Investigating Extreme Snowfall Changes in China Based on an Ensemble of High-Resolution Regional Climate Models

Abstract

Anthropogenically induced global warming intensifies the water cycle around the world. As a critical sector of the water cycle, snow depth and its related extremes greatly impact agriculture, animal husbandry, and food security, yet lack investigation. In this study, five high-resolution climate models are selected to simulate and project snow depth and its extremes over China. The simulation capabilities of models in reproducing the basic climate variables in winter are gauged in terms of spatial and temporal patterns over nine subregions. It is found that the driving global climate model (GCM) can contribute to similar patterns, while the different regional climate model (RCM) schemes lead to large variations in the snowfall accumulating on the land surface. The warming magnitude is larger under a higher representative concentration pathway (RCP) scenario (2.5 °C greater under RCP8.5 than RCP4.5). The distribution of ensemble mean winter precipitation changes is more fragmented because of the relatively low skill in reproducing water-related content in the climate system. The projected precipitation change is larger under RCP8.5 than under RCP4.5 due to the amplification of the hydrological cycle by temperature warming. The projected changes in the ensemble mean snow depth mainly occur over the Tibetan Plateau with a decreasing trend. Only several grids over the Himalayas Mountains and the upper stream of the Yarlung Zangbo River are projected with a slight increase in snow depth. Both the intensity and frequency of extreme snow events are projected to increase in Northeast China and Inner Mongolia, which are important agricultural and animal husbandry production areas in China. The reason behind this projection can be explained by the fact that the hydrological cycle intensified by temperature warming leads to excessive snowfall stacking up during winter. The changes in extreme snowfall events in the future will have a significant impact on China’s agricultural and animal husbandry production and threaten food security.

Snowfall Shift and Precipitation Variability over Sikkim Himalaya Attributed to Elevation-Dependent Warming

“…The North Atlantic Oscillation (NAO), El Nio Southern Oscillation (ENSO), Jet Stream, Indian Ocean Dipole (IOD) and other monsoons teleconnection climatic factors also influence precipitation distribution and amount over the Himalayan region [5,[17][18][19] . By utilizing Weather Research Forecast simulation, Norris et al (2015) addressed extreme snowfall events over the entire Himalayan region [14,[20][21][22][23][24][25][26][27][28][29] . The amount of snowfall and resulting snow accumulation are recommended as key indicators of climatic change [11,[30][31][32][33][34] .…”