Estimation of subpixel snow sublimation from multispectral satellite observations

Ning Wang, Li Jia*, Chaolei Zheng, Massimo Menenti

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)


Snow sublimation is an important hydrological process and its spatial and temporal variation remains largely unknown; however, few studies have been conducted to quantify its spatial variability. Our study focuses on the evaluation of two algorithms, Penman-Monteith (P-M) equation and the bulk aerodynamic (BA) parameterization of snow sublimation. The two methods were first evaluated against eddy covariance (EC) measurements of latent heat flux at towers located in the upper reaches of the Heihe River Basin (China). Both methods were in good agreement with the ground observations with high coefficient of determination (R2) and low root mean squared error (RMSE). Next, we estimated subpixel snow sublimation using remote sensing data at a 1-km × 1-km spatial resolution. The results based on satellite data were evaluated against ground measurements at the two experimental sites. The P-M equation gave R2 = 0.75, RMSE = 8.4 Wm-2 for Dashalong site and R2 = 0.36, RMSE = 9.1 Wm-2 for the Dadongshu site and performed better than the BA parameterization, which gave R2 = 0.65, RMSE = 17.5 Wm-2 for the Dashalong site and R2 = 0.06, RMSE = 21.2 Wm-2 for the Dadongshu site. Overall, the results indicate that P-M is promising for estimating snow sublimation at the regional scale using satellite observations.

Original languageEnglish
Article number046017
JournalJournal of Applied Remote Sensing
Issue number4
Publication statusPublished - 1 Oct 2017


  • bulk aerodynamic method
  • Penman-Monteith
  • satellite observations
  • snow sublimation


Dive into the research topics of 'Estimation of subpixel snow sublimation from multispectral satellite observations'. Together they form a unique fingerprint.

Cite this