Sea-ice variations and trends during the Common Era in the Atlantic sector of the Arctic Ocean

Abstract

Sea ice is crucial in regulating the heat balance between the ocean and atmosphere and quintessential for supporting the prevailing Arctic food web. Due to limited and often local data availability back in time, the sensitivity of sea-ice proxies to long-term climate changes is not well constrained, which renders any comparison with palaeoclimate model simulations difficult. Here we compiled a set of marine sea-ice proxy records with a relatively high temporal resolution of at least 100 years, covering the Common Era (past 2k years) in the Greenland–North Atlantic sector of the Arctic to explore the presence of coherent long-term trends and common low-frequency variability, and we compared those data with transient climate model simulations. We used cluster analysis and empirical orthogonal functions to extract leading modes of sea-ice variability, which efficiently filtered out local variations and improved comparison between proxy records and model simulations. We find that a compilation of multiple proxy-based sea-ice reconstructions accurately reflects general long-term changes in sea-ice history, consistent with simulations from two transient climate models. Although sea-ice proxies have varying mechanistic relationships to sea-ice cover, typically differing in habitat or seasonal representation, the long-term trend recorded by proxy-based reconstructions showed a good agreement with summer minimum sea-ice area from the model simulations. The short-term variability was not as coherent between proxy-based reconstructions and model simulations. The leading mode of simulated sea ice associated with the multidecadal to centennial timescale presented a relatively low explained variance and might be explained by changes in solar radiation and/or inflow of warm Atlantic waters to the Arctic Ocean. Short variations in proxy-based reconstructions, however, are mainly associated with local factors and the ecological nature of the proxies. Therefore, a regional or large-scale view of sea-ice trends necessitates multiple spatially spread sea-ice proxy-based reconstructions, avoiding confusion between long-term regional trends and short-term local variability. Local-scale sea-ice studies, in turn, benefit from reconstructions from well-understood individual research sites.