Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations

How to cite this Dataset

Melia, Nathanael (2015): Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations. University of Reading. Dataset. https://doi.org/10.17864/1947.9

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