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Cited by 251

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

THE ECONOMICS OF HURRICANES AND IMPLICATIONS OF GLOBAL WARMING

Open access
NORDHAUS, WILLIAM D.·2010·Climate Change Economics

Abstract

This study examines the economic impacts of US hurricanes. The major conclusions are the following: First, there are substantial vulnerabilities to intense hurricanes in the Atlantic coastal United States. Damages appear to rise with the ninth power of maximum wind speed. Second, greenhouse warming is likely to lead to stronger hurricanes, but the evidence on hurricane frequency is unclear. We estimate that the average annual US hurricane damages will increase by $10 billion at 2005 incomes (0.08 percent of GDP) due to global warming. However, this number may be underestimated by current storm models. Third, 2005 appears to have been a quadruple hurricane outlier, involving a record number of North Atlantic tropical cyclones, a large fraction of intense storms, a large fraction of the intense storms making landfall in the United States, and an intense storm hitting the most vulnerable high-value region in the country.

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Crossref · 10.1142/s2010007810000054

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Metadata

Authors
NORDHAUS, W. D.
Venue
Climate Change Economics
Published
2010-05
Volume
01
Issue
01
Pages
1-20
ISSN
  • 2010-0078 (ISSN-L)
  • 2010-0086
OpenAlex
W2075300652
Cited by
251
References
1
FWCI
8.91
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: THE ECONOMICS OF HURRICANES AND IMPLICATIONS OF GLOBAL WARMING. https://app.cochat.ai/papers/10.1142/s2010007810000054
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NORDHAUS, W. D. (2010). THE ECONOMICS OF HURRICANES AND IMPLICATIONS OF GLOBAL WARMING. Climate Change Economics. https://doi.org/10.1142/s2010007810000054

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.