Articles | Volume 15, issue 18
https://doi.org/10.5194/amt-15-5465-2022
https://doi.org/10.5194/amt-15-5465-2022
Research article
 | 
27 Sep 2022
Research article |  | 27 Sep 2022

Towards vertical wind and turbulent flux estimation with multicopter uncrewed aircraft systems

Norman Wildmann and Tamino Wetz

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Cited articles

Aubinet, M., Vesala, T., and Papale, D.: Eddy Covariance – A Practical Guide to Measurement and Data Analysis, Springer, Dordrecht, ISBN 978-94-007-2351-1, https://doi.org/10.1007/978-94-007-2351-1, 2012. a
Baldocchi, D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, W., Oechel, W., U, K. T. P., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and Wofsy, S.: FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities, B. Am. Meteorol. Soc., 82, 2415–2434, https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2, 2001. a
Bangura, M., Melega, M., Naldi, R., and Mahony, R.: Aerodynamics of rotor blades for quadrotors, arXiv preprint arXiv:1601.00733, p. 42, 2016. a
Fernando, H. J. S., Mann, J., Palma, J. M. L. M., Lundquist, J. K., Barthelmie, R. J., Belo-Pereira, M., Brown, W. O. J., Chow, F. K., Gerz, T., Hocut, C. M., Klein, P. M., Leo, L. S., Matos, J. C., Oncley, S. P., Pryor, S. C., Bariteau, L., Bell, T. M., Bodini, N., Carney, M. B., Courtney, M. S., Creegan, E. D., Dimitrova, R., Gomes, S., Hagen, M., Hyde, J. O., Kigle, S., Krishnamurthy, R., Lopes, J. C., Mazzaro, L., Neher, J. M. T., Menke, R., Murphy, P., Oswald, L., Otarola-Bustos, S., Pattantyus, A. K., Rodrigues, C. V., Schady, A., Sirin, N., Spuler, S., Svensson, E., Tomaszewski, J., Turner, D. D., van Veen, L., Vasiljević, N., Vassallo, D., Voss, S., Wildmann, N., and Wang, Y.: The Perdigão: Peering into Microscale Details of Mountain Winds, B. Am. Meteorol. Soc., 100, 799–819, https://doi.org/10.1175/BAMS-D-17-0227.1, 2019. a
Kaimal, J. C. and Businger, J. A.: A Continuous Wave Sonic Anemometer-Thermometer, J. Appl. Meteorol. Climatol., 2, 156–164, https://doi.org/10.1175/1520-0450(1963)002<0156:ACWSAT>2.0.CO;2, 1963. a
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Short summary
Multicopter uncrewed aerial systems (UAS, also known as drones) are very easy to use systems for collecting data in the lowest part of the atmosphere. Wind and turbulence are parameters that are particularly important for understanding the dynamics in the atmosphere. Only with three-dimensional measurements of the wind can a full understanding can be achieved. In this study, we show how even the vertical wind through the UAS can be measured with good accuracy.