Spatial Aerodynamic Roughness of Forested Landscapes from Airborne LiDAR

Abstract. Accurately representing forest canopies in atmospheric models remains challenging because trees interact with airflow in complex ways and strongly modulate surface–atmosphere exchanges. Aerodynamic roughness is therefore a key control variable in models of air quality, meteorology, and atmospheric transport. In this study, we test a physically based, spatially resolved framework for estimating aerodynamic roughness length from remote sensing observations. Using AHN (Actueel Hoogtebestand Nederland) airborne laser scanning data over a coniferous forest in Loobos, within the Veluwe Natura 2000 region in the central Netherlands, we derive geometric roughness parameters and compare them with eddy-covariance (EC) tower measurements. To further evaluate the approach, the LiDAR-derived roughness field is aggregated within sector-specific tower footprint climatologies and compared with tower-derived roughness estimates across 12 wind-direction sectors. Results show that LiDAR-based roughness captures strong directional and structural variability driven by forest stand height and canopy heterogeneity, closely aligning with the anisotropy observed in EC-derived displacement height and roughness length. The sector-wise comparison reproduces the main directional variability of tower-based aerodynamic roughness, although the LiDAR-derived values generally underestimate its magnitude, consistent with the distinction between structural and effective aerodynamic roughness. Seasonal differences between leaf-on and leaf-off conditions further highlight the role of canopy phenology in aerodynamic behaviour. The spatial patterns resolved by AHN demonstrate the potential of high-resolution laser scanning to capture fine-scale canopy–atmosphere interactions missed by traditional land-use-based roughness representations. This framework offers an observation-driven pathway for improving surface roughness parameterization in wind-flow and chemical transport models such as LOTOS–EUROS.