Preprints
https://doi.org/10.5194/nhess-2019-405
https://doi.org/10.5194/nhess-2019-405

  23 Mar 2020

23 Mar 2020

Review status: a revised version of this preprint is currently under review for the journal NHESS.

Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk

Luc Bonnafous1,2,3 and Upmanu Lall1,2 Luc Bonnafous and Upmanu Lall
  • 1Columbia Water Center, New York, United States
  • 2Earth and Environmental Engineering Department, Columbia University, New York, United States
  • 3Beyond Ratings, London Stock Exchange Group, Paris, France

Abstract. We present evidence that the global juxtaposition of major assets relevant to the economy with the space and time expression of extreme floods or droughts leads to a much higher aggregate risk than would be expected by chance. Using a century long, globally gridded time series that indexes net water availability, we compute local occurrences of an extreme dry or wet condition for a specified duration and return period, every year. A global exposure index is then derived for major mining commodities, by weighting extreme event occurrence by local production exposed. We note significant spatial and temporal clustering of exposure leading to the potential for fat tail risk associated with investment portfolios and supply chains. The traditional approach of climate risk analysis only considers local or point extreme value analysis and hence does not account for this spatially and temporally clustered exposure. Consequently, the global economic implications of the past or future financial and social exposure are understated in current climate risk analyses.

Luc Bonnafous and Upmanu Lall

 
Status: final response (author comments only)
Status: final response (author comments only)
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Luc Bonnafous and Upmanu Lall

Luc Bonnafous and Upmanu Lall

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Short summary
Extreme climate events can cause human and economic catastrophe at the global scale. For specific sectors, such as humanitarian aid or insurance, being able to understand how (i.e. with which frequency and intensity) these events can occur simultaneously at different locations or several times in a given amount of time and hit critical assets is all-important to design contingency plans. Here we develop and indicator to study co-occurence in space and time of wet and dry extremes.
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