Improving estimates of roughness length in a road weather prediction model using airborne LIDAR data

Changes in the aerodynamic characteristics of a site can have a major influence on the wind regime at the surface/air interface along a road which in turn has a local effect on road surface temperatures. Traditionally a parameter known as roughness length (Z0) is used as the primary measure of the aerodynamic roughness of a surface, but Z0 is notoriously difficult to estimate. This study takes a new approach to the estimation of Z0 for a route-based road weather prediction model, using high resolution LIDAR data coupled with spatial processing techniques to provide estimates of effective roughness length (Z0 eff ) which take into account both the prevailing wind direction and the height of the surface elements (e.g. buildings, trees) within the upwind fetch of the forecast points. The range of roughness values obtained using this new technique are consistent with published values obtained from detailed boundary layer experiements, and are shown to distinguish between a variety of land use categories around a mixed urban and rural study route, thus giving confidence in the new technique.