Abstract. In this study, a fleet of quadrotor unmanned aerial vehicles (UAVs) is presented as a system to measure the spatial distribution of atmospheric boundary layer flow. The big advantage of this approach is that multiple and flexible measurement points in space can be sampled synchronously. The algorithm to obtain horizontal wind speed and direction is designed for hovering flight phases and is based on the principle of aerodynamic drag and the related quadrotor dynamics. During the FESST@MOL campaign at the boundary layer field site (Grenzschichtmessfeld, GM) Falkenberg of the Lindenberg Meteorological Observatory – Richard Assmann Observatory (MOL-RAO), 76 calibration and validation flights were performed. The 99 m tower equipped with cup and sonic anemometers at the site is used as the reference for the calibration of the wind measurements. The validation with an independent dataset against the tower anemometers reveals that an average accuracy of σrms<0.3 m s−1 for the wind speed and σrms,ψ<8∘ for the wind direction was achieved. Furthermore, we compare the spatial distribution of wind measurements with the fleet of quadrotors to the tower vertical profiles and Doppler wind lidar scans. We show that the observed shear in the vertical profiles matches well with the tower and the fluctuations on short timescales agree between the systems. Flow structures that appear in the time series of a line-of-sight measurement and a two-dimensional vertical scan of the lidar can be observed with the fleet of quadrotors and are even sampled with a higher resolution than the deployed lidar can provide.

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 the typical heights of these masts, 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 uncrewed aircraft systems (UAS). To achieve a good accuracy in both average and fluctuating parts of the wind components, calibrated motor thrusts 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.

The understanding of micro-scale flow in the atmospheric boundary layer is one major challenge in wind energy research. Besides the broad possibilities of numerical simulations, experimental data are necessary for tests of the flow conditions within a wind farm under real conditions. In wind energy and atmospheric science, a variety of measurement devices exist for measuring the wind speed. We propose a measurement system that enables completely flexible simultaneous wind measurements using a fleet of multirotor unmanned aircraft systems (UAS). This approach is validated through a two-week measurement campaign at the boundary layer field site Falkenberg of the German National Meteorological Service (DWD). The wind speed is calculated from UAS motions in hover state without additional wind sensors. The measurements are calibrated and validated against sonic anemometers mounted at a 99 m mast. The capability of highly accurate spatial distributed wind measurement with an improved wind algorithm is proven by a root mean square error (RMSE) of 0.25 ms−1 for the horizontal wind speed and < 5° for the wind direction. Further, turbulence measurements are presented showing valid results up to a frequency of 2 Hz in high turbulence conditions. Additionally, spatially horizontal distributed measurements with multiple UAS are examined in a case study of a gust front event.

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.

The spatial structures of turbulent flow in the atmospheric boundary layer (ABL) are complex and diverse. Multi-point spatial correlation measurements can help improve our understanding of these structures and their statistics. In this context, we investigate Taylor’s hypothesis and the statistics of spatial structures on the microscale. For the first time, simultaneous horizontally distributed wind measurements with a fleet of 20 quadrotor UAS (unmanned aerial systems) are realized. The measurements were taken at different heights and under different atmospheric conditions at the boundary layer field site in Falkenberg of the German Meteorological Service (DWD). A horizontal flight pattern has been specifically developed, consisting of measurements distributed along and lateral to the mean flow direction with separation distances of $$5\ldots 205$$ 5 … 205  m. The validity of Taylor’s hypothesis is studied by examining the cross-correlations of longitudinally distributed UAS and comparing them with the autocorrelations of single UAS. To assess the similarity of flow structures on different scales, the lateral and longitudinal coherence of the streamwise velocity component is examined. Two modeling approaches for the decay of coherence are compared. The experimental results are in good agreement with the model approaches for neutral atmospheric conditions, whereas in stable and convective ABL, the exponential approaches are not unconditionally valid. The validation results and the agreement with the literature on coherence in the ABL underline the potential of the UAS fleet for the purpose of spatial turbulence measurements.