Mechanisms driving the asymmetric seasonal cycle of Antarctic Sea Ice in the CESM Large Ensemble
Bibliographic record
Abstract
Abstract The yearly paired process of slow growth and rapid melt of some 15 million square kilometers of Antarctic sea ice takes place with a regular asymmetry; the process has been linked to the relationship of the position of the ice edge with the band of low pressure that circles the continent between 60° and 70°S. In autumn, winds to the north of the low-pressure band slow the advancing ice edge. In summer, Ekman divergence created by opposing winds on either side of the low-pressure band opens up warm water regions that rapidly melt sea ice. We use the 40 ensemble members from the CESM-LENS historical run (1920–2005) to examine the relationship between the asymmetry in the annual cycle and the position and intensity of the low-pressure band. CESM-LENS reproduces the magnitude of the annual cycle of Antarctic sea ice extent with a short lag (2 weeks). Melt rate is the characteristic of the annual cycle that varies the most. Our results provide evidence that lower pressure leads to increased melt rates, which supports the importance of the role of divergence in increasing the melt rate of Antarctic sea ice. The role of winds during the growing season remains unquantified.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".