Improvements to CopterSonde Wind Algorithms

Weather-sensing UAS continue to advance to higher levels of accuracy and autonomy, but wind speed estimation continues to be a challenge. The CopterSonde UAS has been shown to provide accurate wind speed information when compared to Doppler wind lidar, but uncertainty is larger in the tails of the distribution (i.e. very low winds and very high winds). Due to the targeted operations envelope of the CopterSonde, some of the assumptions used in the current wind speed algorithm based on the Rayleigh drag equation are not sufficient to capture precise measurements across the full range of desired wind speed conditions. Additionally, since the CopterSonde has been largely designed to meet requirements for next-generation observing networks, uncertainty in the wind speed algorithms used to create the observations, as well as the uncertainty in the observations themselves, need to be considered for the creation of analysis products and data assimilation applications.

Since 2018, the CopterSonde has flown in a large range of locations and conditions without significant changes to its design and configuration. Many of these observations were collected while co-located with a Doppler wind lidar that is part of the OU/NSSL Collaborative Lower Atmospheric Mobile Profiling System. This provides a large validation dataset to determine the accuracy of more complex wind estimation algorithms in a wide range of conditions. This study revists the CopterSonde wind speed algorithm and considers both the observation uncertainties as well as the model uncertainty over the full range of conditions in which the CopterSonde is expected to fly.