Combining Surge and Wind Risk from Hurricanes Using a Copula Model: An Example from Galveston, Texas Jill C. Trepanier and Hal F. Needham Louisiana State University James B. Elsner and Thomas H. Jagger Florida State University Consideration of climate-related impacts on coasts is important to ensure readiness for disaster response. Local risk of storm surge and strong winds from hurricanes affecting Galveston, Texas, is quantified using a bivariate copula model fit to observed data. The model uses a two-dimensional Archimedean copula. Parametric uncertainty (5th and 95th percentiles) is quantified using a Monte Carlo procedure. The annual probability of a hurricane producing winds of at least 50 ms −1 and a surge of at least 4 m is 1.7 percent with a 95 percent confidence interval of (1.33, 1.78) percent. The methodology can be extended to include inland flooding and can be applied elsewhere with available information. Key Words: copula, extreme winds, hurricanes, risk, storm surge. ,  ,  , ,  () 50ms-1  ,  (1.33, 1.78)  ,  : , , , ,  Es importante tomar en consideraci ´ on los impactos relacionados con el clima en las costas para asegurar una pronta respuesta en caso de desastre. El riesgo local por marejadas de tormenta y por vientos fuertes asociados con los huracanes que afectan a Galveston, Texas, se cuantifica utilizando un modelo c ´ opula bivariado ajustado a los datos observados. El modelo utiliza una c´ opula arquimediana bidimensional. La incertidumbre param ´ etrica (percentiles 5 ◦ y 95 ◦ ) se cuantifica por medio de un procedimiento de Monte Carlo. La probabilidad anual de que ocurra un hurac ´ an que produzca vientos de por lo menos 50 ms −1 , y una marejada de por lo menos 4 m, es de 1.7 por ciento al 95 por ciento de confianza en intervalo (1.33, 1.78 por ciento). La metodolog´ıa puede extenderse para incluir la inundaci ´ on tierra adentro y puede aplicarse en otras partes con la informaci ´ on que se tenga a mano. Palabras clave: c ´ opula, vientos extremos, huracanes, riesgo, marejada de tormenta. H urricanes are awesomely powerful and po- tentially devastating weather phenomena that threaten the United States annually. According to the U.S. Geological Survey (USGS 2005), hurricanes bring high winds, storm surge, heavy rain, flooding, and tornadoes. More than half of the U.S. population lives within fifty miles of a coast, and as coastal popu- lations and infrastructure continue to rise, so does the property damage associated with these events (USGS 2005). Economic losses from individual events can reach billions of dollars, and, collectively, these storms have cost well over $450 billion in the United States since the early 20th century (Pielke et al. 2008; Malm- stadt, Scheitlin, and Elsner 2009). The active season of 2005, with Katrina, Rita, and Wilma, demonstrated that hurricanes can inflict vast amounts of damage, and the need for hurricane research and preparedness has escalated (USGS 2005). The principal hurricane hazards causing these extreme losses are the violent winds and widespread inundation from storm surges and heavy rainfall (Czajkowski, Simmons, and Sutter 2011). This study focuses on the combined risk of high winds and storm surge at a location on the U.S. Gulf Coast. Storm surge is a dome of elevated water that is pushed onshore as a hurricane approaches the coast- line. As coastal flooding inundations often persist for many hours, the rise and fall of tidal cycles combines with storm-related flooding to produce elevated water levels, known as storm tides. Removing the tidal oscil- lations from these water levels leaves us with the storm surge, or the component of the flood that is produced solely from the storm. Here risk refers to the statistical likelihood of these hazards affecting a given location or region. Past re- search has focused on estimating the risk of a single hazard. Chu and Wang (1998) employed the use of the Gumbel, the Weibull, and the lognormal distri- bution to model tropical cyclone return periods in the vicinity of Hawai’i based on wind speeds alone. Elsner, Jagger, and Liu (2008) estimated hurricane return lev- els for Lake Shelby, Alabama, as a way to compare geological proxies of past hurricanes with historical records. Malmstadt, Elsner, and Jagger (2010) auto- mated the approach offered in Elsner, Jagger, and Liu The Professional Geographer, 67(1) 2015, pages 52–61 C  Copyright 2015 by Association of American Geographers. Initial submission, March 2013; revised submission, May 2013; final acceptance, July 2013. Published by Taylor & Francis Group, LLC.