Development and Validation of a Custom Stochastic Microscale Wind Model for Urban Air Mobility Applications

Highlights: What are the main findings? A Stochastic Microscale Wind Model (SWM) has been developed and validated to support the operation and certification flight testing of Urban Air Mobility (UAM) aircraft, including drones, RPAs, and piloted VTOL vehicles. SWM can rapidly generate high-resolution, quasi-non-stationary urban wind fields, delivering mid-fidelity performance that bridges the gap between spectral models and CFD-based approaches. What is the implication of the main finding? SWM delivers realistic, low-cost microscale wind simulations using open-source terrain data and standard wind solvers, with straightforward mesoscale integration and a clear pathway toward real-time wind prediction. SWM-generated wind data can support preliminary flight dynamics, performance, control, safety, and operational risk assessments for drones and VTOL aircraft, as well as vertiport siting studies, helping accelerate the development and deployment of UAM. Urban air mobility operations, such as flying Uncrewed Aerial Vehicles (UAVs) and small passenger aircraft in and around cities, will be inherently susceptible to the turbulent wind conditions in urban environments. Therefore, understanding UAM aircraft performance under microscale wind disturbances is critical. Gaining such insight is non-trivial due to the lack of sufficient UAM aircraft operational data and the complexities involved in flight testing UAM aircraft. A viable solution to overcome this hindrance is through simulation-based flight testing, data collection, and performance assessment. To support this effort, the present paper establishes a custom Stochastic microscale Wind Model (SWM) capable of efficiently generating high-resolution, spatio-temporally varying urban wind fields. The SWM is validated against wind tunnel test data, and subsequently, the findings are employed to guide targeted refinements of urban wake simulation. Furthermore, to incorporate realistic atmospheric conditions and demonstrate the ability to generate location-specific wind fields, the SWM is coupled with the mesoscale Weather Research and Forecasting (WRF) model. This integrated approach is demonstrated through a case study focused on a potential vertiport site in Milan, Italy, illustrating its utility for assessing operational area-specific UAM aircraft performance and vertiport emplacement.