University of Reading Research Data Archive

Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations

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Description

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 to narrow projection uncertainty via a statistical bias correction technique. This method is applied to six GCMs from CMIP5, the outputs of which are available in this dataset. Results are reported in: Melia, N., Haines, K., and Hawkins, E.: Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations, The Cryosphere Discuss., 9, 3821-3857, doi:10.5194/tcd-9-3821-2015, 2015.

Alternative title: MAVRIC dataset
Resource Type: Dataset
Creators: Melia, Nathanael
Contributors: Haines, Keith and Hawkins, Ed
Rights-holders: Nathanael Melia
Data Publisher: University of Reading
Publication Year: 2015
Data last accessed: 22 June 2024
DOI: https://doi.org/10.17864/1947.9
Metadata Record URL: https://researchdata.reading.ac.uk/id/eprint/9
Organisational units: Science > School of Mathematical, Computational and Physical Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Computational and Physical Sciences > NCAS
Science > School of Mathematical, Computational and Physical Sciences > Department of Meteorology
Participating Organisations: University of Reading
Keywords: Arctic, sea ice thickness, CMIP5, projections, uncertainty, bias correction
Rights:
Data Availability: OPEN

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