Home >> Research Progress

Modeling Reveals What Drives Snow Mass Variation in Tianshan Mountains

2021-05-31

Seasonal snow mass is an essential natural resource in the Tianshan Mountains. Climate warming alters the snowmelt timing and shortens the snow cover duration.

However, a reliable estimation of snow mass in the Tianshan Mountains is still unclear due to the scarcity of extensive continuous surface observations and a complex spatial heterogeneity.

A research group of Xinjiang Institute of Ecology and Geography of Chinese Academy of Sciences, in cooperation with scientists from Ghent University and Royal Meteorological Institute in Belgium, revealed the variations of snow mass and its forcing drivers in the Tianshan Mountains by means of the WRF/Noah-MP model and remote sensing vegetation products.

A long-time snow simulation from 1982 until 2018 indicated that the March snow mass (97.85 ± 16.60 Gt) represented the annual maximum snow storage in the entire Tianshan Mountains and exhibited a negligible trend. The total precipitation amount during the cold season (November-March) controlled the variations of the March snow mass. The increased precipitation in the high-altitude regions contributed to the extensive snow mass, which could offset snow mass loss in the low-altitude regions of the Tianshan Mountains. Additionally, the March snow cover fraction declined significantly, which was mainly attributed to a rapid increase of air temperature in March, particularly in the Southern Tianshan Mountains.

In their previous studies, the researchers also revealed the influences of key vegetation parameters on snow simulation. Compared with default vegetation parameters, more realistic remote sensing vegetation parameters could improve the performance of the snow simulation in the WRF/Noah-MP through reducing the loss of intercepted snow and melted snow, especially in the forest regions.

Related studies were published in Journal of Geophysical Research: Atmospheres and Journal of Hydrology.

 

Contact: LIU Jie, Xinjiang Institute of Ecology and Geography 

E-mail: liujie@ms.xjb.ac.cn