As the Wind Blows? Understanding Hurricane Damages at the Local Level through a Case Study Analysis

An understanding of the potential drivers of local-scale hurricane losses is developed through a case study analysis. Two recent category-3 U.S. landfalling hurricanes (Ivan in 2004 and Dennis in 2005) are analyzed that, although similar in terms of maximum wind speed at their proximate coastal landfall locations, caused vastly different loss amounts. In contrast to existing studies that assess loss mostly at the relatively aggregate level, detailed local factors related to hazard, exposure, and vulnerability are identified. State-level raw wind insured loss data split by personal, commercial, and auto business lines are downscaled to the census tract level using the wind field. At this scale, losses are found to extend far inland and across business lines. Storm size is found to play an important role in explaining the different loss amounts by controlling not only the size of the impacted area but also the duration of damaging winds and the likelihood of large changes in wind direction. An empirical analysis of census tract losses provides further evidence for the importance of wind duration and wind directional change in addition to wind speed. The importance of exposure values however is more sensitive to assumptions in how loss data are downscaled. Appropriate consideration of these local drivers of hurricane loss may improve historical loss assessments and may also act upscale to impact future projections of hurricane losses under climate and socioeconomic change.

[1]  Susan L. Cutter,et al.  When do losses count? Six fallacies of natural hazards loss data. , 2009 .

[2]  Kerry A. Emanuel,et al.  The impact of climate change on global tropical cyclone damage , 2012 .

[3]  R. Katz,et al.  US billion-dollar weather and climate disasters: data sources, trends, accuracy and biases , 2013, Natural Hazards.

[4]  Mark A. Saunders,et al.  Normalized Hurricane Damage in the United States: 1900–2005 , 2008 .

[5]  L. Bouwer.  Have disaster losses increased due to anthropogenic climate change , 2011 .

[6]  David V. Rosowsky,et al.  Long-term hurricane risk assessment and expected damage to residential structures , 2001, Reliab. Eng. Syst. Saf..

[7]  Nicholas R. Cavanaugh,et al.  U.S. Hurricanes and Economic Damage: Extreme Value Perspective , 2013 .

[8]  William D. Nordhaus,et al.  The Economics of Hurricanes in the United States , 2006 .

[9]  G. Holland,et al.  Model Investigations of the Effects of Climate Variability and Change on Future Gulf of Mexico Tropical Cyclone Activity , 2010 .

[10]  J. Elsner,et al.  Climate and solar signals in property damage losses from hurricanes affecting the United States , 2011 .

[11]  Daniel Sutter,et al.  Hurricane Fatalities and Hurricane Damages: Are Safer Hurricanes More Damaging? , 2005 .

[12]  R. Pielke,et al.  Normalized Hurricane Damages in the United States: 1925-95 , 1998 .

[13]  T. Karl,et al.  Economic Growth in the Face of Weather and Climate Extremes: A Call for Better Data , 2013 .

[14]  William D. Nordhaus,et al.  THE ECONOMICS OF HURRICANES AND IMPLICATIONS OF GLOBAL WARMING , 2010 .

[15]  Eric Strobl.  The Economic Growth Impact of Hurricanes: Evidence from US Coastal Counties , 2008 .

[16]  The Impact of Climate Change on Global Tropical Storm Damages , 2011 .

[17]  Wolfgang Kron,et al.  How to deal properly with a natural catastrophe database – analysis of flood losses , 2012 .

[18]  A. Murphy,et al.  The Impact of Hurricanes on Housing Prices: Evidence from US Coastal Cities , 2009 .

[19]  Nicholas R. Cavanaugh,et al.  US Hurricanes and economic damage : an extreme value perspective , 2011 .

[20]  Douglas J. Collins,et al.  A Macro Validation Dataset for U.S. Hurricane Models , 1999 .

[21]  Paul Fronstin,et al.  The Determinants of Residential Property Damage Caused by Hurricane Andrew , 1994 .

[22]  Debarati Guha-Sapir,et al.  Quality and accuracy of disaster data: A comparative analyse of 3 global data sets , 2002 .

[23]  James B. Elsner,et al.  Maximum wind speeds and US hurricane losses , 2012 .

[24]  U. Ulbrich,et al.  A model for the estimation of storm losses and the identification of severe winter storms in Germany , 2003 .

[25]  J. Elsner,et al.  Florida Hurricanes and Damage Costs , 2009 .

[26]  Debarati Guha-Sapir,et al.  THE QUALITY AND ACCURACY OF DISASTER DATA A COMPARATIVE ANALYSES OF THREE GLOBAL DATA SETS , 2002 .

[27]  F. Barthel,et al.  Normalizing Economic Loss from Natural Disasters: A Global Analysis , 2010 .

[28]  Eric Strobl,et al.  The Economic Growth Impact of Hurricanes: Evidence from U.S. Coastal Counties , 2011, Review of Economics and Statistics.

[29]  Edward N. Rappaport,et al.  THE DEADLIEST, COSTLIEST, AND MOST INTENSE UNITED STATES TROPICAL CYCLONES FROM 1851 TO 2004 (AND OTHER FREQUENTLY REQUESTED HURRICANE FACTS) , 2005 .

[30]  Forrest J. Masters,et al.  Hurricane hazard modeling: The past, present, and future , 2009 .

[31]  L. Kantha.  Correction to ``Time to Replace the Saffir-Simpson Hurricane Scale?'' , 2006 .

[32]  Mark D. Powell,et al.  The HRD real-time hurricane wind analysis system , 1998 .

[33]  C. Kemfert,et al.  The impact of socio-economics and climate change on tropical cyclone losses in the USA , 2010 .

[34]  C. Kemfert,et al.  Simulation of Economic Losses from Tropical Cyclones in the Years 2015 and 2050: The Effects of Anthropogenic Climate Change and Growing Wealth , 2009 .