Evaluation of precipitation and its time series components in CMIP6 over the Yellow River Basin

Precipitation is a main part of the regional hydrological cycle, and global warming affects the hydrological cycle because regional precipitation is impacted by mechanistic changes in the hydrological cycle under global warming. This study presents an exploration of the composition variation characteristics of precipitation time series under global climate change. Twelve CMIP6 models were used to forecast precipitation changes in the Yellow River Basin (YRB). Climatic Research Unit (CRU) data were applied in the analysis of historical precipitation. Trend analysis, precipitation bias correction, and Fourier functions were used to analyze the future precipitation change characteristics. Our results showed that the IPSL-CM6A-LR and EC-Earth3-CC models had excellent performances in simulating precipitation in the YRB. Most CMIP6 models showed that precipitation under the SSP5-8.5 scenario had a higher increasing trend and was higher than that under the SSP2-4.5 scenario. The multimodel ensemble means (MEM) of CMIP6 precipitation showed that the future trend and stochastic component of precipitation had a higher degree of contribution than the historical trend and stochastic component of precipitation. However, the future periodic component of precipitation had a lower degree of contribution than the historical component. Most models showed that the degree of contribution of the periodic component of precipitation in Period IV (2015-2057) was higher than that in Period V (2058-2100). Most models showed similar degrees of contribution in Period I (1901-1938), Period II (1939-1976), and Period III (1977-2014). However, the degree of contribution of the stochastic component in 2058-2100 was lower than that in 2015-2057. This study improves the understanding of future precipitation change characteristics and provides a reference for disaster prevention and mitigation in the YRB.