More Rapid Reduction of Spring Snow Cover on the Western Tibetan Plateau by Emergent Constraint

Abstract Snow cover is a critical component of climate, hydrological, and ecological systems, particularly in high‐altitude and high‐latitude regions. Global warming has driven substantial snow cover retreat, yet projections from climate models vary widely, hindering reliable climate change adaptation and policy planning. For the Tibetan Plateau (TP), observationally constrained projections offer an opportunity to improve the credibility of snow cover projections, yet such applications are still limited. Based on climate models, we find that the historical inter‐model snow cover reductions are strongly correlated with the projected remaining snow cover by the end of the 21st century. By this emergent relationship and satellite‐derived products, we calibrate the best estimate of the remaining frequency of spring snow cover (relative to 1981–2020) to 37%, which is lower than the multi‐models' prediction (55%) and substantially reduces inter‐model spread (17% after constraint compared to 23% in standard deviation) in a high emission scenario. Cross‐validation tests reinforce the robustness of the constrained projection. The underestimation of snow cover loss is likely attributed to an underestimation of observed warming magnitude. Sensitivity analyses indicate that the choice of period for historical snow cover extent reduction trends and climate model ensemble are the main sources of uncertainty, whereas differences between the two satellite‐derived data sets have only a limited impact on the constraint.