Towards vertical wind and turbulent flux estimation with multicopter UAS

Abstract

Abstract. Vertical wind velocity and its fluctuations are essential parameters in the Atmospheric Boundary Layer (ABL) to determine turbulent fluxes and scaling parameters for ABL processes. The typical instrument to measure fluxes of momentum and heat in the surface layer are sonic anemometers. Without the infrastructure of meteorological masts and above their typical heights, in-situ point measurements of the three-dimensional wind vector are hardly available. We present a method to obtain the three-dimensional wind vector from avionic data of small multicopter unmanned aerial systems (UAS). To achieve a good accuracy in both, average and fluctuating parts of the wind components, calibrated motor thrust and measured accelerations by the UAS are used. In a validation campaign, in comparison to sonic anemometers on a 99-m mast, accuracies below 0.2 m s-1 are achieved for the mean wind components and below 0.2 m2 s-2 for their variances. The spectra of variances and covariances show good agreement with the sonic anemometer up to 1 Hz temporal resolution. A case study of continuous measurements in a morning transition of a convective boundary layer with five UAS illustrates the potential of such measurements for ABL research.

Analyses of Spatial Correlation and Coherence in ABL flow with a Fleet of UAS

“…In future, the results of the coherence can be compared with theoretical In this study, we only considered the streamwise velocity component, but the component perpendicular to the mean flow is also available and can be analyzed in future. Most recently, we developed new methods to retrieve the vertical wind component as well (Wildmann and Wetz 2022). Using all three wind components the calculation of the complete coherence tensor becomes possible.…”

“…The inertial measurement unit (IMU) measures the UAS attitude and its first and second derivative with a set of sensors including gyroscopes, accelerometers and magnetometers. The sensor data are logged to an SD-Card with a temporal resolution between 1 and 250 Hz depending on the sensor type (see also Wildmann and Wetz 2022). Additionally, a combined temperature and humidity sensor is mounted on each UAS.…”

High resolution wind speed measurements with quadcopter UAS: calibration and verification in a wind tunnel with active grid

“…The wind estimation with the SWUF-3D (Simultaneous Wind measurement with Unmanned Flight Systems in 3D) fleet (Wetz et al, 2021;Wildmann and Wetz, 2022) for determination of turbulence in the ABL is also based on the latter technique. The so far used calibration of the fleet and its validation have been performed in free field measurements up to this point (Wetz and Wildmann, 2022), which always have inherent uncertainties.…”

“…The wind estimation with the SWUF-3D (Simultaneous Wind measurement with Unmanned Flight Systems in 3D) fleet (Wetz et al, 2021;Wildmann and Wetz, 2022) for determination of turbulence in the ABL is also based on the latter technique. The so far used calibration of the fleet and its validation have been performed in free field measurements up to this point (Wetz and Wildmann, 2022), which always have inherent uncertainties. This motivates the first part of this work: the calibration of the coefficients of the extended Rayleigh drag equations of the wind measurement algorithm from Wetz and Wildmann (2022) under laboratory conditions.…”

“…The so far used calibration of the fleet and its validation have been performed in free field measurements up to this point (Wetz and Wildmann, 2022), which always have inherent uncertainties. This motivates the first part of this work: the calibration of the coefficients of the extended Rayleigh drag equations of the wind measurement algorithm from Wetz and Wildmann (2022) under laboratory conditions. The calibration is carried out for mean wind speeds along the main axes (x-and y-direction) of the fixed-body coordinate system of a single UAS.…”