UCSB Biogeography Lab

UCSB Biogeography Lab Publications Abstracts

CORRESPONDENCE BETWEEN REMOTELY SENSED DATA AND LAND SURFACE ENERGY BALANCE OVER A TALLGRASS PRAIRIE
FRIEDL, MARK ANDREW, 1993
PhD Dissertation, Department of Geography, University of California, Santa Barbara. 185 pp.

This research explores relationships among remotely sensed data and land surface energy balance components over a tallgrass prairie site in northeastern Kansas. An empirical analysis of contemporaneous measurements of land surface energy balance components and remotely sensed data focussed on the role of spatial variation in percent canopy cover versus spatial variation in surface energy balance as the causal mechanisms contributing to spatial variance in $T/sb[s]$. Next, an invertible two-layer energy balance model was developed that explicitly accounts for the unique microclimate of the grassland canopies present at the study site. Finally, instantaneous area-integrated fluxes estimated from ground stations distributed across the study site were compared with estimates calculated by running the energy balance model using a hybrid stratification-modeling app=
roach, where the input data to the model were stratified by burning treatment. Land surface energy balance showed little statistical association with $T/sb[s].$ Spatial variation in $T/sb[s]$ was primarily a function of spatial variation in the fraction of exposed soils, which tended to be warmer than the overlying vegetation canopies. The two-layer energy balance model reproduced observed fluxes with good accuracy at individual surface flux sites using in-situ data, but exhibited moderate sensitivity to uncertainty in canopy stomatal resistance and emissivity for both the soil and canopy. Comparison of observed fluxes over individual surface flux sites with estimates modeled using remotely sensed data showed significant scatter, but overall good agreement. Estimates of area-integrated fluxes calculated using random samples of remotely sensed data exhibited significant time and flux dependent differences from area-integrated fluxes calculated from ground station data. The causes of these discrepancies probably lie in a combination of effects resulting from errors in model specification and parameterization, and effects associated with the positioning of surface flux stations in misrepresentative areas within the study site.

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	UCSB Biogeography Lab Publications Abstracts CORRESPONDENCE BETWEEN REMOTELY SENSED DATA AND LAND SURFACE ENERGY BALANCE OVER A TALLGRASS PRAIRIE FRIEDL, MARK ANDREW, 1993 PhD Dissertation, Department of Geography, University of California, Santa Barbara. 185 pp. This research explores relationships among remotely sensed data and land surface energy balance components over a tallgrass prairie site in northeastern Kansas. An empirical analysis of contemporaneous measurements of land surface energy balance components and remotely sensed data focussed on the role of spatial variation in percent canopy cover versus spatial variation in surface energy balance as the causal mechanisms contributing to spatial variance in $T/sb[s]$. Next, an invertible two-layer energy balance model was developed that explicitly accounts for the unique microclimate of the grassland canopies present at the study site. Finally, instantaneous area-integrated fluxes estimated from ground stations distributed across the study site were compared with estimates calculated by running the energy balance model using a hybrid stratification-modeling app= roach, where the input data to the model were stratified by burning treatment. Land surface energy balance showed little statistical association with $T/sb[s].$ Spatial variation in $T/sb[s]$ was primarily a function of spatial variation in the fraction of exposed soils, which tended to be warmer than the overlying vegetation canopies. The two-layer energy balance model reproduced observed fluxes with good accuracy at individual surface flux sites using in-situ data, but exhibited moderate sensitivity to uncertainty in canopy stomatal resistance and emissivity for both the soil and canopy. Comparison of observed fluxes over individual surface flux sites with estimates modeled using remotely sensed data showed significant scatter, but overall good agreement. Estimates of area-integrated fluxes calculated using random samples of remotely sensed data exhibited significant time and flux dependent differences from area-integrated fluxes calculated from ground station data. The causes of these discrepancies probably lie in a combination of effects resulting from errors in model specification and parameterization, and effects associated with the positioning of surface flux stations in misrepresentative areas within the study site. Go to UCSB Biogeography Lab home page
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