High-resolution 3D turbulence measurements with different quadcopter uncrewed aerial systems: verification and validation for single- and multi-vehicle measurements

Abstract. The SWUF-3D drone fleet is used to obtain in situ measurements of three-dimensional turbulence in the atmospheric boundary layer (ABL). This requires high measurement accuracy and a quantification of measurement uncertainties. Hardware modifications can extend flight duration but may also alter flight behavior. Because wind estimates are derived from forces inferred from avionics data, the open question is how far turbulence measurements become affected by such modifications. We therefore quantify hardware-dependent resolvable frequency ranges and uncertainties for single-point and multi-point turbulence statistics. Since we perform simultaneous, spatially distributed fleet measurements with the drones, we also assess the capabilities and limitations of such multi-location measurements. To determine the uncertainties, we perform verification under laboratory conditions and validation under real-world conditions against reference sensors using different hardware configurations. Using the main hardware configuration of the drones, we perform fleet measurements of the 3D wind vector with spatial separations in all directions to evaluate measurements for the analysis of velocity increments and coherence. The dataset comprises 42 wind tunnel time series of approximately 10 min and 155 field flight time series with an average duration of more than 10 min. We identify hardware-dependent maximum resolvable frequencies of approximately 2.5–5 Hz, with the main configuration capable of resolving frequencies up to 3.5 Hz. Variance estimates are comparable across configurations, with a root mean square error of ≤ 0.21 m² s⁻². Within the resolvable frequency ranges, the probability density functions (PDFs) of ve- locity increments agree well with those derived from reference sensors down to a minimum resolved spatial lag of 2 m. At very short lags and low wind speeds, extreme deviations from Gaussianity (i. e. intermittency) are not fully captured, which leads to an underestimation of the kurtosis of the velocity increment PDFs. Fleet measurements resolve spatial velocity increments and coherence for the 3D wind components in all three separation directions at distances of 50–100 m. All drone configurations resolve the frequency range over which coherence is observed. The SWUF-3D fleet can reliably measure turbulence statistics within hardware-dependent small-scale limits, which mainly affect the quantification of intermittency at small scales. The fleet measurements enable spatial two-point analyses of turbulence in all directions. The quantified effects and uncertainties provide a basis for future ABL turbulence studies, for example in complex terrain and wind turbine wakes.