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Abstract Due to differences between air and debris motions, debris centrifuging creates bias in wind estimates based on Doppler velocities and radar wind retrievals in tornadoes. Anomalous radial divergence, azimuthal wind underestimation, and vertical velocity bias associated with debris centrifuging can lead to erroneous interpretations of tornado intensity and structure from radar data. A novel spectral velocity correction technique is developed to reduce bias by identifying rain and debris motion in radar signals using dual-polarization spectral density estimation and fuzzy logic classification. This technique successfully improves Doppler velocity estimates in simulated S-band polarimetric time series data, although debris concentration modulates both the magnitude and correctability of velocity bias. Large bias magnitudes associated with high debris concentrations are the most difficult to fully correct using this technique, especially at low elevation angles and near the center of the tornado. However, the magnitudes of corrections applied are proportional to the original bias magnitudes, suggesting that the technique performs consistently across low and high debris concentrations. Spectral correction results in an overall 84% reduction in bias in simulations. The spectral correction technique is also applied to dual-polarization S-band radar observations of the 20 May 2013 Moore, Oklahoma tornado. Overall increases in Doppler velocity magnitudes, especially at lower elevation angles, imply that spectral correction can successfully reduce centrifuging bias in observed Doppler velocities. 

Abstract The scientific community has expressed interest in the potential of phased array radars (PARs) to observe the atmosphere with finer spatial and temporal scales. Although convergence has occurred between the meteorological and engineering communities, the need exists to increase access of PAR to meteorologists. Here, we facilitate these interdisciplinary efforts in the field of ground-based PARs for atmospheric studies. We cover high-level technical concepts and terminology for PARs as applied to studies of the atmosphere. A historical perspective is provided as context along with an overview of PAR system architectures, technical challenges, and opportunities. Envisioned scan strategies are summarized because they are distinct from traditional mechanically scanned radars and are the most advantageous for high-resolution studies of the atmosphere. Open access to PAR data is emphasized as a mechanism to educate the future generation of atmospheric scientists. Finally, a vision for the future of operational networks, research facilities, and expansion into complementary radar wavelengths is provided. 

Abstract When a tornado lofts debris to the height of the radar beam, a signature known as the tornadic debris signature (TDS) can sometimes be observed on radar. The TDS is a useful signature for operational forecasters because it can confirm the presence of a tornado and provide information about the amount of damage occurring. Since real-time estimates of tornadic intensity do not have a high degree of accuracy, past studies have hypothesized that the TDS could also be an indicator of the strength of a tornado. However, few studies have related the tornadic wind field to TDS characteristics because of the difficulty of obtaining accurate, three-dimensional wind data in tornadoes from radar data. With this in mind, the goals of this study are twofold: 1) to investigate the relationships between polarimetric characteristics of TDSs and the three-dimensional tornadic winds, and 2) to define relationships between polarimetric radar variables and debris characteristics. Simulations are performed using a dual-polarization radar simulator called SimRadar; large-eddy simulations (LESs) of tornadoes; and a single-volume,-matrix-based emulator. Results show that for all simulated debris types increases in horizontal and vertical wind speeds are related to decreases in correlation coefficient and increases in TDS area and height and that, conversely, decreases in horizontal and vertical wind speeds are related to increases in correlation coefficient and decreases in TDS area and height. However, the range of correlation coefficient values varies with debris type, indicating that TDSs that are composed of similar debris types can appear remarkably different on radar in comparison with a TDS with diverse scatterers. Such findings confirm past observational hypotheses and can aid operational forecasters in tornado detection and potentially the categorization of damage severity using radar data.