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Radiometric surface temperatures obtained from remote sensing measurements are a function of both the physical surface temperature and the effective emissivity of the surface within the band pass of the radiometric measurement. For sparsely vegetated areas, however, a sensor views significant fractions of both bare soil and various vegetation types. In this case the radiometric response of a sensor is a function of the emissivities and kinetic temperatures of various surface elements, the proportion of those surface elements within the field of view of the sensor, and the interaction of radiation emitted from the various surface components. In order to effectively utilize thermal remote sensing data to quantify energy balance components for a sparsely vegetated area, it is important to examine the typical magnitude and degree of variability of emissivity and surface temperature for such surfaces. Surface emissivity measurements and ground and low-altitude-aircraft-based surface temperature measurements (8-13 μm band pass) made in conjunction with the Monsoon '90 field experiment were used to evaluate the typical variability of those quantities during the summer rainy season in a semiarid watershed. The average value for thermal band emissivity of the exposed bare soil portions of the surface was found to be approximately 0.96; the average value measured for most of the varieties of desert shrubs present was approximately 0.99. Surface composite emissivity was estimated to be approximately 0.98 for both the grass-dominated and shrub-dominated portions of the watershed. The spatial variability of surface temperature was found to be highly dependent on the spatial scale of integration for the instantaneous field of view (IFOV) of the instrument, the spatial scale of the total area under evaluation, and the time of day. For the conditions which existed during most of the Monsoon '90 experiment, the differences in kinetic (physical) temperature between the vegetation and soil background were typically between 10° and 25°C at midday. These differences gave rise to large variations in radiometric composite surface temperatures observed with a ground-based instrument configuration which allowed a ground IFOV of approximately 0.5 m. An evaluation of the frequency distribution for these observations indicated that the variance in surface temperature observed over an intensively sampled target area (approximately 500 m×120 m) increased significantly in the early to late morning hours of a typical diurnal heating cycle. For aircraft-based composite radiometric temperature measurements at the watershed scale (with ground IFOV of approximately 40 m for each observation), much of the variability in surface temperature due to differences in soil and vegetation temperature was integrated into a single measurement; consequently, the variance between observations over the watershed was not significantly larger than those observed at length scales of 100 m. [ABSTRACT FROM AUTHOR]

A primary motivation for using remotely sensed data to estimate components of the surface energy balance is to quantify surface energy fluxes in a spatially distributed manner over various spatial scales. However, all models which utilize remotely sensed data to estimate surface fluxes also require input variables and parameters which cannot be estimated on a spatially distributed basis with remotely sensed data. In this analysis, data from the Monsoon '90 experiment were used to evaluate the limitations in spatially extending a relatively simple energy balance model with remotely sensed data over a semiarid rangeland watershed. Using one ground-based meteorological and flux station as a reference site, aircraft-based remotely sensed data (surface temperatures and reflectances) were used to compute energy balance components for seven other locations within the watershed. The results indicated that for clear sky conditions, all components of the surface energy balance could be estimated to within approximately the same level of uncertainty with which the fluxes were measured with ground-based flux instrumentation. However, under partly cloudy conditions the variability in incoming solar radiation across the watershed significantly degraded the estimation of distributed values of net radiation ( Rnet). If ground-based estimates of incoming solar radiation are used to calculate Rnet from remotely sensed data, then the spatial extent over which that measurement is valid limits the area over which accurate spatially distributed values of Rnet can be estimated. Additionally, the results of sensitivity analyses indicate that the level of uncertainty to which the roughness length for momentum, or z0 m, is typically known for spatially distributed values in an area of naturally variable vegetation can give rise to significant uncertainties in the estimation of sensible heat flux. For areas where the spatial variation in roughness parameters is of the order of several centimeters, the error associated with assuming constant values for the roughness length for momentum is similar in size to the errors associated with temperature variations of the order of several degrees. In order to utilize radiometric temperatures to reliably estimate spatially distributed values of sensible heat flux, techniques such as those explored by Menenti and Ritchie (this issue) are needed to provide spatially distributed information on surface roughness parameters. [ABSTRACT FROM AUTHOR]

Remotely sensed data in the visible, near-infrared, and thermal-infrared wave bands were collected from a low-flying aircraft during the Monsoon '90 field experiment. Monsoon '90 was a multidisciplinary experiment conducted in a semiarid watershed. It had as one of its objectives the quantification of hydrometeorological fluxes during the 'monsoon' or wet season. The remote sensing observations along with micrometeprological and atmospheric boundary layer (ABL) data were used to compute the surface energy balance over a range of spatial scales. The procedure involved averaging multiple pixels along transects flown over the meteorological and flux (METFLUX) stations. Average values of the spectral reflectance and thermal-infrared temperatures were computed for pixels of order 10−1 to 101 km in length and were used with atmospheric data for evaluating net radiation ( R n), soil heat flux ( G), and sensible ( H) and latent ( LE) heat fluxes at these same length scales. The model employs a single-layer resistance approach for estimating H that requires wind speed and air temperature in the ABL and a remotely sensed surface temperature. The values of R n and G are estimated from remote sensing information together with near-surface observations of air temperature, relative humidity, and solar radiation. Finally, LE is solved as the residual term in the surface energy balance equation. Model calculations were compared to measurements from the METFLUX network for three days having different environmental conditions. Average percent differences for the three days between model and the METFLUX estimates of the local fluxes were about 5% for R n, 20% for G and H, and 15% for LE. Larger differences occurred during partly cloudy conditions because of errors in interpreting the remote sensing data and the higher spatial and temporal variation in the energy fluxes. Minor variations in modeled energy fluxes were observed when the pixel size representing the remote sensing inputs changed from 0.2 to 2 km. Regional scale estimates of the surface energy balance using bulk ABL properties for the model parameters and input variables and the 10-km pixel data differed from the METFLUX network averages by about 4% for Rn, 10% for G and H, and 15% for LE. Model sensitivity in calculating the turbulent fluxes H and LE to possible variations in key model parameters (i.e., the roughness lengths for heat and momentum) was found to be fairly significant. Therefore the reliability of the methods for estimating key model parameters and potential errors needs further testing over different ecosystems and environmental conditions. [ABSTRACT FROM AUTHOR]