Climate Zones of the Conterminous United States Defined Using Cluster Analysis

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  • 1 Department of Atmospheric Sciences, University of California, Los Angeles, Los Angeles, California
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Abstract

A regionalization of the conterminous United States is accomplished using hierarchical cluster analysis on temperature and precipitation data. The “best” combination of clustering method and data preprocessing strategy yields a set of candidate clustering levels, from which the 14-, 25-, and 8-duster solutions are chosen. Collectively, these are termed the “reference clusterings.” At the 14-cluster level, the bulk of the nation is partitioned into four principal climate zones: the Southeast, East Central, Northeastern Tier, and Interior West clusters. Many small clusters are concentrated in the Pacific Northwest. The 25-cluster solution can be used to identify the subzones within the 14 clusters. At that more detailed level, many of the areally more extensive clusters are partitioned into smaller, more internally cohesive subgroups.

The “best” clustering approach is the one that minimizes the influences of three forms of bias-methodological, latent, and information-for the dataset at hand. Sources of, and remedies for, these biases are discussed. Sensitivity tests indicate that some of the clusters in the reference clusterings lack robustness, especially those in the Northeast quadrant of the United States. Some of the tests involve small and large alterations to the data preprocessing strategy.

The major shortcomings of the analysis procedure are that the clusters are unnaturally constrained to he nonoverlapping and also that potentially important data from points outside of the political boundaries of the conterminous United States and over water are not included. Also, other variables that could be important or useful in characterizing climate type could be added to, or used in place of, the temperature and precipitation variables used herein. Further work on data preprocessing techniques is also required. Remedies for these and other shortcomings are proposed.

Abstract

A regionalization of the conterminous United States is accomplished using hierarchical cluster analysis on temperature and precipitation data. The “best” combination of clustering method and data preprocessing strategy yields a set of candidate clustering levels, from which the 14-, 25-, and 8-duster solutions are chosen. Collectively, these are termed the “reference clusterings.” At the 14-cluster level, the bulk of the nation is partitioned into four principal climate zones: the Southeast, East Central, Northeastern Tier, and Interior West clusters. Many small clusters are concentrated in the Pacific Northwest. The 25-cluster solution can be used to identify the subzones within the 14 clusters. At that more detailed level, many of the areally more extensive clusters are partitioned into smaller, more internally cohesive subgroups.

The “best” clustering approach is the one that minimizes the influences of three forms of bias-methodological, latent, and information-for the dataset at hand. Sources of, and remedies for, these biases are discussed. Sensitivity tests indicate that some of the clusters in the reference clusterings lack robustness, especially those in the Northeast quadrant of the United States. Some of the tests involve small and large alterations to the data preprocessing strategy.

The major shortcomings of the analysis procedure are that the clusters are unnaturally constrained to he nonoverlapping and also that potentially important data from points outside of the political boundaries of the conterminous United States and over water are not included. Also, other variables that could be important or useful in characterizing climate type could be added to, or used in place of, the temperature and precipitation variables used herein. Further work on data preprocessing techniques is also required. Remedies for these and other shortcomings are proposed.

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