A Novel Technique to Correct Debris Centrifuging Bias in Doppler Velocity Measurements of Tornadoes

Debris centrifuging in tornadoes is known to create bias in Doppler velocities and radar wind retrievals. Anomalous radial divergence, azimuthal wind underestimation, and negative vertical velocity bias associated with debris centrifuging can lead to erroneous interpretations of tornado intensity and structure from radar data. However, physically based methods to correct these errors do not yet exist. A novel technique is developed to correct velocity bias by identifying rain and debris motion in a signal using dual-polarization spectral density estimation and fuzzy logic classification, then filtering debris motion from the signal to obtain a new, corrected velocity estimate. This velocity correction technique is first applied to simulated data from SimRadar, a polarimetric, time-series radar simulator that combines a high-resolution vortex model from large-eddy simulations with debris trajectory and electromagnetic scattering calculations for physically realistic tornadic debris signature studies. Overall, the technique largely improves velocity estimates across all simulations when compared to pre-correction velocities. While debris concentration appears to modulate the degree to which bias can be fully removed, the technique consistently applies larger magnitudes of correction to more-biased velocities without overcorrecting when bias is small, suggesting that spectral velocity correction is most impactful when it is most needed. The technique is also applied to KOUN radar observations from the 20 May 2013 Moore, Oklahoma tornado. Corrected Doppler velocities within the tornado are generally larger in magnitude than the original measured velocities, suggesting that this technique can successfully reduce debris centrifuging errors in radar observations of tornadoes.