On the relevance of serial cyclone clustering for Arctic sea ice

Short-term changes in Arctic sea-ice area are largely driven by weather events such as synoptic-scale cyclones, which typically cause ice loss during warm and stormy conditions in the Arctic. Physical mechanisms of this ice loss include enhanced sea-ice divergence, poleward ice drift, and changes in the surface energy budget due to advection of warm-moist air masses. In extreme cases, enhanced basal melt of sea ice occurs due to upward mixing of relatively warm ocean water. Such anomalous conditions are prolonged when several cyclones follow rapidly on each other, a phenomenon referred to as serial cyclone clustering. Serial cyclone clustering has been identified as a high-impact phenomenon, substantially amplifying wind damage, precipitation, and sea level extremes across several regions of the Earth. However, this weather phenomenon and its impacts have not yet been examined in the polar regions.

Here, we analyze changes in Arctic sea-ice concentration (SIC) for periods of serial cyclone clustering utilizing satellite observations and reanalysis data from 1979-2024. While cyclones generally decrease SIC compared to non-cyclone conditions in cold and warm seasons, the impact of cyclone clusters is approximately twice as strong and persists 2.5 times longer than for solitary cyclones. The amount of SIC-loss due to cyclone clusters scales with the intensity and number of clustered storms, and greater SIC-loss occurs during 2000-2024 compared to 1979-1999.

These findings emphasize the need to better understand drivers of serial cyclone clustering in the Arctic and more generally highlight the relevance of accumulated impacts of clustered weather events for Arctic sea-ice variability. Applying similar frameworks to other types of weather events and other target quantities (e.g. snow accumulation on sea ice or wind-driven ocean currents) could help to further sharpen our understanding of the role of weather extremes in the coupled polar climate system.