences, with implied enhanced ice shelf mass loss in some sectors but suppressed basal melting in others. The model ensemble indicates a warming feedback on the continental shelf in most East Antarctic regions, whereas in West Antarctica, the region with the greatest observed ice shelf mass loss in recent decades, most models simulate cooling or reduced warming, suggesting a negative feedback. This regional contrast implies that East Antarctica may play an increasingly dominant role in future ice shelf mass loss. Simulations support existing hypotheses linking these asymmetric temperature responses to strong regional connectivity and shelf break dynamics, including a strengthened Antarctic Slope Front, an accelerated Antarctic Slope Current, and reduced dense shelf water formation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".