Influence of near-surface soil moisture on regional scale heat fluxes: model results using microwave remote sensing data from SGP97

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_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 ~40×260 km) using a remote sensing model (called the two-source energy Balance-soil moisture, TSEB_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_c, correlations (R) between W and LE varied from 0.4 to 0.6 (R~0.5 on average), while correlations between W and H varied from -0.3 to -0.7 (R~-0.6 on average). The W-LE and W-H correlations were dramatically higher when variability due to f_c was considered by using NDVI as a surrogate for f_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_c. Typically, |R|≳0.9 for data sorted by NDVI having values ≲0.5 or f_c ≲0.5, while |R|≲0.5 for the data sorted under high canopy cover where NDVI≳0.6 or f_c≳0.7