期刊
INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE
卷 13, 期 4, 页码 592-601出版社
SPRINGER
DOI: 10.1007/s13753-022-00430-5
关键词
Climate change; Cost estimation; Extreme weather; Loss and damage; Loss normalization; Monte Carlo simulation
This study introduces and applies a hybrid simulation model to improve understanding of the costs of extreme weather events based on empirical data. The model results show promising accuracy in estimating the expected costs for specific event types and locations, which can help make a business case for resilience investment.
History has shown that occurrences of extreme weather are becoming more frequent and with greater impact, regardless of one's geographical location. In a risk analysis setting, what will happen, how likely it is to happen, and what are the consequences, are motivating questions searching for answers. To help address these considerations, this study introduced and applied a hybrid simulation model developed for the purpose of improving understanding of the costs of extreme weather events in the form of loss and damage, based on empirical data in the contiguous United States. Model results are encouraging, showing on average a mean cost estimate within 5% of the historical cost. This creates opportunities to improve the accuracy in estimating the expected costs of such events for a specific event type and geographic location. In turn, by having a more credible price point in determining the cost-effectiveness of various infrastructure adaptation strategies, it can help in making the business case for resilience investment.
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