A multi-scale data set based on CASES-97 for studying land-surface heterogeneity and for validating land-surface models

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we developed a multi-scale data set based on the Cooperative Atmosphere-Surface Exchange Study (CASES-97) field observation conducted in the upper Walnut River watershed, Kansas. The domain covered by this data set is 74x71 km, which approaches the grid size used in many weather and climate models. The surface meteorological conditions obtained from nine surface stations, high-resolution S-Pol radar precipitation analysis, and 4-km hourly NCEP national precipitation analysis are interpolated/mapped into half-hourly, continuous gridded data with three resolutions of 1, 5, and 10 km. Also, the gridded surface boundary conditions are comprised of a 1x1 km STATSGO soil data, 1x1 km USGS/EROS vegetation data, and 30 m Kansas land use map. The 1x1 km AVHRR products which give the NDVI was also utilized to specify the surface vegetation characterization.

We use this multi-scale surface forcing data set to drive three land-surface models to generate gridded surface heat flux maps for the CASES-97 area. The surface heat fluxes generated by the models are validated against those measured at ten flux stations to ensure the quality of the uniformly distributed surface heat flux maps. Based on these multi-scale surface flux maps, we investigated several approaches for estimating the area-integrated surface heat flux. These flux maps are also compared to the aircraft-measured fluxes at multiple levels to understand the effects of subgrid-scale variability on the area-integrated heat fluxes.