WINDMAP: Wind Intelligent Navigation Data and Models for Aviation Planning

WINDMAP (Wind Intelligent Navigation Data and Models for Aviation Planning) is a NASA University Leadership Initiative with participants from Oklahoma State University, Virginia Tech University, Universities of Kentucky, Nebraska, and Oklahoma, NCAR, and the Choctaw Nation, as well as several industry partners. The project addresses emerging needs in real-time weather forecasting to improve the safety of low altitude aircraft operations through the integration of real-time observations from autonomous systems with numerical weather prediction and flight management and safety systems. In addition to the challenges of traffic congestion and obstacles, critical technology gaps exist for modeling, detecting, and accommodating the dynamic local weather environment and for precision navigation through uncertain weather conditions. The use of small uncrewed aircraft systems (sUAS) as a tool for use in atmospheric observations is well known. However, they will play an increasingly larger role in advanced air mobility (AAM) in the integration of urban air mobility (UAM) solutions as well as unmanned traffic management (UTM) system development and implementation. However, the challenges of urban wind field sensing include high spatial turbulence gradients, high turbulence magnitudes, and degraded position references, all of which complicate the traditional approach. This is particularly true in urban environments where the presence of buildings produce complex, unsteady flow patterns. This paper discusses approaches and field tests the WINDMAP team has utilized over the effort for utilizing UAS to provide real-time data to enable UAM and UTM operations, and the last year of integrated flight campaigns for improving the resolution and accuracy of comprehensive wind and thermodynamic field observation, data assimilation, numerical weather prediction, and system implementation.