Capacity of a set of CMIP6 models to simulate Arctic sea ice drift
Abstract
Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.
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