ERAD 2010 - THE SIXTH EUROPEAN CONFERENCE ON RADAR IN METEOROLOGY AND HYDROLOGY Wind Turbine Clutter Detection in Scanning Weather Radar Tasks

Wind Turbine Clutter (WTC) mitigation is a challenging issue that worldwide weather services are facing at the moment. The use of wind farms to generate electricity is growing increasingly due to the importance of being a renewable energy source. Wind farm installations relatively near to weather radars may block the normal propagation of the radar signals and cause reflectivity clutter returns. Due to the motion of blades, with tip velocities near 90 m s-1, the standard clutter mitigation techniques fail to mitigate the effects of wind farms on radar products. Thus, this clutter and interference cause false estimates of rain accumulation and rain Doppler velocity. Several studies addressing the problem in C-band and S-band Doppler weather radars have been published to date, with encouraging results. However, most of them are oriented to WTC lessening in spotlight operation mode, that is, with the antenna dish stationary. In operational radars these techniques are useless, as the radar antenna is constantly rotating in a surveillance operation mode. Some studies propose interpolation in order to remove WTC from reflectivity and velocity PPIs, but a previous knowledge about the location of wind turbines is required. A fixed wind turbine clutter map has two main disadvantages. First, wind farms can occupy more than 50 km long where inter-turbine distances can be smaller or not than the radar range resolution. This can cause an important lost of valuable weather information. Second, wind turbines are not always running. The blades only move when the velocity of the wind is appropriate for energy production. Then, on-the-go detection is highly more efficient for weather data accuracy. In this work a holistic approach to wind turbine clutter detection is performed. The detection is based on feature extraction. Although the technique is employed in surveillance operation mode, the experience with spotlight data will be used, as it provides the information about the behavior of WTC in time. Then, several parameters will be used as indicators of WTC presence in radar data. Both simulated and recorded radar data from clutter and weather will be used for this purpose.