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United States Department of Agriculture

Agricultural Research Service

Research Project: PRESERVING GROUND WATER QUALITY AND AVAILABILITY FOR AGRICULTURE IN THE LOWER MISSISSIPPI RIVER BASIN

Location: Watershed Physical Processes Research Unit

Title: Sensitivity of model parameterizations for simulated latent heat flux at the snow surface for complex mountain sites

Authors
item Reba, Michele
item Marks, Daniel
item Link, Timothy -
item Pomeroy, John -
item Winstral, Adam

Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 8, 2012
Publication Date: January 30, 2014
Repository URL: http://handle.nal.usda.gov/10113/58307
Citation: Reba, M.L., Marks, D.G., Link, T., Pomeroy, J., Winstral, A.H. 2014. Sensitivity of model parameterizations for simulated latent heat flux at the snow surface for complex mountain sites. Hydrological Processes. 28:868-881.

Interpretive Summary: Accurate modeling of the seasonal snow cover in regions of western North America is important for water resources management, where snow can constitute approximately 50-70% of water resources. Improvements in modeling seasonal snow cover may improve the management of this over-allocated resource. Snow melt is dominated by radiation followed by turbulent fluxes. Turbulent fluxes are made up of sensible and latent heat flux. Latent heat flux is the energy associated with a change in phase and is significant during rain-on-snow events. Projected climate change suggests an increase in the frequency of rain-on-snow events. The measurement of turbulent fluxes over snow is generally difficult and even more complex in mountainous regions. Parameters associated with the calculation of latent heat flux were determined using measured values from eddy covariance (EC) sensors at two sites over snow in a mountainous region. Accuracy of simulated snow water equivalent was retained while parameters for latent heat flux were optimized. Optimal roughness length and snow model active layer thickness at the two study sites were determined for the snow season. Point modeling was used to determine the optimal parameters, which were linked to vegetation and site characteristics. Future work will incorporate site characteristics for distributed modeling of the seasonal snow cover.

Technical Abstract: The snowcover energy balance is typically dominated by net radiation and sensible and latent heat fluxes. Validation of the two latter components is rare and often difficult to undertake at complex mountain sites. Latent heat flux, the focus of this paper, is the primary coupling mechanism between the snow surface and the atmosphere. It accounts for the critical exchange of mass (sublimation or condensation), along with the associated snowcover energy loss or gain. Measured and modeled latent heat fluxes at a wind-exposed and a wind-sheltered site were compared in order to evaluate temporal variability in model parameters. A well-tested and validated snowcover energy balance model, Snobal, was selected for this comparison because of previously successful applications of the model at these sites, and because of the adjustability of the parameters specific to latent heat transfer within the model. Simulated latent heat flux and snow water equivalent (SWE) were not sensitive to different formulations of the stability profile functions associated with heat transfer calculations. The model parameters of snow surface roughness length and active snow layer thickness were used to improve latent heat flux simulations while retaining accuracy in the simulation of the snow water equivalent. Optimal parameters for simulated latent heat flux and SWE were found at the exposed site with a shorter roughness length and thicker active layer, and at the sheltered site with a longer roughness length and thinner active layer. These findings were linked to physical characteristics of the study sites and could be incorporated into the spatially distributed version of the model Isnobal by allowing critical parameters to vary over the modeling domain.

Last Modified: 10/1/2014
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