  Sea ice, or frozen ocean water, freezes and melts every year in the Arctic.
Forecasts of where sea ice will be located weeks to months in advance have
become more important as the amount of sea ice declines due to climate change,
for maritime planning and other uses. Typical sea ice forecasts are made with
ensemble models, physics-based models of sea ice and the surrounding ocean and
atmosphere. This paper introduces Mixture Contour Forecasting, a method to
forecast sea ice probabilistically using a mixture of two distributions, one
based on post-processed output from ensembles and the other on observed sea ice
patterns in recent years. At short lead times, these forecasts are better
calibrated than unadjusted dynamic ensemble forecasts and other statistical
reference forecasts. To produce these forecasts, a statistical technique is
introduced that directly models the sea ice edge contour, the boundary around
the region that is ice-covered. Mixture Contour Forecasting and reference
methods are evaluated for monthly sea ice forecasts for 2008-2016 at lead times
ranging from 0.5-6.5 months using one of the European Centre for Medium-Range
Weather Forecasts ensembles.
