Seasonal to interannual Arctic sea-ice predictability in current GCMs

Tietsche, S., Day, J.J., Guemas, V., Hurlin, W. J., Keeley, S.P.E., Matei, D., Msadek, R., Collins, M. and Hawkins, E. ORCID: https://orcid.org/0000-0001-9477-3677 (2014) Seasonal to interannual Arctic sea-ice predictability in current GCMs. Geophysical Research Letters, 41 (3). pp. 1035-1043. ISSN 0094-8276 doi: 10.1002/2013GL058755

Abstract/Summary

We establish the first inter-model comparison of seasonal to interannual predictability of present-day Arctic climate by performing coordinated sets of idealized ensemble predictions with four state-of-the-art global climate models. For Arctic sea-ice extent and volume, there is potential predictive skill for lead times of up to three years, and potential prediction errors have similar growth rates and magnitudes across the models. Spatial patterns of potential prediction errors differ substantially between the models, but some features are robust. Sea-ice concentration errors are largest in the marginal ice zone, and in winter they are almost zero away from the ice edge. Sea-ice thickness errors are amplified along the coasts of the Arctic Ocean, an effect that is dominated by sea-ice advection. These results give an upper bound on the ability of current global climate models to predict important aspects of Arctic climate.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/35894
Identification Number/DOI	10.1002/2013GL058755
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Geophysical Union
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