Sources of multi-decadal variability in Arctic sea ice extent

The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend...

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Bibliographic Details
Published in:Environmental Research Letters
Main Authors: Day, J. J., Hargreaves, J C, Annan, J D, Abe-Ouchi, A
Format: Article in Journal/Newspaper
Language:English
Published: Institute of Physics 2012
Subjects:
Arctic
Sea ice
Online Access:https://centaur.reading.ac.uk/28905/
https://centaur.reading.ac.uk/28905/1/Day%20et%20al.%20-%202012%20-%20Sources%20of%20multi-decadal%20variability%20in%20Arctic%20sea.pdf
http://iopscience.iop.org/1748-9326/7/3/034011
Description
Summary:The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability.

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