Snow Mass Components Analysis: Greater Contribution to Atmospheric Water Vapor than to Water Resources on the Tibetan and Pamir Plateaus

Abstract. Snow in the high-altitude and high-latitude regions is essential for water resources and climate regulation. However, studies on snow mass balance components in alpine areas like the Tibetan and Pamir Plateaus (TPP) are limited. To fill the gap, a novel snow simulation framework was developed, combining in-situ snow depth, satellite snow cover, and point- and grid-scale modelling, supported by sensitivity analysis, automatic calibration, and deep learning. Key snow components—snowfall, snow water equivalent (SWE), refrozen snow, sublimation, evaporation, and snowmelt—were simulated across the TPP from 1962 to 2019 with reliable accuracy. Regionally averaged annual snowfall and refrozen snow—together representing snow pack input—were 70.67 ± 17.32 mm and 16.56 ± 3.85 mm, respectively. On average, 38 % of this input is converted into SWE and snowmelt that contributes 12–19 % of total river discharge over the TPP, while the remaining 62 % is lost to the atmosphere through sublimation and evaporation. Snow contributes less to water resources than to atmospheric moisture over the TPP on annual average. Seasonal snow patterns vary by region: in the Pamirs snow accumulates throughout the winter, making March–April SWE a key water resource indicator; while in the Tibetan Plateau, limited snow accumulation means total annual snowmelt better representing snow water resources. Significant regional declines have been simulated for key snow components though the trends vary spatially, potentially greatly influencing weather and climate both locally and remotely. Precipitation drives SWE changes in the north and west of the TPP, while temperature and wind speed play greater roles in the center and south.