Articles | Volume 8, issue 5
https://doi.org/10.5194/amt-8-2183-2015
https://doi.org/10.5194/amt-8-2183-2015
Research article
 | 
27 May 2015
Research article |  | 27 May 2015

Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services

I. Angulo, O. Grande, D. Jenn, D. Guerra, and D. de la Vega

Abstract. The World Meteorological Organization (WMO) has repeatedly expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. Current signal processing techniques to mitigate wind turbine clutter (WTC) are scarce, so the most practical approach to this issue is the assessment of the potential interference from a wind farm before it is installed. To do so, and in order to obtain a WTC reflectivity model, it is crucial to estimate the radar cross section (RCS) of the wind turbines to be built, which represents the power percentage of the radar signal that is backscattered to the radar receiver.

For the proposed model, a representative scenario has been chosen in which both the weather radar and the wind farm are placed on clear areas; i.e., wind turbines are supposed to be illuminated only by the lowest elevation angles of the radar beam.

This paper first characterizes the RCS of wind turbines in the weather radar frequency bands by means of computer simulations based on the physical optics theory and then proposes a simplified model to estimate wind turbine RCS values. This model is of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation.

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Short summary
The World Meteorological Organization has expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. This paper proposes a wind turbine clutter reflectivity model, which aims at being of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation. First the radar cross section (RCS) of wind turbines is characterized by means of computer simulations and then a simplified RCS model is proposed.