4.8 Article

A reconciled estimate of the influence of Arctic sea-ice loss on recent Eurasian cooling

Journal

NATURE CLIMATE CHANGE
Volume 9, Issue 2, Pages 123-+

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41558-018-0379-3

Keywords

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Funding

  1. Integrated Research Program for Advancing Climate Models from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan
  2. Arctic Challenge for Sustainability (ArCS) Program from MEXT, Japan
  3. Japan Science and Technology Agency through the Belmont Forum Collaborative Research Action 'InterDec' project

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Northern midlatitudes, over central Eurasia in particular, have experienced frequent severe winters in recent decades(1-3). A remote influence of Arctic sea-ice loss has been suggested(4-14); however, the importance of this connection remains controversial because of discrepancies among modelling and between modelling and observational studies(15-17). Here, using a hybrid analysis of observations and multi-model large ensembles from seven atmospheric general circulation models, we examine the cause of these differences. While all models capture the observed structure of the forced surface temperature response to sea-ice loss in the Barents-Kara Seas-including Eurasian cooling-we show that its magnitude is systematically underestimated. Owing to the varying degrees of this underestimation of sea-ice-forced signal, the signal-to-noise ratio differs markedly. Correcting this underestimation reconciles the discrepancy between models and observations, leading to the conclusion that similar to 44% of the central Eurasian cooling trend for 1995-2014 is attributable to sea-ice loss in the Barents-Kara Seas. Our results strongly suggest that anthropogenic forcing has significantly amplified the probability of severe winter occurrence in central Eurasia via enhanced melting of the Barents-Kara sea ice. The difference in underestimation of signal-to-noise ratio between models therefore calls for careful experimental design and interpretation for regional climate change attribution.

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