Projections of surface air temperature and precipitation in the 21st century in the Qilian Mountains, Northwest China, using REMO in the CORDEX

Abstract

Qilian Mountains (QM) is an important ecological security barrier in China and has been significantly affected by climate change, it is therefore of great importance and necessity to project its future climate change using high-resolution climate models because of mountainous areas in the QM and relatively few targeted simulation analyses. In this study, we used the simulations of the regional climate model REMO with 25 km spatial resolution, driven by three different global climate models (MPI-ESM-MR, NorESM1-M, and HadGEM2-ES), to evaluate how annual and seasonal mean surface air temperature and precipitation in the QM are likely to change for three future periods (2011–2040, 2041–2070, and 2071–2100) under two representative concentration pathways (RCP2.6 and RCP8.5). The REMO model, shows noticeable cold and wet biases compared to observations for the reference period (1971–2000) and air temperature simulation outperforms precipitation simulation. The REMO simulations exhibit a warm and wet centre around lake, indicating that the simulation are likely influenced by lake. Projections under RCP2.6 show regional warming reaching 1.74 °C during 2011–2100, characterized by an initial increase and a decrease afterwards. Under RCP8.5, air temperatures increase monotonously from 2011 to 2100, with a warming magnitude of 5.36 °C for 2071–2100 relative to 1971–2000. The overall change in regional-average annual precipitation is not evident during 2011–2100, with some increases or decreases in certain time periods. In the 2071–2100 both the strongest warming and precipitation increase are projected to occur in winter under both scenarios, while precipitation in summer and autumn is projected to decrease in the east of the QM for the three future periods. The results suggest that the QM is likely to experience drought conditions in warm seasons in the future, which could impact agricultural and livestock production.