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

A research group of Xinjiang Institute of Ecology and Geography of Chinese Academy of Sciences cooperated with the scientists from Ghent University and Royal Meteorological Institute in Belgium, revealing the influences of key vegetation parameters on snow simulation, and the variations of snow mass and its forcing drivers in the Tianshan Mountains by mean of the WRF/Noah-MP model and remote sensing vegetation products.

The 10 years control numerical experiment suggested that more realistic vegetation parameters could improve the performance of the snow simulation through reducing the loss of intercepted snow and melted snow, especially in the forest regions.

The results entitled as “Improving snow simulation with more realistic vegetation parameters in a regional climate model in the Tianshan Mountains, Central Asia” has been published in Journal of Hydrology.

Moreover, a long-time snow simulation from 1982 to 2018 indicated that 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 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.

The research results titled “Variation of snow mass in a regional climate model downscaling simulation covering the Tianshan Mountains, Central Asia” has been published in Journal of Geophysical Research: Atmospheres.

Article link:

https://doi.org/10.1016/j.jhydrol.2020.125525

https://doi.org/10.1029/2020JD034183

Contact: LIU Jie, Xinjiang Institute of Ecology and Geography 

E-mail: liujie@ms.xjb.ac.cn 

(From: Xinjiang Institute of Ecology and Geography)