During the 1997 Southern Great Plains Hydrology Experiment (SGP97), passive microwave observations using the L-band electronically scanned thinned array radiometer (ESTAR) were used to extend surface soil moisture retrieval algorithms to coarser resolutions and larger regions with more diverse conditions. This near-surface soil moisture product (W) at 800 m pixel resolution together with land use and fractional vegetation cover (f/sub c/) estimated from normalized difference vegetation index (NDVI) was used for computing spatially distributed sensible (H) and latent (LE) heat fluxes over the SGP97 domain (an area /spl sim/40/spl times/260 km) using a remote sensing model (called the two-source energy Balance-soil moisture, TSEB/sub SM/, model). With regional maps of W and the heat fluxes, spatial correlations were computed to evaluate the influence of W on H and LE. For the whole SGP97 domain and full range in f/sub c/, correlations (R) between W and LE varied from 0.4 to 0.6 (R/spl sim/0.5 on average), while correlations between W and H varied from -0.3 to -0.7 (R/spl sim/-0.6 on average). The W-LE and W-H correlations were dramatically higher when variability due to f/sub c/ was considered by using NDVI as a surrogate for f/sub c/ and computing R between heat fluxes and corresponding W values under similar fractional vegetation cover conditions. The results showed a steady decline in correlation with increasing NDVI or f/sub c/. Typically, |R|/spl gsim/0.9 for data sorted by NDVI having values /spl lsim/0.5 or f/sub c//spl lsim/0.5, while |R|/spl lsim/0.5 for the data sorted under high canopy cover where NDVI/spl gsim/0.6 or f/sub c//spl gsim/0.7.
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Bindlish et al. (2001) studied this question.
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