Economic losses from extreme weather in the U.S. Gulf Coast region
Spatially differential contributions of climate hazard and socioeconomic exposure and vulnerability
Bibliographic Data
| ID | 17804830 |
|---|---|
| Authors | Sujithkumar Surendran Nair (0000-0003-2915-7864, Oak Ridge National Laboratory, corresponding author), Anthony W King, Jay Gulledge (0000-0002-9779-8690, University of Tennessee at Knoxville), Benjamin L Preston (0000-0002-7966-2386, Oak Ridge National Laboratory), Ryan A McManamay (0000-0002-5551-3140, Oak Ridge National Laboratory), Christopher D Clark (0000-0002-7735-4101, University of Tennessee at Knoxville) |
| Year | 2020 |
| Volume | 15 |
| Issue | 7 |
| Pages | 074038-074038 |
| Publication date | 2020-03-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/ab7b9a |
| OpenAlex | W3009284381 |
| Language | EN |
| Citations received | 1 |
| References cited | 20 |
Worldwide economic losses from extreme weather events (EWE) have increased over recent decades, with significant geographic heterogeneity in damages. The IPCC defines the risk from EWE as a function of the climate hazard, socioeconomic exposure, and vulnerability. Although these three drivers vary at fine spatial scales, spatial variability largely has been overlooked in assessments of the drivers of economic loss from EWE. Using cluster analysis, we developed a novel socio-climate hazard typology (SCT) that integrates locally defined climate hazard and socioeconomic exposure and social vulnerability typologies. The results identified 838 unique SCT types impacted by EWE across the Gulf Coastal United States during 1981–2010. We regressed the SCT types and their constituent hazard and socioeconomic components against the cumulative economic loss (1981–2010) from EWE for each SCT type. Across the landscape, economic damages of SCT types were determined by unique, spatially explicit combinations of different risk factors, even in explaining the same level of economic loss. For example, multi-billion-dollar damages in the central Gulf Coast and peninsular Florida were explained by different drivers of risk, with damages in the former explained by additive interaction between climate hazard and multiplicative interaction between climate hazard and socioeconomic exposure and vulnerability, and in the latter explained by socioeconomic exposure and vulnerability. These results highlight the need to diagnose additive and multiplicative interactions among drivers of EWE risk in a spatially explicit context
Climate change · Climatology · Damages · Geography · Hazard · Population · Socioeconomic status · Demography · Disaster Management and Resilience · Environmental Science · Flood Risk Assessment and Management · Tropical and Extratropical Cyclones Research · Ecology
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| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |