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