Extreme climate events and economic impacts in China: A CGE analysis with a new damage function in IAM

Abstract

• A new integrated assessment model (IAM) named EMRICES-2020 was constructed to realize the close connection of the complicated climate change information in ESMs and the social economic growth model. • The coupling technology of the damage function in the climate feedback module for China was then reconstructed and improved by adding the economic impact mechanism of precipitation and extreme climate events. • The improved mode damage function was embedded into the production function of a multi-sector dynamic CGE economic model. • The new damage function has better simulated the sudden economic impact of extreme climate events and the volatility of climatic losses, compared with the Nordhaus damage function. • The long-term forecasting of climatic economic losses under the RCP carbon emission scenarios were simulated and calculated, especially the climatic economic losses of the extreme climate events on the economic activities of industrial sectors. Integrated assessment models (IAMs) have been widely used to assess the effect of climatic policy. They are used to combine economic activity with simple climatic systems. Coupling earth system models (ESMs) to a socioeconomic framework for scientific research on climate change impacts is a challenging task. The coupling mechanism for complicated climate information in ESMs and economic activities, particularly the effects of extreme climate events on economic activities of industrial sectors, needs to be further explored. Therefore, we constructed a new IAM named EMRICES-2021 and improved the key coupling technology of damage function by adding an economic impact mechanism of precipitation, and extreme climate events. Considering the dynamic persistence features of climatic impacts on industrial sectors, we embedded the new damage function into the Cobb-Douglas production function of a computable general equilibrium (CGE) model and simulated future climatic losses on industrial economic system. Results show that the new damage function could better simulate the sudden economic impacts of extreme climate events and volatilities of climatic losses than Nordhaus mode. The cumulative indirect losses caused by extreme weather far exceeded direct losses in RCP scenarios. Climatic economic losses on real estate, finance, wholesale and retail trade increased fastest. Figure 10. Climatic losses to the economic system in various RCP scenarios