The Siberian Storm Track Weakens the Warm Arctic–Cold Eurasia Pattern
Bibliographic record
Abstract
Abstract With a particular focus on the Siberian storm track, this study provides new insights into variations in the warm Arctic–cold Eurasia (WACE) temperature anomaly pattern by using reanalysis data. The results show that the Siberian storm track has a significant out-of-phase relationship with both the WACE pattern and Ural blocking on the interannual time scale. The strengthened WACE pattern can weaken the Siberian storm track through a suppression of the low-level atmospheric baroclinicity over midlatitude Eurasia. The weakened Siberian storm track can contribute to the WACE pattern through feedback forcing from synoptic-scale eddies, which can also create favorable conditions for the development of Ural blocking. Composite temporal evolution reveals that the strongest cold Arctic–warm Eurasia pattern is preceded by the peak of the Siberian storm track. The Ural cyclonic circulation reaches its maximum amplitude on the peak day of the Siberian storm track strength and continues to persist for one day with the maximum amplitude due to the feedback forcing resulting from the Siberian storm track. On the intraseasonal time scale, the occurrence of the Siberian storm track activity can serve as an early indication of the diminished Ural blocking and WACE pattern. Significance Statement Because of the high impacts of the warm Arctic–cold Eurasia (WACE) pattern on public safety, socioeconomic development, and the economy, it is crucial to enhance our understanding of variations in the WACE pattern. This paper specifically investigates the impact of internal atmospheric variability on the WACE pattern, focusing on a pronounced negative correlation between the Siberian storm track and the WACE pattern. Daily composites also reveal that Siberian storm track activities can promote a strong cold Arctic–warm Eurasia pattern by maintaining the strength of the quasi-stationary Ural cyclonic circulation. As such, paying close attention to Siberian storm track activities may hold the promise to improve the prediction of the strength of the WACE pattern.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".