Based on 30 CMIP6 global climate models and observational data from 2374 meteorological stations in China during 1961–2020, the primary objective of this study is to investigate the sources of uncertainty in model projections from both thermodynamic and dynamic perspectives. The projection of mid‐summer precipitation trend is slight increasing in the near‐term (2021–2040), maximum in the mid‐term (2041–2060) and slowing down i...

The influencing factors of summer precipitation in China are complex, making prediction challenging, with the need to further improve its forecast accuracy. In the rapid development of machine learning algorithms, a key research topic is how to extract the physical factors that influence summer precipitation in China, and how to effectively integrate these factors with numerical models using machine learning methods to constru...

Compound heat‐humidity extremes (CHHEs) have gained significant attention as crucial indicators of heat stress. This research investigates the summer wet bulb globe temperature (WBGT) to elucidate the spatial variation of CHHEs across China from 1961 to 2022. The results reveal a clear increase in CHHEs, with the highest WBGT observed in southeastern China, while significant increases are noted in the northwestern and northeas...

Regional cold winters have occurred frequently in Eurasia since the beginning of the 21st century, increasing the interannual variability in winter temperatures and increasing the difficulty of prediction. In this study, we evaluate the performance of Climate Forecast version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP) in predicting winter temperature anomalies over the Northern Hemisphere and find th...