Arctic weather variability and connectivity

Jun Meng; Jingfang Fan; Uma S. Bhatt; Jürgen Kurths

doi:10.1038/s41467-023-42351-x

Arctic weather variability and connectivity

Jun Meng, Jingfang Fan, Uma S. Bhatt, Jürgen Kurths

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The Arctic’s rapid sea ice decline may influence global weather patterns, making the understanding of Arctic weather variability (WV) vital for accurate weather forecasting and analyzing extreme weather events. Quantifying this WV and its impacts under human-induced climate change remains a challenge. Here we develop a complexity-based approach and discover a strong statistical correlation between intraseasonal WV in the Arctic and the Arctic Oscillation. Our findings highlight an increased variability in daily Arctic sea ice, attributed to its decline accelerated by global warming. This weather instability can influence broader regional patterns via atmospheric teleconnections, elevating risks to human activities and weather forecast predictability. Our analyses reveal these teleconnections and a positive feedback loop between Arctic and global weather instabilities, offering insights into how Arctic changes affect global weather. This framework bridges complexity science, Arctic WV, and its widespread implications.

Original language	English
Article number	6574
Journal	Nature Communications
Volume	14
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-42351-x
State	Published - 18 Oct 2023
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2023, Springer Nature Limited.

Funding

The authors wish to thank T. Liu for his helpful suggestions. We acknowledge funding support from the Ministry of Science and Technology of China (2019QZKK0906). J.M. and J.F. acknowledge the support of the National Natural Science Foundation of China (Grant No. 12205025, 12275020, 12135003). U.S.B. acknowledges funding support from the National Science Foundation’s Office of Polar Programs through Grants OPP-1749081 for the Sea Ice Prediction Network-Phase 2 (SIPN2). J.K. acknowledges funding support from the Sidney Chapman Chair Endowment through the College of Natural Sciences and Mathematics at the University of Alaska Fairbanks.

Funders	Funder number
Office of Polar Programs	OPP-1749081
University of Alaska Fairbanks
National Natural Science Foundation of China	12135003, 12275020, 12205025
Ministry of Science and Technology of the People's Republic of China	2019QZKK0906

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-023-42351-x

Cite this

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Arctic weather variability and connectivity

Abstract

Bibliographical note

Funding

UN SDGs

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