A new method for detection of microbursts via point observation methods and field measurement for validation study with Doppler weather radar.

Abstract

Wind shear (WS) phenomena are critical in many applications, especially in aviation, wind energy and urban planning. Microburst (MB) detection is important for ensuring safety during aircraft landing/takeoff, eliminating imbalances caused by shear from wind turbines, and for static calculations in urban planning. In this study, microburst events were detected using meteorological data. A new algorithm was applied to Light Detection and Ranging (LIDAR) data and 3 different cup anemometer data were available for 1-min and 10-min measurement periods. First, MB condition parameters using power law and basic wind shear analysis based on the scope of international criteria were defined, then checked in the algorithm. All results are compared with each other on behalf of detected microburst count, day, minute, and period. Detected events were matched at 66% and 85%, respectively, 10-min, and 1-min intervals. Validation studies were carried out for the same location by analysing the reflection values, reflection image and velocity product of the Doppler Weather Radar (DWR) with classical methods. However, when the radar results compared with 1- and 10-minute data sets, it was shown that 80% and 75% of daily events matched. The algorithm provided good continuity across LIDAR, different cup anemometers, and the weather radar. Consequently, the new algorithm will provide a great economic advantage.