Future projections of temperature extremes over East Asia based on a deep learning downscaled CMIP6 high-resolution (0.1°) dataset

Abstract

East Asia, with its diverse landscapes and dense population, is particularly vulnerable to the impacts of climate change. This study utilizes the Climate Change for East Asia with Bias corrected UNet Dataset (CLIMEA-BCUD), a high-resolution and bias-corrected dataset of future climate projections, to assess the potential changes in temperature extremes across East Asia under three Shared Socioeconomic Pathways (SSPs) scenarios (SSP1–2.6, SSP2–4.5, and SSP5–8.5). The accuracy of CLIMEA-BCUD is verified through comparisons with observational data during the baseline period (1981–2010). CLIMEA-BCUD demonstrates remarkable accuracy in simulating the intensity, frequency and duration of extreme temperature events, although overestimation exists for the duration of warm spell and cold spell in some areas of India and Indo-China. Its high spatial resolution allows it to provide more spatial details of the distribution of extreme temperature events. In general, CLIMEA-BCUD outperforms the global climate models with smaller biases and lower root mean square errors. In the future, CLIMEA-BCUD projects a greater increase in TNn than TXx across East Asia. TX90p and TN90p are projected to increase, especially over India and Indo-China. Warm spell duration shows a robust increase, particularly in the Tibetan Plateau and Indo-China, while the cold spell duration will shorten. East Asia will see more frequent record-breaking extreme high-temperature events. Extreme temperature indices related to frequency and duration are more likely to break historical records than intensity indices. The Tibetan Plateau and Xinjiang emerge as hotspots for record-breaking frequency and duration of extreme temperature events.