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The Cryosphere An interactive open-access journal of the European Geosciences Union
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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. Melia1, K. Haines2, and E. Hawkins3 N. Melia et al.
  • 1Department of Meteorology, University of Reading, Reading, UK
  • 2National Centre for Earth Observation, Department of Meteorology, University of Reading, Reading, UK
  • 3NCAS-Climate, Department of Meteorology, University of Reading, Reading, UK

Abstract. Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 global climate models (GCMs) produce a wide range of simulated SIT in the historical period (1979–2014) and exhibit various biases when compared with the Pan-Arctic Ice–Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the spread in projections of SIT and reveals the significant contributions of climate internal variability in the first half of the century and of scenario uncertainty from the mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to reduce spread in climate projections more generally.

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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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