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Description

This data set contains in-situ airborne measurements of atmospheric parameters by unmanned aircraft system (UAS) of type fixed-wing conducted with the multi-purpose airborne sensor carrier "MASC-3" (Rautenberg et al. 2019b, DOI:10.3390/s19102292). The UAS recorded in-situ meteorological parameters of the three-dimensional wind vector, temperature and humidity in high temporal resolution with a sampling rate of 100 Hz. For measuring the three-dimensional wind vector MASC-3 uses a five-hole probe (Rautenberg et al. 2019a, DOI:10.3390/atmos10030124, Wildmann et al. 2014c, DOI:10.5194/amt-7-1027-2014), for temperature a fine wire platinum resistance thermometer (Wildmann et al. 2013, DOI:10.5194/amt-6-2101-2013) and for positional measurements an INS with a GPS sensor.

The data was obtained at the boundary layer-measurement site Falkenberg during two intensive observational periods (IOP), 07 July - 31 July 2020 and 06 June - 02 July 2021, in the framework of the VALUAS project. The project is funded by the German Meteorological Service (DWD) to validate Doppler wind lidar measurements. The measurements in 2021 took place in parallel to the Field Experiment on submesoscale spatio-temporal variability in Lindenberg (FESSTVAL) campaign.

The overall atmospheric conditions during the campaign were typical summer-time atmospheric boundary layers with strong convection. The overall duration of a flight is 1 – 1.5 h in an altitude band of 90 m - 500 m above ground. Each measurement flight of the presented data set comprises flight sections, which are straight and leveled (called legs hereafter), with a length of approx. 2.5 km.

The data has been processed by the Environmental Physics group at the University of Tübingen. The data set contains 53 flights in the NetCDF format which is provided here. It contains leg-averaged data for each flight (median values for the variables time, latitude, longitude, u_component_of_wind, v_component_of_wind and w_component_of_wind; arithmetic mean values for all others).

Limitations: All flights have been quality controlled and filtered for systematic errors. The uncertainties of the measurement principle are described in detail in van den Kroonenberg et al. (2008, DOI:10.1175/2008JTECHA1114.1) and the uncertainty of absolute wind measurement was validated to below 0.4 m/s.

Only straight and level flight sections (legs) are used during post-processing. The average (mean or median) values and standard deviations are calculated for each variable, resulting in the data set.

Flights took place only in good weather conditions (visual contact with the aircaft, no flying in rain, thunderstorms, above clouds or at night). The maximum measurable wind speed is approx. 12 - 15 m/s. The MASC-3 can resolve turbulence down to an eddy size of about 1 m (Rautenberg et al. 2019b).

The data could be used for validation with different remote sensing instruments, which measure the according quantity at certain altitudes. Another possible usage could be the comparison with numerical weather models.

Don't hesitate to get in touch with the authors of the data if there are further questions.

• Multipurpose Airborne Sensor Carrier, Typ 3
• Location: Latitude 52.16456 - 52.17297 °N, Longitude 14.12-14.1235 °E, Falkenberg, Germany
• File format: NETCDF4
• Time period
  Start: 2020-07-07
  End: 2021-07-02
• Standard: SAMD v2.2, https://doi.org/10.25592/uhhfdm.9902
• Project: FESSTVAL
• Funding: The project is funded by the German Meteorological Service (DWD).
• Provenance and History: The data has been processed by the Environmental Physics group at the University of Tübingen. All meteorological equations are based on the Python package “PARMESAN” (https://tue-umphy.gitlab.io/software/parmesan/)
• References:
  Rautenberg A., Allgeier J., Jung S., and Bange J., 2019a: 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. Atmosphere, 10, 124.
  Rautenberg A., Schön M., zum Berge K., Mauz M., Manz P., Platis A., van Kesteren B., Suomi I., Kral S.T., and Bange J., 2019b: The Multi-Purpose Airborne Sensor Carrier MASC-3 for Wind and Turbulence Measurements in the Atmospheric Boundary Layer. Sensors, 19, 2292.
  van den Kroonenberg, A., Martin, T., Buschmann, M., Bange, J. and Vörsmann, P., 2008: Measuring the wind vector using the autonomous mini aerial vehicle M²AV. Journal of Atmospheric and Oceanic Technology, 25(11), 1969-1982.
  Wildmann N., Hofsäß M., Weimer F., Joos A., and Bange J., 2014a: MASC - A small Remotely Piloted Aircraft (RPA) for Wind Energy Research. Advances in Science and Research, 11, 55–61.
  Wildmann N., Kaufmann F., and Bange J., 2014b: An inverse-modelling approach for frequency response correction of capacitive humidity sensors in ABL research with small remotely piloted aircraft (RPA). Atmos. Meas. Tech., 7, 3059–3069.
  Wildmann N., Ravi S., and Bange J., 2014c: Towards Higher Accuracy and Better Frequency Re- sponse with Standard Multi-Hole Probes in Turbulence Measurement with Remotely Piloted Air- craft (RPA). Atmos. Meas. Tech., 7, 1027–1041.
  Wildmann N., Mauz M., and Bange J., 2013: Two Fast Temperature Sensors for Probing of the Atmospheric Boundary Layer Using Small Remotely Piloted Aircraft (RPA). Atmos. Meas. Tech., 6, 2101–2113.

University of Tübingen

andreas.platis (at) uni-tuebingen.de

This data is subject to the FESSTVaL data policy to be found at https://doi.org/10.25592/uhhfdm.9890  and in the SAMD Observation Data Product Standard https://doi.org/10.25592/uhhfdm.9902 .