Using a Canopy Model Framework to Improve Large-Eddy Simulations of the Atmospheric Boundary Layer in the Weather Research and Forecasting Model

A canopy model framework is implemented into the Weather Research and Forecasting model to improve the accuracy of large-eddy simulation (LES) of the atmospheric boundary layer (ABL). The model includes two options that depend on the scale of surface roughness elements. A resolved canopy model, typically used to model flow through vegetation canopies, is employed when roughness elements are resolved by the vertical LES grid. In the case of unresolved roughness, a modified "pseudo-canopy" model is developed to distribute drag over a shallow layer above the surface. Both canopy model options are validated against idealized test cases in neutral stability conditions, and are shown to improve surface layer velocity profiles relative to simulations employing Monin-Obukhov Similarity Theory (MOST), which is commonly used as a surface boundary condition in ABL models. Use of the canopy model framework also leads to increased levels of resolved turbulence kinetic energy and turbulent stresses. Because LES of the ABL has a well-known difficulty recovering the expected logarithmic (log-law) velocity profile in the surface layer, particular focus is placed on using the pseudo-canopy model to alleviate this issue over a range of model configurations. Tests with varying surface roughness values, LES closures, and grid aspect ratios confirm that the pseudo-canopy model generally improves log-law agreement relative to simulations that employ a standard MOST boundary condition. The canopy model framework thus represents a low-cost, easy-to-implement method for improving LES of the ABL. Prepared by LLNL under Contract DE-AC52-07NA27344.