Improving and validating 3D models for the leaf energy balance in canopy-scale problems with complex geometry

Thursday, 18 December 2014
Brian Bailey1, Rob Stoll II1, Nathan E Miller1, Eric Pardyjak1 and Walter Mahaffee2, (1)University of Utah, Mechanical Engineering, Salt Lake City, UT, United States, (2)USDA ARS, Corvallis, OR, United States
Plants cover the majority of Earth’s land surface, and thus play a critical role in the surface energy balance. Within individual plant communities, the leaf energy balance is a fundamental component of most biophysical processes. Absorbed radiation drives the energy balance and provides the means by which plants produce food. Available energy is partitioned into sensible and latent heat fluxes to determine surface temperature, which strongly influences rates of metabolic activity and growth. The energy balance of an individual leaf is coupled with other leaves in the community through longwave radiation emission and advection through the air. This complex coupling can make scaling models from leaves to whole-canopies difficult, specifically in canopies with complex, heterogeneous geometries. We present a new three-dimensional canopy model that simultaneously resolves sub-tree to whole-canopy scales. The model provides spatially explicit predictions of net radiation exchange, boundary-layer and stomatal conductances, evapotranspiration rates, and ultimately leaf surface temperature. The radiation model includes complex physics such as anisotropic emission and scattering. Radiation calculations are accelerated by leveraging graphics processing unit (GPU) technology, which allows canopy-scale problems to be performed on a standard desktop workstation. Since validating the three-dimensional distribution of leaf temperature can be extremely challenging, we used several independent measurement techniques to quantify errors in measured and modeled values. When compared with measured leaf temperatures, the model gave a mean error of about 2°C, which was close to the estimated measurement uncertainty.