Evaluation of a Two-Source Snow–Vegetation Energy Balance Model for Estimating Surface Energy Fluxes in a Rangeland Ecosystem

Cezar Kongoli Earth System Science Interdisciplinary Center, University of Maryland College Park, and NOAA/National Environmental Satellite, Data, and Information Service, College Park, Maryland

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William P. Kustas Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland

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Martha C. Anderson Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland

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John M. Norman Department of Soil Science, University of Wisconsin—Madison, Madison, Wisconsin

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Joseph G. Alfieri Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland

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Gerald N. Flerchinger Northwest Watershed Research Center, Agricultural Research Service, USDA, Boise, Idaho

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Danny Marks Northwest Watershed Research Center, Agricultural Research Service, USDA, Boise, Idaho

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Abstract

The utility of a snow–vegetation energy balance model for estimating surface energy fluxes is evaluated with field measurements at two sites in a rangeland ecosystem in southwestern Idaho during the winter of 2007: one site dominated by aspen vegetation and the other by sagebrush. Model parameterizations are adopted from the two-source energy balance (TSEB) modeling scheme, which estimates fluxes from the vegetation and surface substrate separately using remotely sensed measurements of land surface temperature. Modifications include development of routines to account for surface snowmelt energy flux and snow masking of vegetation. Comparisons between modeled and measured surface energy fluxes of net radiation and turbulent heat showed reasonable agreement when considering measurement uncertainties in snow environments and the simplified algorithm used for the snow surface heat flux, particularly on a daily basis. There was generally better performance over the aspen field site, likely due to more reliable input data of snow depth/snow cover. The model was robust in capturing the evolution of surface energy fluxes during melt periods. The model behavior was also consistent with previous studies that indicate the occurrence of upward sensible heat fluxes during daytime owing to solar heating of vegetation limbs and branches, which often exceeds the downward sensible heat flux driving the snowmelt. However, model simulations over aspen trees showed that the upward sensible heat flux could be reversed for a lower canopy fraction owing to the dominance of downward sensible heat flux over snow. This indicates that reliable vegetation or snow cover fraction inputs to the model are needed for estimating fluxes over snow-covered landscapes.

Corresponding author address: Dr. Cezar Kongoli, NOAA/NESDIS, NOAA Center for Weather and Climate Prediction (NCWCP), 5830 University Research Ct. 2804, College Park, MD 20740. E-mail: cezar.kongoli@noaa.gov

Abstract

The utility of a snow–vegetation energy balance model for estimating surface energy fluxes is evaluated with field measurements at two sites in a rangeland ecosystem in southwestern Idaho during the winter of 2007: one site dominated by aspen vegetation and the other by sagebrush. Model parameterizations are adopted from the two-source energy balance (TSEB) modeling scheme, which estimates fluxes from the vegetation and surface substrate separately using remotely sensed measurements of land surface temperature. Modifications include development of routines to account for surface snowmelt energy flux and snow masking of vegetation. Comparisons between modeled and measured surface energy fluxes of net radiation and turbulent heat showed reasonable agreement when considering measurement uncertainties in snow environments and the simplified algorithm used for the snow surface heat flux, particularly on a daily basis. There was generally better performance over the aspen field site, likely due to more reliable input data of snow depth/snow cover. The model was robust in capturing the evolution of surface energy fluxes during melt periods. The model behavior was also consistent with previous studies that indicate the occurrence of upward sensible heat fluxes during daytime owing to solar heating of vegetation limbs and branches, which often exceeds the downward sensible heat flux driving the snowmelt. However, model simulations over aspen trees showed that the upward sensible heat flux could be reversed for a lower canopy fraction owing to the dominance of downward sensible heat flux over snow. This indicates that reliable vegetation or snow cover fraction inputs to the model are needed for estimating fluxes over snow-covered landscapes.

Corresponding author address: Dr. Cezar Kongoli, NOAA/NESDIS, NOAA Center for Weather and Climate Prediction (NCWCP), 5830 University Research Ct. 2804, College Park, MD 20740. E-mail: cezar.kongoli@noaa.gov
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