Targeted Weather Forecasts for Small Unmanned Aircraft Systems

With the rapid development of small Unmanned Aircraft Systems (sUAS), the FAA predicts that there will be as many as 7 million sUAS flying over the United States by 2020. Safe sUAS operations depend on many factors including reliable communication, collision avoidance, and accurate weather predictions. Weather predictions for sUAS present a particular challenge because the important spatial and temporal forecasting scales are much finer than those of current weather forecasts. Most sUAS operations have less than a 1 hour duration and span a distance of ~ 1 km. The highest resolution forecast that is currently available over the United States is the High Resolution Rapid Refresh (HRRR) weather model. This is a 3 km resolution hourly forecast run by NOAA. Weather hazards not captured by the HRRR can be significant and potentially dangerous to sUAS operations. The present work couples high resolution forecasting with lower order aircraft models in order to develop a tool for sUAS operators to make weather-aware decisions about flight plans. Weather forecasts are calculated using the Weather Research and Forecasting Model (WRF) produced by NCAR and NOAA. The WRF simulations are initialized with the HRRR data. The targeted forecasts performed to date have a spatial resolution of 1 km and a temporal resolution of 15 minutes. The horizontal grid is 74 km west-east by 61 km south-north. The simulations are performed in parallel on a six core desktop computer. This project is focused on simulations that require relatively low computing power in order to make this technology available to a wide range of sUAS operators. The figure shows the improved weather detail that can be provided to sUAS operators when using the high fidelity WRF simulations compared with the currently available HRRR data. The output data from the WRF simulations can be used to check any number of possible aircraft limitations including maximum wind speed, extreme temperatures, and precipitation. sUAS operators can obtain vehicle specific weather advisories when the improved weather forecast is compared against flight plans and aircraft limitations. This work has demonstrated the possibility of performing targeted high resolution forecasts for sUAS operations. In addition to providing weather data for safe sUAS operations, this project also provides a great opportunity for improving local weather models. Future work will involve comparing on-board sUAS data with these high resolution forecasts in order to check and improve local weather models for better weather forecasting.