Abstract

During a remote sensing field experiment conducted in the Southern Great Plains in 1997 (SGP97), tower and aircraft-based flux observations were collected over one of the main study sites in central Oklahoma. This is an agricultural region and contains primarily grassland/pasture and winter wheat, which was recently harvested leaving a significant number of fields either as wheat stubble or plowed bare soil. Multi-spectral data obtained by aircraft provided high-resolution (30 m) spatially-distributed vegetation cover and surface temperature information over the study area. The spatial variations in these surface states strongly affect the partitioning of surface fluxes between sensible and latent heat. These data, together with coarser resolution (5 km) satellite data, are used in a remote sensing-based energy balance modeling system that disaggregates flux estimates from 5 km to 30-m resolution. The resulting high-resolution flux maps provide a means for evaluating whether tower and aircraft-based flux measurements sample a full range in flux conditions for this landscape. In addition, this remote sensing-based modeling system can be used to investigate the influence of variability in these key surface states on tower and aircraft measurements through flux-footprint modeling. Under the light wind and unstable conditions that existed during the observations, highest correlation between aircraft and modeled estimated heat and water vapor fluxes were obtained using different flux-footprint estimates. More specifically, the source area for heat was estimated to be much closer to the aircraft flight line than for water vapor.

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