1
Return

How to Predict the Phase Shift of “Warm Arctic–Cold Eurasia” Pattern Between Early and Late Winter?

delete2026-07-05
delete0
delete
OA
AI
Z
Zhicong Yin *
T
Tianbao Xu
DOI:10.1029/2025JD046278delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
The “Warm Arctic−Cold Eurasia” (WACE) pattern frequently undergoes distinct phase reversals between early and late winter, posing significant challenges for climate prediction. Current state-of-the-art real-time prediction models exhibit limited skill in forecasting WACE reversals, and the main reason is poor representation of key atmospheric circulation systems, such as the Ural high (UH) and Siberian high (SH). To address this gap, we develop statistical forecast models targeting these circulation systems and then integrate the predicted UH and SH into existing real-time prediction models. This approach accounts for early and late winter differences and addresses model limitations in representing physical processes. The enhanced models markedly improve WACE reversal prediction, increasing the forecast correlation skill from virtually zero in the original models to a robust value of 0.69. Forecast skill for early-winter, late-winter, and seasonal-mean WACE patterns also improves substantially, with the enhanced models showing consistently higher correlations and reduced prediction errors. In addition, the approach yields notable improvements in Eurasian surface air temperature forecasts across high-, mid-, and low-latitude regions, showing that its benefits extend over a wide range of regions. The findings of this study provide practical guidance for predicting extreme cold–warm transition events and thereby support disaster-risk management and early warning efforts.
Keywords:
warm Arctic-cold Eurasia
climate prediction
Ural blocking
Siberian high
surface air temperature
subseasonal reversal
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

J
journal of geophysical research: atmospheres
IF:
0
Papers:
437
Citations:
0

Organization

N
Nanjing University of Information Science and Technology
Scholars:
2.4K
Papers: 1.0K
Citations: 1.7W
Cited Papers

Cited Papers

Citing Papers

Citing Papers