Improved Detection of Severe Storms Using Experimental Fine-Resolution WSR-88D Measurements

Abstract

Doppler velocity and reflectivity measurements from Weather Surveillance Radar-1988 Doppler (WSR-88D) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0°and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory's test bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5°-azimuthal spacing and 0.25-km-range spacing, resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fineresolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.

Impact of increased spatio-temporal radar data resolution on forecaster wind assessments

“…The increase in mean wind speed assessments, for forecasters using both NEXRAD and CASA data sources, lends support to work by Brown and Wood [6] who predict that increased spatial sampling results in higher radial velocity data points. These higher values in the CASA data were visible in the display and observable by the forecasters resulting in wind speed assessments higher than with only NEXRAD data.…”

“…While they have the potential to improve the weather hazard assessment and warning process, their exact impacts should be quantified in order to influence training, decision support tool design, normative decision making processes and policy. With respect to resolution, for example, Brown and Wood [6] indicate that radars with greater spatial resolution will report radial wind velocities with greater (absolute) magnitudes and will therefore depict severe storm signatures more clearly than their lower resolution counterparts. These sampling changes can lead to higher forecaster wind speed assessments and differences in the number of wind-related warnings.…”

Tornado Damage Estimation Using Polarimetric Radar

“…The random orientations, irregular shapes, and wide range of dielectric constants and sizes of lofted tornadic debris produce a unique polarimetric signature called the tornadic debris signature (TDS; Ryzhkov et al 2002Ryzhkov et al , 2005. These scattering characteristics produce a distinct TDS (Ryzhkov et al 2002(Ryzhkov et al , 2005Bluestein et al 2007; Kumjian and Ryzhkov 2008;Snyder et al 2010;Palmer et al 2011;Bodine et al 2011;Schwarz and Burgess 2011;Bunkers and Baxter 2011) characterized by high horizontal radar reflectivity factor (Z HH ), low differential reflectivity (Z DR ), and very low copolar cross-correlation coefficient (r HV ) values, which are typically collocated with the tornadic vortex signature (TVS; Brown et al 1978).…”

The Impact of Signal Processing on the Range-Weighting Function for Weather Radars

“…For weather radars, distributed meteorological scatterers are the targets of interest, but the range resolution is still important for observing finescale phenomena, such as tornado vortices. For example, Brown et al (2005) showed that many signatures (e.g., gust fronts, hook echoes, bounded weak echo regions) could be identified at farther ranges by using meteorological data with finer range and angular resolution.…”