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Simulating Impacts of Ice Storms on Forest Ecosystems
Published on: June 30, 2020
Arctic sea ice trends, variability and implications for seasonal ice forecasting
Mark C Serreze1, Julienne Stroeve2
1National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Campus Box 449, Boulder, CO 80309-0449, USA serreze@kryos.colorado.edu.
Abstract:
September Arctic sea ice extent over the period of satellite observations has a strong downward trend, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward trend itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening trend. These findings have implications for seasonal ice forecasting. In particular, while advances in observing sea ice thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability.
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