In recent decades, Northeast China (NEC) has witnessed a substantial 20% rise in the occurrence of intense winter snowfall, resulting in a notable increase in the overall snowfall accumulation. Using Empirical Orthogonal Function (EOF) analysis, this study identifies a dominant interdecadal variation of the winter extreme snowfall with a turning point around 2000. The analysis uncovers abnormal atmospheric circulations linked to the positive phase of the like-Scandinavian pattern and anomalous North Pacific anticyclone, providing favorable conditions for cold air outbreak and water vapor enhancement for the increase in extreme snowfall. The positive phase of the like-Scandinavian pattern exhibits a strong correlation with sea ice loss in the Baffin Bay, Greenland Sea, and Barents-Kara Sea (BGBK). This positive pattern is primarily sustained by a positive feedback mechanism stemming from sea-ice-atmosphere interactions. Specifically, the positive like-Scandinavian pattern leads to increased water vapor over the BGBK region, promoting sea ice loss through enhanced clear-sky downward longwave radiation (CDLW) and increased surface turbulent heat flux. Conversely, a positive sea surface temperature anomaly prevails in the negative phase of the Interdecadal Pacific Oscillation (IPO), triggering an anomalous anticyclone over the North Pacific and East Asia, contributing to the observed increase in extreme snowfall over NEC. Furthermore, this study demonstrates a modulating relationship between the positive like-Scandinavian pattern and the anomalous anticyclone associated with the negative phase of the IPO, achieved through the triggering of Rossby wave trains, which were verified through numerical experiments using an atmospheric general circulation model. These results underscore the joint impact of interdecadal variability in Arctic Sea ice and the IPO on the decadal increase in winter extreme snowfall over NEC.

Extreme snowfall,Arctic Sea ice,Interdecadal Pacific Oscillation,Sea-ice-atmosphere interaction,Northeast China