Discussion of the impact of data contamination on TDWR algorithm performance
The Federal Aviation Administration (FAA) is currently deploying Terminal Doppler Weather Radars (TDWRs) at key airports in the continental U.S. that experience high volumes of traffic and high frequencies of thunderstorm impact. The TDWR is designed to display the location and intensity of storm cells as well as the location and intensity of wind shear events in the airport vicinity. The TDWR system uses clutter filters and four data quality editing techniques: point target removal, clutter residue editing maps (CREMs), range obscuration editing, and velocity dealiasing in an attempt to reduce base data contamination prior to wind shear algorithm processing. The performance of the wind shear detection algorithms is directly related to the quality of the base data. In particular, failures of the data quality editors can seriously degrade the wind shear detection algorithm's performance. It will be shown that these failures can lead to both undetected and false events. In addition, clutter contamination from nonmeteorological sources such as birds can produce false wind shear signatures in the radar data. This paper will examine the impact of data contamination on algorithm performance at key TDWR sites where base and products data have been collected. The severity of these failures will be discussed, along with possible solutions to the most significant problems.