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Volume 9, issue 6
The Cryosphere, 9, 2237–2251, 2015
https://doi.org/10.5194/tc-9-2237-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 9, 2237–2251, 2015
https://doi.org/10.5194/tc-9-2237-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 04 Dec 2015

Research article | 04 Dec 2015

Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations

N. Melia et al.

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Cited articles

Blanchard-Wrigglesworth, E. and Bitz, C. M.: Characteristics of Arctic Sea-Ice Thickness Variability in GCMs, J. Climate, 27, 8244–8258, https://doi.org/10.1175/Jcli-D-14-00345.1, 2014.
Boe, J., Hall, A., and Qu, X.: September sea-ice cover in the Arctic Ocean projected to vanish by 2100, Nat. Geosci, 2, 341–343, https://doi.org/10.1038/ngeo467, 2009.
Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On the need for bias correction of regional climate change projections of temperature and precipitation, Geophys. Res. Lett., 35, L20709, https://doi.org/10.1029/2008gl035694, 2008.
Day, J. J., Hargreaves, J. C., Annan, J. D., and Abe-Ouchi, A.: Sources of multi-decadal variability in Arctic sea ice extent, Environ. Res. Lett., 7, 034011, https://doi.org/10.1088/1748-9326/7/3/034011, 2012.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.: Evaluation of Climate Models, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 741–866, 2013.
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Short summary
Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. We present a new method to constrain global climate model simulations of SIT to narrow projection uncertainty via a statistical bias-correction technique.
Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about...
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