Projecting Economic Loss with Climate Change

Climate change is increasing the magnitude and frequency of extreme weather events, leading to an increase in the economic losses from these natural disasters. Financial institutions, corporations, and governments are required to report on their exposures to climate change, in particular those related to meteorological hazards. Typically, approaches that project losses due to climate change employ top-down approaches using impact models and damage curves. Despite their high levels of complexity, the confidence in these approaches is low. We propose a novel approach to calculate future economic losses, using a physically based statistical approach that is directly linked to future climate projections. The approach is general and can be applied to any economic risk from extreme weather. We model aggregate loss distributions using a nonstationary multivariate Poisson distribution to model the frequency of events, and a conditional generalized Pareto distribution to model the magnitude of the events. These distributions employ demographic and climate covariates which are easily projected from climate model simulations. We illustrate our method by estimating the flood risk to property for Western North America. By the end of the century, the estimated economic losses under a high emissions scenario (SSP585) are twice the magnitude of the estimates under a rapid emissions reduction and negative emissions pathway (SSP126), highlighting the importance of meeting the Paris climate agreement targets.