Abstract


A statistical linear regression model is used to forecast end of summer ice
conditions in the Beaufort Sea with several months lead time.  The model retains six sea ice and atmospheric parameters, where relatively more (less) multiyear ice
concentration, fewer (more) heating degree days, lower (higher) North Atlantic
Oscillation index values, higher (lower) Tropical-Northern Hemisphere index values, higher (lower) January Pacific-Decadal Oscillation index values, and lower (higher) June Arctic Oscillation index values are associated with lighter (heavier) sea ice conditions.  Cross validation diagnostics indicate that variations in these parameters are related to 91% of the variation in sea ice conditions, suggesting a relatively simple ice-atmosphere statistical model can be used to forecast end of summer ice conditions in the Beaufort Sea.

Submitted to Geophysical Research Letters
Dr. Sheldon D. Drobot   and Dr. James A. Maslanik