Polar Amplification in Idealized Climates: The Role of Ice, Moisture, and Seasons
Bibliographic record
Abstract
Abstract The drivers of polar amplification are investigated by isolating the role of sea‐ice processes, moist energy transport, and the seasonal cycle of insolation in two models, an energy balance model and an idealized general circulation model. Compared to a simple ice‐albedo feedback (temperature‐dependent surface albedo), the addition of thermodynamic‐ice processes and the seasonal cycle of insolation profoundly affects seasonal polar warming. Climatologically limited‐extent ice in the warm season permits only small increases in absorbed solar radiation, producing weak warming, while thick, cold ice in the cold season enables a large radiatively forced response. Despite this enhanced winter warming, the annual‐mean polar amplification is modestly reduced by thermodynamic‐ice processes. When latent heat transport is disabled, polar amplification is further reduced by a factor of 1.8 across the range of ice representations, suggestive of a nearly additive warming by ice and moist‐transport processes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".