Articles | Volume 14, issue 5
Atmos. Meas. Tech., 14, 3541–3560, 2021
https://doi.org/10.5194/amt-14-3541-2021
Atmos. Meas. Tech., 14, 3541–3560, 2021
https://doi.org/10.5194/amt-14-3541-2021

Research article 18 May 2021

Research article | 18 May 2021

Insights into wind turbine reflectivity and radar cross-section (RCS) and their variability using X-band weather radar observations

Martin Lainer et al.

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Cited articles

Angulo, I., de la Vega, D., Cascon, I., Canizo, J., Wu, Y., Guerra, D., and Angueira, P.: Impact analysis of wind farms on telecommunication services, Renewable and Sustainable Energy Reviews, 32, 84–99, https://doi.org/10.1016/j.rser.2013.12.055, 2014. a
Angulo, I., Grande, O., Jenn, D., Guerra, D., and de la Vega, D.: Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services, Atmos. Meas. Tech., 8, 2183–2193, https://doi.org/10.5194/amt-8-2183-2015, 2015. a, b, c
Battan, L. J.: Radar observation of the atmosphere, University of Chicago press, Chicago, USA, 324 pp., https://doi.org/10.1002/qj.49709942229, 1973. a
Bredemeyer, J., Schubert, K., Werner, J., Schrader, T., and Mihalachi, M.: Comparison of principles for measuring the reflectivity values from wind turbines, in: 2019 20th International Radar Symposium (IRS), pp. 1–10, https://doi.org/10.23919/IRS.2019.8768171, 2019. a
Bringi, V. N. and Chandrasekar, V.: Polarimetric Doppler Weather Radar: Principles and Applications, Cambridge University Press, Cambridge, UK, 636 pp., https://doi.org/10.1017/CBO9780511541094, 2001. a
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Short summary
We show results from two unique measurement campaigns aimed at better understanding effects of large wind turbines on radar returns by deploying a mobile X-band weather radar system in the proximity of a small wind park. Measurements were taken in 24/7 operation with dedicated scan strategies to retrieve the variability and most extreme values of reflectivity and radar cross-section of the wind turbines. The findings are useful for wind turbine interference mitigation measures in radar systems.