Abstract
Abstract. Snow security plays a crucial role in ensuring the success of winter sports events and supporting the ski industry. One effective approach to enhancing snow reliability is through snow storage. Despite its potential benefits, investigations of snow storage in China have been limited. To address this gap, we implemented snow storage covered with geotextiles at two venues, namely the Big Air Shougang (BAS) in Beijing for the Beijing 2022 Winter Olympic Games and the National Biathlon Center (NBC) in Chongli for the Beijing 2022 Winter Paralympic Games, in response to possible extreme meteorological conditions. To assess the key concerns associated with snow storage, ablation (the process of snow loss) and snow properties, we introduced a fine-snow-pile monitoring system and the SNOWPACK model. Our observations revealed that, by 18 February, the snow pile at BAS had lost 158.6 m3 of snow (equivalent to 6.7 % of the initial volume). Subsequently, the accelerated ablation was influenced by meteorological conditions and a thin geotextile layer. Between 16 January and 15 April, the snow pile at BAS experienced a total loss of 1242.9 m3 of snow (corresponding to 52.7 % of the original volume). Regarding snow properties, no significant variations were modeled at the study sites, except for the upper part of the snow piles. Notably, the evaporation of the geotextiles contributed to slowing the ablation process. Consequently, we discourage the use of impermeable coverage schemes for snow storage. Instead, the thickness of the cover played a vital role in preserving the snow pile. At Beijing and Chongli, the 0.7 and 0.4 m thick cover layers, respectively, were found to protect approximately half of the snow pile height over the summer season. Importantly, the evolution of snow properties was consistent across the different cover thicknesses. The findings of our study have implications for the ski industry in China, as they provide valuable insights into snow storage techniques and their impact on snow reliability.
Funder
Key Technologies Research and Development Program
Xinjiang Uygur Autonomous Region Department of Education
State Key Laboratory of Cryospheric Sciences, Chinese Academy of Sciences