Extreme Weather Loss and Damage Estimation Using a Hybrid Simulation Technique

Charles Doktycz; Mark Abkowitz; Hiba Baroud

doi:10.1007/s13753-022-00430-5

Volume 13 Issue 4

Aug. 2022

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Charles Doktycz, Mark Abkowitz, Hiba Baroud. Extreme Weather Loss and Damage Estimation Using a Hybrid Simulation Technique[J]. International Journal of Disaster Risk Science, 2022, 13(4): 592-601. doi: 10.1007/s13753-022-00430-5

Citation:

Charles Doktycz, Mark Abkowitz, Hiba Baroud. Extreme Weather Loss and Damage Estimation Using a Hybrid Simulation Technique[J]. International Journal of Disaster Risk Science, 2022, 13(4): 592-601. doi: 10.1007/s13753-022-00430-5

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Extreme Weather Loss and Damage Estimation Using a Hybrid Simulation Technique

doi: 10.1007/s13753-022-00430-5

School of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, 37235, USA

Available Online: 2022-09-09

Abstract

Abstract

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.
- Climate change,
- Cost estimation,
- Extreme weather,
- Loss and damage,
- Loss normalization,
- Monte Carlo simulation

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References(21)

References

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