Browsing by Subject "LLWAS"

Low-level wind shear is a significant aviation hazard. A sudden reduction in the headwind along an aircraft flight path can induce a loss of lift, from which an aircraft may not be able to recover when it is close to the ground. Airports therefore use low-level wind shear alert systems to monitor wind velocities within the airport terminal area and alert of any detected hazardous wind shear. There exist three ground-based sensor systems capable of independently observing low-level wind shear: a Doppler weather radar-based, a Doppler wind lidar-based, and an anemometer-based system. However, as no single sensor system is capable of all-weather wind shear observations, multiple alert systems are used simultaneously, and observations from each system are integrated to produce one set of integrated wind shear alerts. Algorithms for integrating Doppler weather radar and anemometer wind shear observations were originally developed in the early 1990s. However, the addition of the Doppler wind lidar-based alert system in more recent years warrants updates to the existing radar/anemometer integration algorithms. This thesis presents four different replacement candidates for the original radar/anemometer integration algorithms. A grid-based integration approach, where observations from different sensor systems are mapped onto a common grid and integrated, is found to best accommodate central integration considerations, and is recommended as the replacement to the original radar/anemometer algorithms in operational use. The grid-based approach is discussed in further detail, and a first possible implementation of the algorithm is presented. In addition, ways of validating the algorithm and adopting it for operational use are outlined.