Journal
INTERNATIONAL JOURNAL OF CLIMATOLOGY
Volume 42, Issue 13, Pages 6685-6698Publisher
WILEY
DOI: 10.1002/joc.7603
Keywords
Arctic Sea ice; cold wave; East Asia; polar vortex; self-organizing maps
Categories
Funding
- National Key Research and Development Program of China [2018YFA0605901, 2019YFC1509104]
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In winter 2020/2021, cold air outbreaks resulted in unusually low temperatures in large parts of northern-to-southeastern China. The anomalous circulation patterns causing the cold wave were a strengthening of the Siberian high, a deepening of the East Asian trough, and a weakening of the stratospheric polar vortex. The substantial sea ice loss along the Siberian coast was found to contribute significantly to the cold wave, with strong coherence between Arctic sea ice coverage and temperatures in the central-to-east Asian region. The mechanism behind this contribution involves favorable circulation patterns on climate timescale and subsequent disruptive chain reactions on weather timescale.
In winter 2020/2021, several episodes of cold air outbreaks have wreaked havoc across much of China, resulting in exceptionally low temperatures over northern-to-southeastern China. Our analysis shows that the anomalous circulation leading to the cold wave in China was characterized as: (a) a strengthening of the Siberian high, (b) a deepening of the East Asian trough, and (c) a weakening of the stratospheric polar vortex. Prior to the winter, in summer and autumn, the largest sea ice loss along the Siberian coast was observed. We therefore address the question whether the substantial sea ice loss has contributed to the cold wave. First, applying singular value decomposition (SVD) analysis, we find strong coherence between the autumn Arctic sea ice coverage and temperatures over the central-to-east Asian region with the sea ice component (SVD1_SIC) reaching a record high in 2020 and displaying a decadal shift around 2005. Associated with both the interannual and decadal variations of the SVD1_SIC, there are similar circulation anomalies as described in (a), (b) and (c) above. Second, applying self-organizing maps, wintertime daily air temperatures are clustered into nine nodes with Node-1 mostly resembling warm Arctic, cold Eurasia pattern. The frequency of Node-1 shows a similar decadal shift as observed in SVD_SIC1 above, with a correlation of about 0.56. Associated with Node-1, the circulation anomalies are consistent with features highlighted in (a), (b) and (c) above. Thus, taking all the evidence into account, we conclude that the substantial sea ice loss along the Siberian coast contributed significantly to the 2020/2021 winter cold wave in China. The mechanism behind the contribution in this study highlights that the Arctic sea ice loss is favourable for certain circulation patterns on climate timescale, reinforcing disruptive chain of reactions on weather timescale, and leading to severe cold events.
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