Item: Decision trees predicting avalanche response: tools for training?
Title: Decision trees predicting avalanche response: tools for training?
Proceedings: Proceedings of the 2000 International Snow Science Workshop, October 1-6, Big Sky, Montana
Authors: Kelly Elder, Rocky Mountain Experiment Station, US Forest Service, Fort Collins, Colorado, Robert E. Davis, Cold Regions Research and Engineering Laboratory, US Army Engineer Research and Development Center, Hanover, New Hampshire
Abstract: This contribution shows examples of decision trees relating weather and between-storm factors to expected maximum avalanche size based on the historical records from Mammoth Mountain, California and Alta, Utah. The structure of the trees involves making binary (yes/no) decisions (e.g. 24-hour precipitation > 40 mm) to proceed from one decision node to the next until the probable response to the given conditions is reached (e.g. maximum avalanche size =3). At each node the decision trees provide the critical factor in distinguishing one situation from another. We suggest that the decision trees in poster form may provide useful and important training guidelines for avalanche workers by increasing their historical perspective, and by emphasizing the variety and range of factors contributing to avalanche release.
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Keywords: avalanche, weather factors, avalanche training
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