Forecasting the Extreme Heat for Chongqing in China

Under global warming, Chongqing, China has seen rising frequencies of extreme heat, severely impacting residents’ lives, production, and the urban ecosystem. Accurately predicting future extreme heat year (hereinafter referred to as extreme heat) is crucial for ecological protection, energy management, and infrastructure planning. Using historical temperature data, this study defines extreme heat via the quantile method, ensuring regional representativeness. To address the limitations of traditional forecasting methods in predicting extreme heat characterized by “small sample sizes and complex influencing factors,” we have proposed a new grey disaster prediction model. The new model introduces a three-element adjacent mean generation operator and uses the particle swarm optimization (PSO) algorithm for global optimization of its key parameters. Applying this model to Chongqing, China’s 1951–2024 extreme heat, we predict the next three occurrences will be in 2026, 2029, and 2031. This model offers a new approach to extreme heat prediction and supports urban heatwave emergency response optimization, aiding high-temperature disaster prevention and sustainable ecological development.