Why Do CMIP6 Models Fail to Simulate Snow Depth in Terms of Temporal Change and High Mountain Snow of China Skillfully?

Abstract Global climate models are important tools for investigating historical and future responses of snow under change. However, simulations from Coupled Model Intercomparison Project Phase 6 (CMIP6) have not been well evaluated in terms temporal change mountain snow, with major error sources remaining unclear. This study synthetically uses long‐term station observations, reanalysis, remote sensing data to evaluate depth 31 state‐of‐the‐art CMIP6 both the high Tibetan Plateau other areas China, analyzes error. For first‐time, accumulated errors precipitation temperature prior months found be crucial explaining why failed capture trends hotspots notable time lags peak month. The worst performance was on resulted more serious overestimates underestimates than regions.