Impacts of Sudden Stratospheric Warming on Extreme Cold Events in Early 2021: An Ensemble‐Based Sensitivity Analysis
Bibliographic record
Abstract
Abstract Impacts of sudden stratospheric warming (SSW) on three severe cold events (C1–C3) over Northern Hemisphere in early 2021 were investigated using subseasonal‐to‐seasonal ensemble forecasts. The SSW was characterized by successive displacement and split of the stratospheric polar vortex (SPV). Ensemble‐based sensitivity analyses showed that C1 over Siberia and C2 over western Canada were more related to SPV variations at a lead time of 1–2 weeks than C3 over central U.S. Within ensemble forecasts, a more elongated SPV with higher geopotential height over northern Eurasia were conducive to C1, whereas a SPV with the more poleward retreat from displacement contributed to C2. The forecast accuracy of stratospheric heights over the sensitive region at 2 weeks lead was significantly correlated with the forecast skill of the tropospheric circulation pattern preceding C1, implying that prediction of specific cold weather events may be improved by a better forecast of key features in SPV variations.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".