Estimating the contribution of Arctic sea-ice loss to central Asia temperature anomalies: the case of winter 2020/2021

Arctic sea-ice cover has declined drastically in recent decades, notably in the Barents-Kara Seas (BKS). Previous research has linked low autumn BKS-ice cover to subsequent cold Eurasian winters. This lagged relationship was observed in 2020/2021. Using a causal network framework grounded in known p...

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Bibliographic Details
Main Authors: Lara R Cosford, Rohit Ghosh, Marlene Kretschmer, Clare Oatley, Theodore G Shepherd
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Letters
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Online Access:https://doi.org/10.1088/1748-9326/adae22
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Summary:Arctic sea-ice cover has declined drastically in recent decades, notably in the Barents-Kara Seas (BKS). Previous research has linked low autumn BKS-ice cover to subsequent cold Eurasian winters. This lagged relationship was observed in 2020/2021. Using a causal network framework grounded in known physical mechanisms, we assess how strongly one factor directly influences another (i.e. the causal relationship) and apply this analysis to the anomalies from 2020/2021. We show that although year-to-year BKS-ice variations have only a minor impact on Central Asia temperatures, that causal effect becomes important for attribution and prediction when we consider the large long-term trend in BKS-ice cover. In particular, we find that Central Asia’s 2021 negative winter surface air temperature anomaly (relative to 1980–2020) can be fully explained by the BKS-ice anomaly. We further estimate that BKS-ice loss has more than halved the winter warming over Central Asia over the past 40 years. Hence rather than debating a cooling trend in Central Asia during winter, we propose shifting the focus to the influence of Arctic Amplification on anticipated warming trends. This study illustrates the efficacy of causal network analysis, which has implications for seasonal prediction and attribution of midlatitude winter anomalies.
ISSN:1748-9326