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Philos Trans A Math Phys Eng Sci. 2015 Jul 13;373(2045). pii: 20140159. doi: 10.1098/rsta.2014.0159.

Arctic sea ice trends, variability and implications for seasonal ice forecasting.

Author information

1
National 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.
2
National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Campus Box 449, Boulder, CO 80309-0449, USA Centre for Polar Observation and Modelling, Pearson Building, University College London, Gower Street, London WC1E 6BT, UK.

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.

KEYWORDS:

atmospheric variability; feedbacks; prediction; sea ice; trends

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