The use of spectral processing to improve radar spectral moments

The data quality of the spectral (Doppler) moments (power, radial velocity and spectrum width) continues to be an on-going problem for the NEXRAD radar products. Data contaminants that are significant include so-called hard targets like road clutter, wind farms, birds, and airplanes. However, the Open RDA system deployed on the WSR-88D fleet allows much more flexibility for processing the so-called level 1, I&Q data. In particular, spectral-domain processing has become a viable method for calculating the moments, thus opening the door to advanced techniques, such as the NEXRAD Spectral Processing Algorithm (NSPA), described in this paper, that can improve moment estimates by isolating weather signals from the isolated contaminants listed above.

NSPA, like its predecessors NCAR Improved Moment Algorithm (NIMA) and NCAR Enhanced Spectra Processing Algorithm (NESPA), use spectral information along a radial, to determine which spectral features are weather rather than contaminants. When contaminants are identified, the algorithm attempts to calculate the spectral moments of only the weather, excluding the contaminants. In this paper, the NSPA algorithm will be described and its performance evaluated.