Evaluating the relationship between wind and storm surge risk in the Philippines and Hong-Kong, an insurance industry perspective.

Due to intense destructive winds and heavy rainfall associated with storm surges, large waves and flooding, tropical cyclones are one of the most damaging natural catastrophes. They are a major threat to human lives and properties across the globe. When travelling over the ocean and approaching shallow water regions, tropical cyclones generate storm surge and waves that can devastate coastal communities and local economies.

In the recent years, Typhoons Hato (2017) and Mangkhut (2018) produced material surge damages to insurers in the Northwest Pacific basin, and therefore raised the need for accurate natural catastrophe models. Cat models consist of very large catalogues of synthetic but realistic events also called “event sets”. These event sets are consistent with experienced historical data but allow extrapolation beyond what was observed. 

In this study, we focus in winds and surges on the Philippines and Hong Kong regions. Driven by an existing tropical cyclone wind event set, over 10k full-physic simulations of storm surge and waves are computed for each region to estimate the complete distribution of coupled wind and surge losses over an exposure dataset. Due to computationally expensive dynamical simulations of storm surges and waves,  we first rank and select a subset of events (10k) based on an IKE (Integrated Kinetic energy) index. For each of these 10k event, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM; Zhang & Baptista, 2008, Zhang et al., 2016) is forced by atmospheric winds and pressure fields to derive wave and surge footprints.

Second, we use adjusted Hazus (FEMA) damage functions to convert the water heights and windspeeds from the simulated events into damage factors. These factors are then multiplied to the considered exposure to derive losses. Third, we study the relationship between the wind and the surge modeled losses based on two criteria, (i) the event level correlation between IKE and surge losses, to ensure this index stands as a robust risk representation, and (ii) the event level proportion of surge losses out of the wind losses, which provides a set of reusable inter perils correlation factors.