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

Abstract

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.

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

“…Coherence is characterized by warmer colors, with significant regions circled in black. A multitaper spectral analysis (Rahim et al, 2017;Slepian, 1978;Thomson, 1982) also shows coherence for cycles of 4 years, consistent with the ENSO and North Atlantic Oscillation (NAO) phenomena (Fig. S14, where common oscillatory behaviors from multitaper analysis are marked by spikes with the x axes corresponding to cycles per year; thus a 0.2 value corresponds to a 5-year cycle) and with the Pacific Decadal Oscillation (PDO) index at scales of about 8 years.…”

“…Using the package biwavelet (Gouhier et al, 2016), we investigate the spectra and the coherence across series. Spectra are also assessed using multitaper analysis (Rahim et al, 2017).…”

Climate-Catchment-Soil Control on Hydrological Droughts in Peninsular India

“…We used daily observed streamflow records of past 50 years (1965 -2019) from 98 stream gauges over PRB in a multi-stage framework 19,20 (Fig. 1) to quantify the contiguity in locations and time of occurrence of hydrologic droughts (the space-time clustering 21 or synchronicity in drought properties) and identify potential KDDs from a wide range of climate, soil, and terrain attributes (Fig. 1, Supplementary Fig.…”