Hurricane storm surge presents a major hazard for the United States. We apply a model-based risk assessment methodology to investigate hurricane storm surge risk for New York City (NYC). We couple a statistical/deterministic hurricane model with the hydrodynamic model SLOSH (sea, lake, and overland surges from hurricanes) to generate a large number of synthetic surge events; the SLOSH model simulations are compared to advanced circulation model simulations. Statistical analysis is carried out on the empirical data. It is observed that the probability distribution of hurricane surge heights at the Battery, NYC, exhibited a heavy tail, which essentially determines the risk of New York City being struck by a catastrophic coastal flood event. The peaks-over-threshold method with the generalized Pareto distribution is applied to estimate the upper tail of the surge heights. The resulting return periods of surge heights are consistent with those of other studies for the New York area. This storm surge risk assessment methodology may be applied to other coastal areas and can be extended to consider the effect of future climate change.