Observations of the Microscale Urban Wind Field Impacting UAVs Using Scanning Doppler Lidar

Urban landscapes give rise to complex wind conditions, such as micro convective cycles, accelerated winds through urban canyons and even large vortices downstream buildings. Such Microscale Wind hazards impact not only the flight dynamics of an unmanned aerial vehicle (UAV) but the whole UAV eco-system itself. For example, the wear and tear of motors induced due to consistently flying through rough turbulent environments can severely deteriorate UAV’s reliability statistics and complicate maintenance operations. Or by simply flying at altitudes with strong headwinds, a UAV’s flight range can be substantially reduced, thus impacting recharging infrastructure, and market reach in case of drone deliveries or passenger transport. Thus, understanding the dynamic of the urban wind field convective cycles can provide UAV’s a wealth of information to support the avoidance of dangerous wind shear, turbulence, headwinds and take advantage of tailwinds.

The scope of this study is to put into evidence by direct measurement the characteristics of the microscale urban wind field impacting UAV operations. To better qualify and quantify the variability of the urban wind field a long-range scanning Doppler LIDAR was installed on the roof of a building within the city of Helsinki, Finland, Europe and collected wind data from multiple scans over a couple of months. Raw radial wind data was collected from the LIDAR and processed to give a three-dimensional vector wind field over the city. The spatial dimensions of the data is of 6x6 km in the horizontal direction and 300m in the vertical direction with a resolution of 200m in the horizontal and 50 m in the vertical.
A most basic observation of this data shows that during nighttime the wind field is much more horizontally uniform than during daytime as you see in the image. These differences are caused due to micro convective cycles related to uneven heating of the urban surface during the day. Furthermore, the radial wind data could be potentially analyzed to provide the area of wind shear and turbulence. Other interesting observations such as the variation of the vertical profile of the wind from one position to another were studied.

Overall, a sufficient amount of statistical real-world data has been collected and provided by a scanning Doppler Lidar. It demonstrates the necessity to measure accurately and in 3D the wind aloft over cities. The Lidar sensor allows then to support UAS stakeholders for the mitigation of wind hazards in the perspectives of UAV Traffic Management system (UTM).