Similarities between sea ice area variations and satellite-derived terrestrial biosphere and cryosphere parameters across the Arctic

Abstract. Satellite time series availability for the Arctic Ocean and adjacent land areas allows cross-comparisons for cryosphere vs. vegetation parameters. Previous studies focused on correlation analyses between vegetation indices (time-integrated normalized difference vegetation index (TI-NDVI) and maximum normalized difference vegetation index (MaxNDVI)) of tundra regions and sea ice extent for selected months. We have refined these analyses through the consideration of distinct sea ice basins and all months and through an extension to south of the treeline, and we have included cryosphere essential climate variables such as snow water equivalent (SWE; March as proxy for annual maximum) and mean annual ground temperature (MAGT) in permafrost areas. The focus was on 2000–2019, reflecting data availability. As a first step, we derived trends. Changes across all the different parameters could be specifically determined for eastern Siberia. Then, time series were de-trended and correlations determined. Linkages between sea ice area (SIA) and normalized difference vegetation index (NDVI) across tundra regions were confirmed, where lower sea ice extent coincides with higher NDVI. The regional extension beyond the treeline revealed linkages for northern European Russia and partially over northern Scandinavia. Differences compared to previous studies ending in 2008 were found for the Kara Sea region and adjacent land area, indicating recent changes. In the case of MAGT, high significant correlations were found for more distant sea ice basins than for the NDVI derivatives, indicating influences of large-scale atmospheric circulation patterns. Negative and positive significant correlations were found for March SWE depending on the SIA month and region. Also, months other than September (sea ice extent minimum) were found to have high correlations vs. land-based variables, with distinct differences across sea ice basins. The fraction of data points with significant correlations north of 60° N was higher for SWE and MAGT than for the NDVI derivatives. Fractions for SWE were higher for Eurasia than northern America. Autumn (incl. October and November) and mid-winter (incl. February, March) were most relevant for both investigated cryosphere-related parameters, MAGT and SWE. Although similar patterns could be found for TI-NDVI and MaxNDVI, a higher proportion of significant correlations was observed for TI-NDVI. The datasets provide a baseline for future studies on common drivers of essential climate parameters and causative effects across the Arctic.