Meeting
2016 SIPN Workshop
Presentation Type
plenary
Presentation Theme
Predictions and Dynamical Predictive Systems II
Abstract Authors

Michael Sigmond, Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, michael.sigmond [at] canada.ca
Cathy Reader, Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, cathy.reader [at] canada.ca
Greg Flato, Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, greg.flato [at] canada.ca
Bill Merryfield, Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, bill.merryfield [at] canada.ca
Adrienne Tivy, Canadian Ice Services, adrienne.tivy [at] canada.ca

Abstract

In recent years, dynamical seasonal forecast systems have started to incorporate interactive sea ice components, allowing for sea ice forecasts on seasonal (1-12 month) timescales. Previous investigations on the forecast skill in such dynamical forecast systems have mainly focused on area-integrated sea ice quantities, which are of little use to end-users. Here we assess the skill in predictions of ice-free and freeze-up dates - variables that are highly relevant to shipping - in a set of hindcasts performed with the Canadian Seasonal to Interannual Prediction System (CanSIPS).

We find statistically significant skill for both ice-free and freeze-up dates in large parts of the Arctic, including Hudson's Bay, Baffin Bay/Labrador Sea and the Barents, Kara and Chukchi Seas. Skill is particularly large for freeze-up dates with significant skill at lead times up to 6-12 months. While most of the skill of ice-free dates stems from persistence of sea ice concentration anomalies, the longer-lead time skill for freeze-up dates is due to a reemergence mechanism involving ocean temperatures. These results highlight the potential for dynamical forecast systems to provide valuable forecasts of socio-economically relevant sea ice variables on seasonal timescales.

Time
-