Spatial Heterogeneity as a Bridge Between Canopy Turbulence and Numerical Weather Prediction

Abstract:

Forest canopies are a fundamental component of the global ecosystem and a significant source of terrestrial surface roughness. In contemporary NWP models, forest canopies are typically considered as homogeneous rough surfaces through Monin-Obukhov similarity theory. The validity of similarity theory for this setting lies in the assumption that turbulence introduced by spatial heterogeneity within the canopy blend away in the lower ABL. However, the blending height is a function of canopy geometry as well as atmospheric properties necessitating the use of subgrid turbulence models or semi-empirical relationships.

In order to resolve heterogeneous canopies in NWP models, a series of wind tunnel experiments were performed at Portland State University. Scale model canopies composed of individual trees were manufactured from reticulated foam and arranged in alternating series of patches and gaps to create five heterogeneous canopy scenarios. SPIV measurements were collected in gaps as well as above canopy patches. Heterogeneous canopy structure is quantified through the lacunarity approach developed by Kadum et al. and related to relevant terms from the equations for kinetic energy. From here, a novel parameterization is proposed linking heterogeneous canopy structure to fluid behavior in the lower ABL for NWP models.