EGU23-4012, updated on 16 Apr 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

How well do global snow products characterize snow storage in High Mountain Asia?

Yufei Liu1, Yiwen Fang2, Dongyue Li2, and Steven A. Margulis2
Yufei Liu et al.
  • 1China Institute of Water Resources and Hydropower Research, Beijing, China (
  • 2Department of Civil and Environmental Engineering, University of California, Los Angeles, Los Angeles, CA, USA

Accurate characterization of peak snow water storage is essential for assessing warm-season water availability in regions reliant on snowmelt-driven runoff. However, knowledge of peak snow water storage in data-sparse regions, such as High Mountain Asia (HMA), is still lacking due to overreliance on model-based estimates. Here, estimates of peak snow storage from eight global snow products were evaluated over HMA, using a newly developed High Mountain Asia Snow Reanalysis (HMASR) dataset as a reference. The particular focus of this work was on peak annual snow storage, as it is the first-order determinant of warm-season water supply in snow-dominated basins.

The results suggest large uncertainty in the eight global snow products in High Mountain Asia, with the climatological peak storage found to be 161 km3 ± 102 km3 across products. Compared to HMASR, most global snow products underestimate peak snow storage in HMA, with an average 33% underestimation. Large inter-product variability in cumulative snowfall (335 km3 ± 148 km3) is found to explain most of the peak snow storage uncertainty (>80%). Significant snowfall loss to ablation during accumulation season (51% ± 9%) also plays an important role in peak snow storage uncertainty, and deserves more investigation in future work.

How to cite: Liu, Y., Fang, Y., Li, D., and Margulis, S. A.: How well do global snow products characterize snow storage in High Mountain Asia?, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4012,, 2023.