The dry‐wet abrupt alternation (DWAA) event, which is defined as the phenomenon of dry (or wet) spells abruptly following wet (or dry) spells, magnifies the influence of individual wet and dry events. The dynamic evolution of DWAA events has not been studied for different climate zones of China that is particularly susceptible to dry and wet extremes. This study explores the future changes in the abrupt alternations between dry and wet extremes across 10 climate divisions of China, with a thorough assessment of dry and wet conditions using the Standardized Precipitation Evapotranspiration Index (SPEI). We take advantage of an ensemble of regional climate model simulations including the Providing Regional Climate Impacts for Studies (PRECIS) experiment and five CORDEX East Asia experiments to produce high‐resolution climate information for a baseline period of 1975−2004 and a future period of 2069−2098. Our findings disclose that a total of 70% of China's land area suffered from the DWAA events at least once during 1975−2004. The wet‐dry alternation event is projected to become more frequent in summer, and a prominent increase in the number of dry‐wet alternation events is expected to occur in spring over most parts of China. Moreover, an increasing number of DWAA events with intensified magnitude is projected to strike the North China Plain dominated by warm‐temperature and humid zone, which is the most densely populated region of the country and is also the largest agriculture production area. Our findings also reveal a strong positive correlation between DWAA and heavy rainfall. The 95^th percentile rainfall event contributes most to the wet‐dry alternation event for most climate divisions of China.

It has been suggested that global warming impacts on human thermal comfort will cause an increase in the heat stress and a decrease in the cold stress in the future. A recent study has shown elevated increases in human‐perceived equivalent temperature (HPET) by using a single index for summer and winter seasons (Li et al., 2018, https://doi.org/10.1038/s41558‐017‐0036‐2). However, they have not considered multiple indices with combined effects on deriving HPET, which can result in large uncertainties in assessing climate change impacts on HPET and related extremes. Therefore, we develop a new framework with high‐resolution projections and an ensemble of 10 indices to quantify the impacts of climate change on HPET and related perceived extremes as well as to address uncertainties in both empirical indices and emission scenarios over China. Our findings reveal that different combinations of climatic variables can lead to two opposite conclusions for both normal and extreme conditions. For example, by using indices only considering the combined effect of temperature and relative humidity, China is projected to have an elevated increase in the HPET and in the frequency of high‐temperature extremes. By taking into account wind speed, the country expects to have the HPET even lower than the surface air temperature and an increase in the frequency of low‐temperature extremes. In addition, the resulting range of HPET due to uncertainty in indices is greater than the uncertainty range derived from different emission scenarios for the entire country. Therefore, it is necessary to conduct a comprehensive assessment that explicitly addresses uncertainties in the HPET in order to improve the robustness and reliability of assessing climate change impacts on human‐perceived temperature extremes.

Soil erosion poses a significant threat to land conservation, freshwater security, and ocean ecology. Climate change, with rainfall as one of its primary drivers, exacerbates this problem. Therefore, reliably predicting future soil erosion rates and taking into account anthropogenic influences are crucial for policymakers and researchers in the earth-system field. To address this challenge, we have developed a novel framework that combines the Bayesian Model Averaging (BMA) method with the Revised Universal Soil Loss Equation (RUSLE) model to estimate erosion rates on a national scale. We used BMA to merge five Regional Climate Models (RCMs), reducing uncertainty in ensemble simulations and improving the plausibility of projected changes in climatic regimes over China under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). The RUSLE model was applied to forecast the effects of climate change and land-use change on water erosion in China, using high-resolution climate simulation and prediction inputs. Our findings revealed that under the RCP4.5 and RCP8.5 scenarios, average annual soil loss will increase by 21.20% and 33.06%, respectively, compared to the baseline period. Our analysis also demonstrated a clear distinction between the effects of climate change and land-use change on water erosion. Climate change leads to an increase in precipitation, which exacerbates water erosion rates, with contributions ranging from 59.99% to 78.21%. Furthermore, an increase in radiative forcing will further amplify the effects of climate change. The transformation of land from one that has not been disturbed by humans to one that has been exposed to some soil and water conservation measures will have a mitigating effect on water erosion, with a contribution of −6.96% to −4.68%. Therefore, implementing effective soil and water conservation measures can somewhat mitigate the severity of ongoing soil loss. Our findings have significant implications for policymakers seeking to develop national strategies for soil conservation and model developers working to reduce uncertainty in erosion predictions.