The present study describes methods to reduce the uncertainty of velocity-azimuth display (VAD) wind and deformation retrievals from downward-pointing, conically-scanning, airborne Doppler radars. These retrievals have important applications in data assimilation and real-time data processing. Several error sources for VAD retrievals are considered here, including: violations to the underlying wind field assumptions, Doppler velocity noise, data gaps, temporal variability, and the spatial weighting function of the VAD retrieval. Specific to airborne VAD retrievals, we also consider errors produced due to the radar scans occurring while the instrument platform is in motion.

While VAD retrievals are typically performed using data from a single antenna revolution, other strategies for selecting data can be used to reduce retrieval errors. Four such data selection strategies for airborne VAD retrievals are evaluated here with respect to their effects on the errors. These methods are evaluated using the Second Hurricane Nature Run numerical simulation, analytic wind fields, and observed Doppler radar radial velocities. The proposed methods are shown to reduce the median absolute error of the VAD wind retrievals, especially in the vicinity of deep convection embedded in stratiform precipitation. The median absolute error due to wind field assumption violations for the along-track (across-track) wind is reduced from 0.36 m s−1 (0.35 m s−1) to 0.08 m s−1 (0.24 m s−1). Although the study focuses on Doppler radars, the results are equally applicable to conically-scanning Doppler lidars as well.

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