A tool for hierarchical climate regionalization (original) (raw)

Abstract

Climate regionalization is an important but often under-emphasized step in studies of climate variability. While most investigations of regional climate make at least an implicit attempt to focus on a study region or sub-regions that are climatically coherent in some respect, rigorous climate regionalization––in which the study area is divided on the basis of the most relevant climate metrics and at a resolution most appropriate to the data and the scientific question––has the potential to enhance the precision and explanatory power of climate studies in many cases. To facilitate the application of rigorous regionalization for climate studies, we introduce an improved hierarchical clustering method, describe a new open-source R package designed specifically for climate regionalization, and offer concise suggestions for performing appropriate regionalization. This paper describes the regionalization algorithms and presents a demonstration application in which the R package is used to regionalize Africa on the basis of interannual precipitation variability. Both the proposed methodology and the R package can be used for a broad range of applications and over different areas of the globe.

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Acknowledgments

This study was supported by the Department of Earth and Planetary Sciences, The Johns Hopkins University, and NASA Applied Sciences grant NNX09AT61G.

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Authors and Affiliations

1. Department of Earth and Planetary Sciences, The Johns Hopkins University (JHU), 3400 N. Charles Street, Olin Hall, Baltimore, MD, 21218, USA
   Hamada S. Badr, Benjamin F. Zaitchik & Amin K. Dezfuli

Authors

1. Hamada S. Badr
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2. Benjamin F. Zaitchik
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3. Amin K. Dezfuli
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Corresponding author

Correspondence toHamada S. Badr.

Additional information

Communicated by: H. A. Babaie

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Badr, H.S., Zaitchik, B.F. & Dezfuli, A.K. A tool for hierarchical climate regionalization.Earth Sci Inform 8, 949–958 (2015). https://doi.org/10.1007/s12145-015-0221-7

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• Received: 12 November 2014
• Accepted: 15 April 2015
• Published: 06 May 2015
• Issue Date: December 2015
• DOI: https://doi.org/10.1007/s12145-015-0221-7

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