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A hierarchical collection of political/economic regions for analysis of climate extremes

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  • Dáithí A. Stone

    (Global Climate Adaptation Partnership
    Lawrence Berkeley National Laboratory
    National Institute of Water and Atmospheric Research)

Abstract

This paper describes five sets of regions intended for use in summarizing extreme weather over Earth’s land areas from a climate perspective. The sets differ in terms of their target size: ∼10 Mm2, ∼5 Mm2, ∼2 Mm2, ∼0.5 Mm2, and ∼0.1 Mm2 (where 1 Mm2= 1 million km2). The regions are based on political/economic divisions, and hence are intended to be primarily aligned with geographical domains of decision-making and disaster response rather than other factors such as climatological homogeneity. This paper describes the method for defining these sets of regions; provides the final definitions of the regions; and performs some comparisons across the five sets and other available regional definitions with global land coverage, according to climatological and non-climatological properties.

Suggested Citation

  • Dáithí A. Stone, 2019. "A hierarchical collection of political/economic regions for analysis of climate extremes," Climatic Change, Springer, vol. 155(4), pages 639-656, August.
    • Handle: RePEc:spr:climat:v:155:y:2019:i:4:d:10.1007_s10584-019-02479-6
    DOI: 10.1007/s10584-019-02479-6
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    Cited by:

    1. Mark D. Risser & William D. Collins & Michael F. Wehner & Travis A. O’Brien & Huanping Huang & Paul A. Ullrich, 2024. "Anthropogenic aerosols mask increases in US rainfall by greenhouse gases," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    2. Vikki Thompson & Dann Mitchell & Gabriele C. Hegerl & Matthew Collins & Nicholas J. Leach & Julia M. Slingo, 2023. "The most at-risk regions in the world for high-impact heatwaves," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    3. Nick Dunstone & Doug M. Smith & Steven C. Hardiman & Paul Davies & Sarah Ineson & Shipra Jain & Chris Kent & Gill Martin & Adam A. Scaife, 2023. "Windows of opportunity for predicting seasonal climate extremes highlighted by the Pakistan floods of 2022," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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