Hurricane Storm Surge Risk Analysis for the Development of Structures of Coastal Resilience

Friday, 19 December 2014
Talea Mayo and Ning Lin, Princeton University, Princeton, NJ, United States
In this work, we use a physically based assessment to estimate the risk of hurricane storm surge at four sites along the U.S. North Atlantic coast. The sites are Narragansett Bay, RI, Jamaica Bay, NY, Atlantic City, NJ, and Norfolk, VA. These sites have all been identified as urban, coastal areas that are particularly vulnerable to storm surge. In consideration of the changing climate, we seek to assess the risk at these sites for both current and projected climate conditions. Using a novel approach to risk analysis, we estimate storm surge recurrence intervals by forcing a hydrodynamic model with thousands of hurricanes. Rather than relying on the limited historical records, we force the hydrodynamic model with the wind and pressure field data of synthetic hurricanes, which are generated from a statistical-deterministic model. This hurricane model uses large-scale atmospheric and oceanic data as input, which can be generated from global climate models (GCMs). To assess the risk of storm surge in the current climate, i.e. the 20th century, we use large-scale data of the observed climate as estimated by the NCEP/NCAR reanalysis. To assess the risk for projected climate scenarios, i.e. the 21st century, we use large-scale data modeled by four GCMs informed by the RCP8.5 emissions scenario from the Intergovernmental Panel on Climate Change fifth assessment report. In addition to the generation of these ``21st century" storms, we account for climate change by incorporating the rising mean sea level. We have also recently investigated strategies to best estimate recurrence intervals for the 21st century from the distinct recurrence intervals that result from each GCM. Our results have been used to inform a multi-institutional, interdisciplinary research effort to develop ``Structures of Coastal Resilience."