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Abstract:
Airborne eddy covariance measurements can bridge the gap between local (tower-based) and regional (satellite/inversion-derived) flux data, as they provide information about the spatial distribution of turbulent fluxes for larger regions. Here, we introduce an airborne eddy covariance measurement platform based on an ASK-16 touring motor glider (TMG; also referred to as a power glider, hereafter referred to as motorized glider), which is equipped to measure the three-dimensional (3D) wind vector, and atmospheric conditions, and we derive airborne turbulent fluxes for the use of measurement campaigns over European landscapes. This study describes the measurement setup of the platform and explains the workflows that were used to calculate and calibrate the 3D wind vector, turbulent fluxes, and their associated source areas. The glider is equipped with an 858 AJ Rosemount five-hole probe, a Picarro G2311-f gas analyzer, a Novatel FlexPak G2-V2 GNSS–INS system, Vaisala temperature and humidity sensors (HMT311), and an OMEGA CHAL-003 thermocouple temperature sensor. Measurement data are processed with PyWingpod (Python) and eddy4R (R) software packages to calculate wind vectors and turbulent fluxes and assign footprints to the calculated fluxes. To evaluate the quality of the obtained fluxes, different quality assessments have been performed, including the determination of detection limits, spectral analysis, stationarity tests, the analysis of integral turbulence characteristics, and measurement noise and error evaluation. The uncertainty of w is between 0.15 and 0.27 m s−1 (median = 0.23 m s−1), and the uncertainty of u and v ranges between 0.16 and 0.55 m s−1 (median = 0.25 m s−1). Analysis of exemplary flux data from flight transects indicates that the platform is capable of producing spatially highly resolved turbulent fluxes over heterogeneous landscapes. Overall, results from our analysis suggest that the ASK-16 airborne platform can measure turbulent fluxes with a similar quality to earlier established high-quality platforms.
