Improving NEXRAD Velocity Retrievals Using Multi-PRT Scans with Regression Processing

A fundamental data quality issue for pulsed Doppler radars is range-velocity ambiguity, especially at low elevation angles where weather echoes out to greater than 400km in range need to be detected for effective long-range weather surveillance while also retrieving unambiguous radial velocities of around 30ms −1 . The United States National Weather Service (US NWS) Next Generation Weather Radars (NEXRADs) mitigate the range-velocity ambiguities by employing a so called “split cut” scan whereby the atmosphere is interrogated twice at the same low elevation angle: once with a surveillance scan and once with a Doppler scan. Due to range overlays in the Doppler scan, the SZ(8/64) systematic phase coding technique is used but frequently velocities still cannot be resolved, which results in velocity voids (referred to as “Purple Haze”). There are two new techniques to recover data in the velocity void regions: 1) Doppler Velocity Recovery and Dealiasing (VRAD) and SZ(8/64) regression processing. These two algorithms are combined here for the first time for enhanced Doppler velocity recovery and it is shown that this combination delivers superior velocity estimates as compared to either algorithm individually.