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

<p>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...

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Main Authors: L. Bonnafous, U. Lall
Format: Article
Language:English
Published: Copernicus Publications 2021-08-01
Series:Natural Hazards and Earth System Sciences
Online Access:https://nhess.copernicus.org/articles/21/2277/2021/nhess-21-2277-2021.pdf
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spelling doaj-e9967a3afd994cd4b4f8b61e24d2822b2021-08-02T13:53:47ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812021-08-01212277228410.5194/nhess-21-2277-2021Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed riskL. Bonnafous0L. Bonnafous1L. Bonnafous2U. Lall3U. Lall4Columbia Water Center, New York, United StatesEarth and Environmental Engineering Department, Columbia University, New York, United StatesWorld Bank, Washington, DC, United StatesColumbia Water Center, New York, United StatesEarth and Environmental Engineering Department, Columbia University, New York, United States<p>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, every year we compute local occurrences of an extreme “dry” or “wet” condition for a specified duration and return period. 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 at the global level leading to the potential for fat-tailed risk associated with investment portfolios and supply chains. This may not be a surprise to climate scientists familiar with the space-time patterns of interannual to decadal climate oscillations that can affect remote regions through teleconnections. However, the traditional approach of climate risk analysis only considers local or point extreme value analysis and hence does not account for temporal and spatial clustering of exposure for global portfolios. As multinational enterprises and supply chains assess and disclose physical climate risks, they need to consider the much higher chance that they may have multiple assets that may be exposed to extreme wet and/or dry climate extremes in the same year.</p>https://nhess.copernicus.org/articles/21/2277/2021/nhess-21-2277-2021.pdf
collection DOAJ
language English
format Article
sources DOAJ
author L. Bonnafous
L. Bonnafous
L. Bonnafous
U. Lall
U. Lall
spellingShingle L. Bonnafous
L. Bonnafous
L. Bonnafous
U. Lall
U. Lall
Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
Natural Hazards and Earth System Sciences
author_facet L. Bonnafous
L. Bonnafous
L. Bonnafous
U. Lall
U. Lall
author_sort L. Bonnafous
title Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
title_short Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
title_full Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
title_fullStr Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
title_full_unstemmed Space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
title_sort space-time clustering of climate extremes amplify global climate impacts, leading to fat-tailed risk
publisher Copernicus Publications
series Natural Hazards and Earth System Sciences
issn 1561-8633
1684-9981
publishDate 2021-08-01
description <p>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, every year we compute local occurrences of an extreme “dry” or “wet” condition for a specified duration and return period. 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 at the global level leading to the potential for fat-tailed risk associated with investment portfolios and supply chains. This may not be a surprise to climate scientists familiar with the space-time patterns of interannual to decadal climate oscillations that can affect remote regions through teleconnections. However, the traditional approach of climate risk analysis only considers local or point extreme value analysis and hence does not account for temporal and spatial clustering of exposure for global portfolios. As multinational enterprises and supply chains assess and disclose physical climate risks, they need to consider the much higher chance that they may have multiple assets that may be exposed to extreme wet and/or dry climate extremes in the same year.</p>
url https://nhess.copernicus.org/articles/21/2277/2021/nhess-21-2277-2021.pdf
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