Abstract
Abstract Climate regions within the northeastern United States are defined using a combination of multivariate statistical techniques. A set of over 100 climatic variables from 641 United States and Canadian Cooperative Observer Network stations form the basis for the classification. Using various numbers of retained principal components, a suite of hierarchical clustering solutions is produced using Ward's method. A single 54-cluster solution is selected based upon the similarity of cluster outcomes using sequentially larger principal component datasets. These clusters form a set of seeds that are used to derive a final nonhierarchical cluster solution. A novel approach is used in the nonhierarchical cluster analysis to reduce bias introduced by both redundant and irrelevant data. A sequence of cluster solutions is developed in which an additional principal component is considered in each successive solution. Final cluster membership is assigned based on the maximum frequency of cluster membership within...
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