Revealing historical observations and future projections of precipitation over Northwest China based on dynamic downscaled CMIP6 simulations - Yang, Xianyu; Li, Douwang; Yang, Zhou; Wu, Kai; Ji, Luyong; Zhou, Ziqiang; Lu, Yaqiong (Frontiers in Earth Science, 2023)
The warming climate driven by global change has great potential in altering regional and global hydrologic cycles, thus leading to considerable changes in spatial variability and temporal pattern of precipitation. Northwest China (NW) has witnessed a significant wetting trend over the past decades, while the persistence of this wetting trend and potential changes in precipitation under future climate impacts remains elusive. In this study, long-term meteorological observations were used to probe historical variations of precipitation from 1950 to 2020, and the WRF model was employed as a regional climate model to examine future precipitation patterns over NW. Two 9-year downscaled WRF simulations were conducted comprising of historical (WRF-HIST; 2012-2020) and future climate change scenarios (WRF-SSP585; 2047-2055) using bias-corrected global climate model outputs from Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with ground observations, the WRF model exhibited strong capability in capturing the spatial patterns and temporal variations of precipitation across the NW. Intense precipitation was mainly found in stations located at the northern NW and southeastern NW. Summertime precipitation substantially contributed to annual precipitation over the study region. Future precipitation projections suggest significant decreases of precipitation across the southern and eastern NW, with a stronger reduction magnitude in the summertime. Further, extreme precipitation events were projected to decrease in spring and summer, suggesting that the NW may become drier and the wetting trend may shift to another pattern in the 2050s under the SSP585 climate scenario. Overall, this study reveals historical and future potential changes in precipitation over NW through a high-resolution, dynamically downscaled dataset from WRF modeling, which in turn will help inform regional mitigation and adaption on potential impacts of future climate change on NW.