Date of this Version
Riley, W. J., S. C. Biraud, M. S. Torn, M. L. Fischer, D. P. Billesbach, and J. A. Berry (2009), Regional CO2 and latent heat surface fluxes in the Southern Great Plains: Measurements, modeling, and scaling, J. Geophys. Res., 114, G04009, doi:10.1029/2009JG001003.
 Characterizing net ecosystem exchanges (NEE) of CO2 and sensible and latent heat fluxes in heterogeneous landscapes is difficult, yet critical given expected changes in climate and land use. We report here a measurement and modeling study designed to improve our understanding of surface to atmosphere gas exchanges under very heterogeneous land cover in the mostly agricultural U.S. Southern Great Plains (SGP). We combined three years of site-level, eddy covariance measurements in several of the dominant land cover types with regional-scale climate data from the distributed Mesonet stations and Next Generation Weather Radar precipitation measurements to calibrate a land surface model of trace gas and energy exchanges (isotope-enabled land surface model (ISOLSM)). Yearly variations in vegetation cover distributions were estimated from Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index and compared to regional and subregional vegetation cover type estimates from the U.S. Department of Agriculture census. We first applied ISOLSM at a 250 m spatial scale to account for vegetation cover type and leaf area variations that occur on hundred meter scales. Because of computational constraints, we developed a subsampling scheme within 10 km ‘‘macrocells’’ to perform these high-resolution simulations. We estimate that the Atmospheric Radiation Measurement Climate Research Facility SGP region net CO2 exchange with the local atmosphere was –240, –340, and –270 gC m–2 yr–1 (positive toward the atmosphere) in 2003, 2004, and 2005, respectively, with large seasonal variations. We also performed simulations using two scaling approaches at resolutions of 10, 30, 60, and 90 km. The scaling approach applied in current land surface models led to regional NEE biases of up to 50 and 20% in weekly and annual estimates, respectively. An important factor in causing these biases was the complex leaf area index (LAI) distribution within cover types. Biases in predicted weekly average regional latent heat fluxes were smaller than for NEE, but larger than for either ecosystem respiration or assimilation alone. However, spatial and diurnal variations of hundreds of W m–2 in latent heat fluxes were common. We conclude that, in this heterogeneous system, characterizing vegetation cover type and LAI at the scale of spatial variation are necessary for accurate estimates of bottom-up, regional NEE and surface energy fluxes.