Impacts of Sea Ice Thickness Initialization on Seasonal Arctic Sea Ice Predictions

摘要: AbstractA promising means for increasing skill of seasonal predictions Arctic sea ice is improving thickness (SIT) initial conditions; however, sparse SIT observations limit this potential. Using the Canadian Climate Model, version 3 (CanCM3), three statistical models designed to estimate fields initialization in a real-time forecasting system are applied initialize hindcasts over 1981–2012. Hindcast assessed relative two benchmark methods (SIT-IMs): climatological currently used operationally and values from Pan-Arctic Ice Ocean Modeling Assimilation System (PIOMAS). Based on several measures skill, generally improved initialization. The accuracy with which represent both thinning pack time interannual variability impacts predictive pan-Arctic area (SIA) regional concentration (SIC)...