The response of the deep convection to the Antarctic Meltwater
Bibliographic record
Abstract
Observations indicate that the mass loss from the Antarctic ice sheet has been increasing over the past several decades. This loss is projected to accelerate significantly into the future. Deep convection in the Southern Ocean is expected to bear the brunt of meltwater from a retreating Antarctic Ice Sheet. Here, we present the responses of deep convection and Antarctic Bottom Water (AABW) formation using six coupled climate models with a constant rate of freshwater flux anomaly. Six models all show a significant decrease in the strength of deep convection, albeit the magnitude and location of the changes vary greatly across models. Models that convect more strongly in the base state decrease more in deep convection. We found that the big difference in response between models is surprisingly consistent with their respective base states. With the cessation of deep convection, the AABW becomes warmer and of contraction, and the sea ice concentration and area increase significantly, accompanying surface cooling. However, the link between the responses in deep convection and sea ice area is more complicated than simply meaning more reduction in deep convection corresponds to more increase in sea ice. We suggest that this complexity is partly because some models convect over too large an area and the freshwater forcing is rather strong. Our results suggest that increasing Antarctic meltwater into the ocean will reduce AABW formation, amplifying the warming rate of deep and abyssal waters and reducing the melting rate of sea ice caused by heat input, and reducing vertical exchange due to intensified stratification.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".