Assessing Wind Velocity Errors in Doppler LiDARs Using a Large Eddy Simulation Approach in an Urban Environment

Doppler Wind LiDARs (DWLs) are increasingly used in boundary layer meteorology, offering detailed wind measurements. They are increasingly adopted in urban environments, providing a significant advantage over traditional mast-mounted measurements, which are limited in height. However, many DWL scanning methods assume a uniform wind field, a condition that can be invalid in urban environments, where turbulence induced by buildings and varying terrain introduces considerable heterogeneity in wind patterns.

Large-Eddy Simulations (LES), such as the Parallelized Large-Eddy Simulation Model (PALM), resolves turbulent motions at high grid resolution and offers an effective framework for assessing errors in DWL sampling techniques. This study employs the Virtual Doppler LiDAR (VDL) tool (Rahlves et al., 2022), designed specifically for PALM, to simulate velocity profiles derived from the Velocity Azimuth Display (VAD) scanning technique. This popular method involves scanning the laser beam in a conical pattern around zenith at a fixed elevation angle to estimate wind velocity and profiles. However, the time required to complete a full 360° scan may introduce inaccuracies, as it assumes wind conditions remain constant throughout the scan. In reality, significant variations in wind, caused by turbulence or flow inhomogeneity within the sampling volume, can cause errors.

The simulations are done for Bristol, UK, a city participating in the ASSURE Project (Across-Scale Processes in Urban Environments). Multiple DWLs were deployed across the city, with scanning strategies being tested during a year-long field campaign commencing in May 2024. This study evaluates differences between the vertical wind profile derived from a VAD scan using the VDL and the profile directly taken from the PALM model, under stable boundary layer conditions. The research offers insights into the challenges of urban wind velocity measurement using DWL instruments and the potential implications of these errors in our understanding of urban climate processes.