The future impacts of climate change on landfalling tropical cyclones are unclear. Regardless of this uncertainty, flooding by tropical cyclones will increase as a result of accelerated sea-level rise. Under similar rates of rapid sea-level rise during the early Holocene epoch most low-lying sedimentary coastlines were generally much less resilient to storm impacts. Society must learn to live with a rapidly evolving shoreline that is increasingly prone to flooding from tropical cyclones. These impacts can be mitigated partly with adaptive strategies, which include careful stewardship of sediments and reductions in human-induced land subsidence.

Over the last quarter-century, hurricane surge has been assumed to be primarily a function of maximum storm wind speed, as might be estimated from the Saffir–Simpson hurricane scale. However, Hurricane Katrina demonstrated that wind speed alone cannot reliably describe surge. Herein it is shown that storm size plays an important role in surge generation, particularly for very intense storms making landfall in mildly sloping regions. Prior to Hurricane Katrina, analysis of the historical hurricane record evidenced no clear correlation between surge and storm size, and consequently little attention was given to the role of size in surge generation. In contrast, it is found herein that, for a given intensity, surge varies by as much as 30% over a reasonable range of storm sizes. These findings demonstrate that storm size must be considered when estimating surge, particularly when predicting socioeconomic and flood risk.

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Tens of millions of people around the world are already exposed to coastal flooding from tropical cyclones. Global warming has the potential to increase hurricane flooding, both by hurricane intensification and by sea level rise. In this paper, the impact of hurricane intensification and sea level rise are evaluated using hydrodynamic surge models and by considering the future climate projections of the Intergovernmental Panel on Climate Change. For the Corpus Christi, Texas, United States study region, mean projections indicate hurricane flood elevation (meteorologically generated storm surge plus sea level rise) will, on average, rise by 0.3 m by the 2030s and by 0.8 m by the 2080s. For catastrophic-type hurricane surge events, flood elevations are projected to rise by as much as 0.5 m and 1.8 m by the 2030s and 2080s, respectively.

This paper reviews historical methods for estimating surge hazards and concludes that the class of solutions produced with Joint Probability Method (JPM) solutions provides a much more stable estimate of hazard levels than alternative methods. We proceed to describe changes in our understanding of the winds in hurricanes approaching a coast and the physics of surge generation that have required recent modifications to procedures utilized in earlier JPM studies. Of critical importance to the accuracy of hazard estimates is the ability to maintain a high level of fidelity in the numerical simulations while allowing for a sufficient number of simulations to populate the joint probability matrices for the surges. To accomplish this, it is important to maximize the information content in the sample storm set to be simulated. This paper introduces the fundamentals of a method based on the functional specification of the surge response for this purpose, along with an example of its application in the New Orleans area. A companion paper in this special issue (Irish et al. 2009) provides details of the portion of this new method related to interpolating/extrapolating along spatial dimensions.

In response to the 2004 and 2005 hurricane seasons, surge risk assessment approaches have been re-evaluated to develop more rapid, reliable methods for predicting the risk associated with extreme hurricanes. Here, the development of dimensionless surge response functions relating surge to hurricane meteorological parameters is presented. Such response functions present an opportunity to maximize surge data usage and to improve statistical estimates of surge probability by providing a means for defining continuous probability density functions. A numerical modeling investigation was carried out for the Texas, USA coastline to develop physical scaling laws relating storm surge response with hurricane parameters including storm size, intensity, and track. It will be shown that these scaling laws successfully estimate the surge response at any arbitrary location for any arbitrary storm track within the study region. Such a prediction methodology has the potential to decrease numerical computation requirements by 75% for hurricane risk assessment studies.