Jinxin Zhu

Abstract 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 95th percentile rainfall event contributes most to the wet‐dry alternation event for most climate divisions of China.

Abstract The warming climate can considerably alter the Earth's water cycle and change precipitation over land. Climate models are the primary tools for projecting precipitation changes and evaluating climate impacts in various fields. This study compares precipitation from 45 models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and 49 models in Phase 6 (CMIP6) to observations. The results reveal that the CMIP6 models outperform the CMIP5 models in simulating precipitation patterns over the global land for the historical period. The cumulative distribution function matching method is used to correct the bias in the outputs of the selected CMIP5 and CMIP6 models, and the multi‐model ensemble (MME) of the corrected models is then utilized in projecting the precipitation changes under the future scenarios over the global land. The observation‐constrained projections show that there is a significant increasing trend in the annual global land precipitation during 2021–2100 under all four scenarios, and the rates are 3.0, 4.23, 6.77 and 8.96 mm/decade under the RCP4.5, SSP2‐4.5, RCP8.5 and SSP5‐8.5 scenarios, respectively. Moreover, the average annual global land precipitation is projected to increase by 4.9% (RCP4.5), 8.1% (RCP8.5), 4.6% (SSP2‐4.5) and 10.1% (SSP5‐8.5) by 2081–2100 relative to 1986–2005. Increases in global average precipitation may result in more flood, causing higher flooding risk in the future.

Abstract 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.

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