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On the relation between weather-related disaster impacts,vulnerability and climate change
Authors:Hans Visser  Arthur C. Petersen  Willem Ligtvoet
Affiliation:1. PBL Netherlands Environmental Assessment Agency, Bilthoven, The Netherlands
2. Centre for the Analysis of Time Series, London School of Economics and Political Science (LSE), London, UK
3. Institute for Environmental Studies (IVM), VU University, Amsterdam, The Netherlands
Abstract:Disasters such as floods, storms, heatwaves and droughts can have enormous implications for health, the environment and economic development. In this article, we address the question of how climate change might have influenced the impact of weather-related disasters. This relation is not straightforward, since disaster burden is not influenced by weather and climate events alone—other drivers are growth in population and wealth, and changes in vulnerability. We normalized disaster impacts, analyzed trends in the data and compared them with trends in extreme weather and climate events and vulnerability, following a 3 by 4 by 3 set-up, with three disaster burden categories, four regions and three extreme weather event categories. The trends in normalized disaster impacts show large differences between regions and weather event categories. Despite these variations, our overall conclusion is that the increasing exposure of people and economic assets is the major cause of increasing trends in disaster impacts. This holds for long-term trends in economic losses as well as the number of people affected. We also found similar, though more qualitative, results for the number of people killed; in all three cases, the role played by climate change cannot be excluded. Furthermore, we found that trends in historic vulnerability tend to be stable over time, despite adaptation measures taken by countries. Based on these findings, we derived disaster impact projections for the coming decades. We argue that projections beyond 2030 are too uncertain, not only due to unknown changes in vulnerability, but also due to increasing non-stationarities in normalization relations.
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