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Published on: June 13, 2020
Subseasonal variability and the "Arctic warming-Eurasia cooling" trend
Zhicong Yin1, Yijia Zhang2, Botao Zhou2
1Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519080, China; Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
The Arctic warming-Eurasia cooling trend has weakened, with more frequent subseasonal shifts between warm Arctic-cold Eurasia (WACE) and cold Arctic-warm Eurasia (CAWE) patterns. Tropical ocean temperatures influence these shifts, impacting mid-latitude climate extremes.
Area of Science:
- * Climate Science
- * Atmospheric Science
- * Earth System Science
Background:
- * The "Arctic warming-Eurasia cooling" trend significantly influences weather patterns and climate extremes at lower latitudes.
- * This trend has weakened between 2012 and 2021, with increased subseasonal variability in the warm Arctic-cold Eurasia (WACE) and cold Arctic-warm Eurasia (CAWE) patterns.
- * Subseasonal intensity of WACE/CAWE patterns remained comparable to earlier periods (1996–2011) despite the overall trend weakening.
Purpose of the Study:
- * To investigate the co-occurrence of subseasonal variability and trend changes in the WACE/CAWE pattern.
- * To identify the drivers influencing the WACE/CAWE pattern and its subseasonal phase reversals.
- * To understand the implications for predicting climate extremes at mid- to low latitudes.
Main Methods:
- * Analysis of long-term reanalysis datasets.
- * Utilization of Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations.
- * Numerical experiments using the Community Atmosphere Model (CAM) and Atmospheric Model Intercomparison Project (AMIP).
Main Results:
- * Tropical Atlantic and Indian Ocean sea surface temperature anomalies significantly impact the WACE/CAWE pattern in early and late winter, respectively.
- * These ocean temperature anomalies were confirmed as primary drivers through numerical experiments.
- * The coordination of tropical ocean influences effectively modulates subseasonal phase reversals between WACE and CAWE patterns, as observed in winters 2020 and 2021.
Conclusions:
- * Subseasonal variability plays a crucial role in modulating the WACE/CAWE pattern, even as the long-term trend weakens.
- * Tropical ocean conditions are key predictors for the subseasonal phase of the WACE/CAWE pattern.
- * Subseasonal climate dynamics must be considered for accurate prediction of climate extremes in mid- to low latitudes.
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