Estimating aerodynamic roughness (z0) from terrestrial laser scanning point cloud data over un-vegetated surfaces

Aerodynamic roughness (z0) is a widely used parameter describing the effective roughness of a surface to fluid flow, commonly measured with wind profiling. Wind profiling is time-consuming, equipment intensive, spatially limited, and requires specific wind conditions. To solve this, satellite and airborne remote sensing and ground-based proxies have been developed to measure and relate physical surface roughness to profile-measured aerodynamic roughness. However, for un-vegetated settings, most satellite and airborne remote sensing proxies are, generally, incapable of estimating sub-meter roughness and ground-based measurements are spatially limited and time-consuming. This paper presents a new method for estimating physical roughness using terrestrial laser scanning (TLS) point cloud data. TLS data provide a centimeter-scale, three-dimensional, spatially contiguous representation of a surface. At seven sites with different roughness conditions (silt playa to boulder covered) we compared TLS metrics of surface roughness to wind profile estimates of z0. From point clouds, the mean height (hTLS) and root-mean squared height (RMSH) of roughness elements were calculated. Manual measurements of clast dimensions, height, and density were used to guide point cloud processing. Results indicate a strong positive linear relation between z0 and hTLS (r2 = 0.99, p < 0.001), and between z0 and RMSH (r2 = 0.96, p < 0.001). This suggests that TLS measurements of physical roughness could serve as a proxy for z0 based on empirical relations developed with wind profiling in un-vegetated terrain. With further testing, TLS could improve operational parameterizations of z0 for use in large scale atmosphere-surface models.