Arctic weather variability and connectivity
Jun Meng,
Jingfang Fan (),
Uma S. Bhatt and
Jürgen Kurths
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Jun Meng: Beijing University of Posts and Telecommunications
Jingfang Fan: Beijing Normal University
Uma S. Bhatt: University of Alaska Fairbanks
Jürgen Kurths: Potsdam Institute for Climate Impact Research
Nature Communications, 2023, vol. 14, issue 1, 1-11
Abstract:
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.
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42351-x
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DOI: 10.1038/s41467-023-42351-x
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