Quantifying Aggregated Economic Damages from “Fat-Tail” Extremes High-Temperature Events in Climate Change

With global warming and the increasing frequency of extreme high-temperature events exhibiting “fat-tail” characteristics, traditional climate-socio-economic models such as Integrated Assessment Models (IAMs) cannot well reflect the related tail trend and economic damages caused by high-temperature risks. We present a dynamic stochastic equation model (referred to as CEM) that incorporates risk factors for a more accurate assessment. Our study reveals: (1) By 2100, the probability of extreme temperature events is expected to increase by about 3.45 times, leading to severe economic damages and confirming a “fat-tail” trend. (2) Extreme high temperatures may cause economic damages that are challenging to quantify, posing difficulties for conventional warming pathways to estimate these impacts accurately. (3) The average increase of temperature tail probability due to an additional carbon emission of 1 ppm is approximately 0.15 × 10−4. The key innovation of this paper lies in its quantitative analysis of the economic damage caused by extreme high-temperatures events and its exploration of the “fat-tail” features of climate change. Our findings offer methodological and empirical insights to support the development of more robust climate policies to address these extreme risks.