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. We estimate storm surge return levels statistically by forcing a hydrodynamic model with the wind and pressure field data of thousands of hurricanes. Rather than relying on the limited historical records, we force the model with 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). Thus, we are able to assess the current risk of storm surge using large-scale data of the observed climate, which has been estimated by the NCEP/NCAR reanalysis. Additionally, we are able to assess the risk for projected climate scenarios using large-scale climate data modeled by four GCMs informed by the RCP8.5 emissions scenario from the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report. The results of this work are being used to inform a multi institutional, interdisciplinary research initiative to propose resilient designs that will mitigate hurricane storm surge.