Editorial Type:
Article
Article Type:
Research Article

Revisiting Climate Region Definitions via Clustering

Robert Lund Department of Mathematical Sciences, Clemson University, Clemson, South Carolina

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Bo Li Department of Statistics, Purdue University, West Lafayette, Indiana

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Print Publication:
01 Apr 2009
DOI:
https://doi.org/10.1175/2008JCLI2455.1
Page(s):
1787–1800
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Abstract

This paper introduces a new distance metric that enables the clustering of general climatic time series. Clustering methods have been frequently used to partition a domain of interest into distinct climatic zones. However, previous techniques have neglected the time series (autocorrelation) component and have also handled seasonal features in a suboptimal way. The distance proposed here incorporates the seasonal mean and autocorrelation structures of the series in a natural way; moreover, trends and covariate effects can be considered. As an important by-product, the methods can be used to statistically assess whether two stations can serve as reference stations for one another. The methods are illustrated by partitioning 292 weather stations within the state of Colorado into six different zones.

Corresponding author address: Robert Lund, Department of Mathematical Sciences, Clemson University, Clemson, SC 29634-0975. Email: lund@clemson.edu

Abstract

This paper introduces a new distance metric that enables the clustering of general climatic time series. Clustering methods have been frequently used to partition a domain of interest into distinct climatic zones. However, previous techniques have neglected the time series (autocorrelation) component and have also handled seasonal features in a suboptimal way. The distance proposed here incorporates the seasonal mean and autocorrelation structures of the series in a natural way; moreover, trends and covariate effects can be considered. As an important by-product, the methods can be used to statistically assess whether two stations can serve as reference stations for one another. The methods are illustrated by partitioning 292 weather stations within the state of Colorado into six different zones.

Corresponding author address: Robert Lund, Department of Mathematical Sciences, Clemson University, Clemson, SC 29634-0975. Email: lund@clemson.edu

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