2.2. Synthetic TC Dataset
To overcome the limitation of historical data, we estimate TC-induced
coastal flood and inundation hazard based on large numbers of synthetic
storms. We apply a synthetic TC dataset generated by the
deterministic-statistical TC model of Emanuel et al. (2008). This model
uses thermodynamic and kinematic statistics of the atmosphere and ocean
derived from reanalysis data or climate-model estimation to produce
synthetic TCs; it has been widely used to study hurricane wind, storm
surge, and rainfall hazards (e.g., Emanuel 2017, Marsooli et al. 2019).
Specifically, Xu et al. (2020) applied the synthetic TC model to study
typhoon wind hazard for the Shanghai area. We apply the synthetic TC
dataset generated in Xu et al. (2020) for the climate over the period of
1979 ~ 2015 based on the National Centers for
Environmental Prediction (NCEP) reanalysis (Kalnay et al. 1996). The
dataset includes 5018 synthetic storms. Each synthetic storm passes
within a 350-km-radius circle centered at a point near Shanghai
(latitude 29.86° and longitude 121.56°), and all storms pass within this
circle with the maximum wind intensity (1-min wind speed at 10 m above
sea level) greater than 21 m/s (40 knots). Each storm is characterized
by 2-hourly time series of the storm parameters (i.e., time, center
position, maximum wind speed, pressure deficit, and radius of maximum
wind) required for storm tide modeling. The annual storm frequency
associated with the storm set is about 2 storms per year. Xu et al.
(2020) found that the estimated wind hazard based on the NCEP synthetic
dataset compared well with historical wind observations in the Shanghai
region.