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Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

Journal article
Authors L. Wang
L. Sun
M. Shrestha
X. Li
W. Liu
J. Zhou
K. Yang
H. Lu
Deliang Chen
Published in Journal of Geophysical Research - Atmospheres
Volume 121
Issue 20
Pages 12,005-12,030
ISSN 0148-0227
Publication year 2016
Published at Department of Earth Sciences
Pages 12,005-12,030
Language en
Keywords distributed hydrological model, lapse rate, MODIS land surface temperature, snow process, water and energy cycle
Subject categories Geophysics


In distributed hydrological modeling, surface air temperature (Tair) is of great importance in simulating cold region processes, while the near-surface-air-temperature lapse rate (NLR) is crucial to prepare Tair (when interpolating Tair from site observations to model grids). In this study, a distributed biosphere hydrological model with improved snow physics (WEB-DHM-S) was rigorously evaluated in a typical cold, large river basin (e.g., the upper Yellow River basin), given a mean monthly NLRs. Based on the validated model, we have examined the influence of the NLR on the simulated snow processes and streamflows. We found that the NLR has a large effect on the simulated streamflows, with a maximum difference of greater than 24% among the various scenarios for NLRs considered. To supplement the insufficient number of monitoring sites for near-surface-air-temperature at developing/undeveloped mountain regions, the nighttime Moderate Resolution Imaging Spectroradiometer land surface temperature is used as an alternative to derive the approximate NLR at a finer spatial scale (e.g., at different elevation bands, different land covers, different aspects, and different snow conditions). Using satellite-based estimation of NLR, the modeling of snow processes has been greatly refined. Results show that both the determination of rainfall/snowfall and the snowpack process were significantly improved, contributing to a reduced summer evapotranspiration and thus an improved streamflow simulation. ©2016. American Geophysical Union. All Rights Reserved.

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