Arctic Sea ice decline whiplash modes in winter investigated from a Pan-Arctic viewpoint: atmospheric drivers and feedbacks
Bibliographic record
Abstract
Abstract The term ‘sea ice decline whiplash’ describes short-term abrupt sea ice decline, as determined falling below the 10th percentile of the probability density function of daily sea ice concentration (SIC) tendency. The leading SIC modes over pan-Arctic show significant locality and co-variability based on empirical orthogonal function (EOF) analysis of sea ice decline whiplash days during winters of 1979–2020. The first and third EOFs correspond to a seesaw and an in-phase anomalous SIC pattern over the Davis Strait/Labrador Sea and the Greenland-northern Barents Sea, respectively. The second EOF shows a dipole pattern, with opposing SIC centers of action in the Bering Sea and the Sea of Okhotsk. These leading EOF modes may occur individually or occasionally simultaneously, which partially explains the spatial heterogeneity of short-term Arctic sea ice retreat. Regression analysis shows that the abrupt sea ice decline associated with these three leading EOF modes is closely related to the enhanced downward longwave radiation over sea ice-covered region due to heat transport from midlatitudes and large-scale condensation heating, in addition to the moist effect produced by the increased evaporation after sea ice decline. The surface turbulent heat flux, however, may indirectly melt the sea ice by heating the surrounding ice-free region mainly through anomalous downward surface sensible heat flux. Conversely, the melting sea ice may have a feedback on the tropospheric atmosphere over mid-high latitudes via anomalous upward surface latent heat flux, which depends on the specific sea ice decline whiplash mode. Our work emphasizes the joint effects of external heat and moisture transportation associated with atmospheric circulation and local vertical feedback of the short-term sea ice decline whiplash.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".