North American cold events following sudden stratospheric warming in the presence of low Barents-Kara Sea sea ice
Bibliographic record
Abstract
Abstract While the relationship between the Arctic sea ice loss and midlatitude winter climate has been well discussed, especially on the seasonal mean scale, it remains unclear whether the Arctic sea ice condition affects the predictability of North American cold weather on the subseasonal time scale. Here we find that, in the presence of low Barents-Kara Sea (BKS) sea ice, sudden stratospheric warmings (SSWs) can favor surface cold spells over North America at the subseasonal timescale based on observations and model experiments. A persistent ridge of wave-2 pattern emerges over the Bering Sea-Gulf of Alaska several weeks after the SSW onset, with a coherent structure from the stratosphere to the surface, which, in turn, is conducive to synoptic cold air outbreaks in Canada and midwestern USA. This highlights a planetary wave pathway relating to BKS sea ice changes, by which the stratospheric polar vortex impacts the regional surface temperature on the subseasonal scale. In contrast, this mechanism does not occur with positive BKS sea ice anomaly. These findings help to improve the subseasonal predictability over North America, especially under the background of rapid change of Arctic sea ice in a warming world.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".