Although traditional signal-processing methods are designed to remove unwanted non-atmospheric signals in the Doppler spectra recorded by wind profilers, there are still contaminated spectral signals that produce erroneous moment-level data from which the winds are estimated. Quality control algorithms are implemented to identify and remove these erroneous data that would otherwise render inaccurate meteorological measurements and interpretation. The NOAA Environmental Technology Laboratory currently uses a continuity method to identify and preserve only those measurements that exhibit consistency in height and time. This continuity method has produced high quality results under a variety of meteorological conditions over many months of observations. Nevertheless, certain types of contamination, such as migrating birds, can persist over time with consistent Doppler shift over many heights. In these situations, the continuity method can produce undesirable results.

In this paper we report the results of applying new and established quality control methods to the wind profiler datasets collected during TEXAQS-2000. Bird contamination is identified by applying thresholds to Doppler velocity, radar reflectivity, and Doppler spectral width. After removing the bird-contaminated winds, the remaining wind data are subjected to quality control via the continuity method. The small percentage of contaminated winds and measurement noise surviving these first two levels of quality control are removed by visual inspection.