Land surface modeling of energy-balance components: Model validation and scaling effects

Scope and method of study. Appropriate quantification of surface energy balance components that influence land-atmosphere exchange phenomena is important for improved weather prediction. The issue of scale interaction has emerged as one of the crucial challenges for the parameterization of general circulation models (GCMs) due to the strong interconnection between land and atmospheric processes. The objective of this study was to examine the effects of different spatial scales of input data on modeled net radiation, latent, sensible and ground heat fluxes and hence to understand the resolution needed for the realistic modeling of large-area land and atmospheric interactions. This study employed the NOAH-OSU (Oregon State University) Land Surface Model (LSM), which is a popular model used in a coupled fashion with the NCEP operational Eta and PSU/MM5 mesoscale models. Since the model requires downwelling longwave radiation as one of its inputs, a simple estimation procedure was developed and tested using nine Oklahoma Atmospheric Surface-Layer Instrumentation System (OASIS) sites. Then the full LSM was tested using seven OASIS sites with diverse soils, vegetation and climate. Finally, at three different spatial scales, model simulations were performed for the most homogeneous and the most heterogeneous areas of the Southern Great Plains 1997 study region.; Findings and conclusions. The newly developed scheme for the estimation of downwelling longwave radiation performed very well during both daytime and nighttime as well as under clear and cloudy sky conditions. Two methods of green vegetation fraction showed some differences in the estimates of latent and sensible heat fluxes. LSM validation using OASIS measurements at individual sites showed that the seven-site mean of modeled net radiation had a slight positive bias. It appeared that the model assigned most of this excess energy to latent heat flux. In the scaling study for the heterogeneous region, simulation results for the 200 m and 2 km scales matched well for net radiation, latent, sensible and ground heat fluxes while they differed at the 20 km resolution. For the homogeneous region, the model's flux predictions at all three scales were in close agreement. The results suggested that the aggregation of spatially variable soil and vegetation inputs can have a significant impact on the quantification of surface energy-balance components and partitioning of latent and sensible heat fluxes. It was confirmed that the effects of scaling-up of input data on model estimates are more pronounced for heterogeneous areas than for homogeneous areas.