On the Discrepancy in Simultaneous Observations of the Structure Parameter of Temperature Using Scintillometers and Unmanned Aircraft

Abstract

We elaborate on the preliminary results presented in Beyrich et al. (in BoundaryLayer Meteorol 144:83-112, 2012), who compared the structure parameter of temperature (C 2 T ) obtained with the unmanned meteorological mini aerial vehicle (M 2 AV) versus C 2 T obtained with two large-aperture scintillometers (LASs) for a limited dataset from one single experiment (LITFASS-2009). They found that C 2 T obtained from the M 2 AV data is significantly larger than that obtained from the LAS data. We investigate if similar differences can be found for the flights on the other six days during LITFASS-2009 and LITFASS-2010, and whether these differences can be reduced or explained through a more elaborate processing of both the LAS data and the M 2 AV data. This processing includes different corrections and measures to reduce the differences between the spatial and temporal averaging of the datasets. We conclude that the differences reported in Beyrich et al. can be found for other days as well. For the LAS-derived values the additional processing steps that have the largest effect are the saturation correction and the humidity correction. For the M 2 AV-derived values the most important step is the application of the scintillometer path-weighting function. Using the true air speed of the M 2 AV to convert from a temporal to a spatial structure function rather than the ground speed (as in Beyrich et al.) does not change the mean discrepancy, but it does affect C 2 T values for individual flights. M 2 AV data depends on the fact that the underlying temperature dataset combines spatial and temporal sampling, we used large-eddy simulation data to analyze C 2 T from virtual flights with different mean ground speeds. This analysis shows that C 2 T does only slightly depends on the true air speed when averaged over many flights.

Proof of concept for turbulence measurements with the RPAS SUMO during the BLLAST campaign

“…However, these operations are, by nature, logistically demanding and expensive. The rapid development of remotely piloted aircraft systems (RPASs) during the last decade has provided new airborne sensor platforms for ABL research (Elston et al, 2015), with several of them having proven their capability for turbulence investigations (e.g., Thomas et al, 2012;Reineman et al, 2013;Martin et al, 2011;van den Kroonenberg et al, 2012;Braam et al, 2016;Wildmann et al, 2014Wildmann et al, , 2015. The continuous miniaturization of electronic components and sensors, both for measurement of meteorological parameters and the required attitude control of the aircraft's autopilot, now also provides the required capability for a micro-RPAS, with a take-off weight below 1 kg (Mansour et al, 2011;Reuder et al, 2012).…”

Calibration Procedure and Accuracy of Wind and Turbulence Measurements with Five-Hole Probes on Fixed-Wing Unmanned Aircraft in the Atmospheric Boundary Layer and Wind Turbine Wakes

“…Furthermore, this study investigates the influence of the calibration of the probe, namely the conversion of the pressure readings to flow angles and magnitude, on turbulence measurements. In the literature a similar question was posed by Martin and Bange [31] and Braam et al [32] who highlighted two important issues. Firstly, airspeed variations cause an uneven sampling of turbulent structures due to the acceleration and deceleration of the UAS, resulting from non-zero vertical wind and gusts.…”

“…Secondly, when compared to other measurement systems such as a scintillometer or other ground-based measurements, path-weighting functions must be considered to account for differences between the spatial and the temporal resolution of the measurement of a quantity. The uncertainties of the wind vector measurement and its calibration actually precede those investigated by Martin and Bange [31] and Braam et al [32]. The influence of the calibration of the probe on turbulence measurements is difficult to investigate in the wind tunnel, and impossible for natural atmospheric turbulence.…”

Wind Energy Instrumentation Atlas

“…Typically, these systems can provide measurements of wind speed, temperature, pressure, and some humidity variables. Depending on the rate of the probe mounted on the remotely piloted aircraft system, many of these platforms have documented capabilities for measuring atmospheric turbulence parameters (Båserud et al 2016), usually a temperature structure parameter (Thomas et al 2012;Kroonenberg et al 2012;Reineman et al 2013;Wildmann et al 2013Wildmann et al , 2014Wildmann et al , 2015Braam et al 2016). These systems have been used to measure the wind speed deficits in wind turbine wakes (Kocer et al 2012;Båserud et al 2014).…”