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The utilization of regional climate methods (RCMs) to predict future climate is an important study under the changing environment. The primary objective of the paper is to correct the temperature and precipitation simulations for the period of 1980–2005 and 2026–2098 in the Wei River Basin (WRB), to evaluate the performance of RCMs for the period of 1980–2005, and further, to analyze the future changes of projected temperature and precipitation during 2026–2098. In this paper, the linear scaling method was used to correct the temperature simulations. Quantile mapping, local intensity scaling method, and hybrid method were used to correct the precipitation simulations. The future changes of projected temperature and precipitation for the near term (2026–2050), mid-term (2051–2075), and far term (2076–2098), relative to the period of 1980–2005, were investigated under RCP 2.6 and RCP 8.5. Results indicate that (1) the temperature biases were either warm or cold in the spatial scale, and the precipitation wet biases were detected. After correction, HadGEM2-ES driven by RegCM4-4 had the best temperature reproducibility, and NCC-NorESM1-M driven by RegCM4-4 had the best precipitation reproducibility. (2) Under RCP 2.6, the projected annual, winter, and spring temperature showed decreasing trends. The temperature was higher than that for the period of 1980–2005 except for the spring temperature decreases in the Beiluo River Basin. Under RCP 8.5, the temperature showed significantly increasing trends. The temperature for the near term was similar to that of the period of 1980–2005, while the temperature increased significantly for the mid-term and far term. (3) Under RCP 2.6, the precipitation had decreasing trends. Under RCP 8.5, precipitation trends were also spatially distributed. The relative deviation of winter precipitation was the largest. Relative to the period of 1980–2005, the light- and moderate-rain days showed little change for the period of 2026–2098, while the extreme-rain days showed significantly increasing trends. [ABSTRACT FROM AUTHOR]

In summer 2020, precipitation in many parts of China reached its maximum in the past 60 years, and southern China suffered from severe flooding, which was mainly due to the strong westward subtropical high, the enhanced east Asian summer monsoon, the development of meridional circulation, and the active cold vortex in the middle and high latitudes. We tried to apply a statistical bias correction method to improve the prediction of summer precipitation at 160 stations in China in 2020. In summer 2020, the precipitation anomaly percentages were above 40% in the Yellow River Basin and the Yangtze River Basin. Using the bias correction method, the main rain belt of the corrected summer precipitation was located in the Yangtze River's middle reaches and the Yellow River Basin, which is in line with the observations, but it does not catch the trend of more summer precipitation in the Huaihe River Basin. In addition, the corrected predicted results can basically catch the trend of dryness in South and Southwest China. Relative to the original model output, the abnormal correlation coefficient (ACC) between the corrected predictions, and the observations increased from − 0.02 to 0.30, and the prediction score (PS) increased from 67.8 to 77.4 for summer rainfall in 2020. Moreover, the bias correction method showed stable and considerable improvement for the prediction of summer precipitation in China from 2014 to 2019. Overall, this study demonstrates that the bias correction method can effectively improve the accuracy of the summer precipitation predicted results in China. [ABSTRACT FROM AUTHOR]