Avalanche activity in an extreme maritime climate: The application of classification trees for forecasting

Two 10 fold cross validated classification trees were created, and suggested for use in forecasting. The classification tree with highest accuracy of 85% predicted avalanche days less well at 79%. An alternative tree using only wind speed and wind speed and precipitation combined in a temperature sensitive wind drift parameter resulted in a lower overall accuracy of 78%, but permitted a higher rate of correct prediction for avalanche days at 86%. The alternative, more conservative tree also reduced the number of false negative cases (observed as avalanche days, but predicted as non-avalanche days) from 31 to 20 at a cost of increasing the false positive or false alarm rate.