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- Author or Editor: David Richardson x
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Abstract
This note assesses the improvements in dual-Doppler wind syntheses by employing a multipass Barnes objective analysis in the interpolation of radial velocities to a Cartesian grid, as opposed to a more typical single-pass Barnes objective analysis. Steeper response functions can be obtained by multipass objective analyses; that is, multipass objective analyses are less damping at well-resolved wavelengths (e.g., 8–20Δ, where Δ is the data spacing) than single-pass objective analyses, while still suppressing small-scale (<4Δ) noise. Synthetic dual-Doppler data were generated from a three-dimensional numerical simulation of a supercell thunderstorm in a way that emulates the data collection by two mobile radars. The synthetic radial velocity data from a pair of simulated radars were objectively analyzed to a grid, after which the three-dimensional wind field was retrieved by iteratively computing the horizontal divergence and integrating the anelastic mass continuity equation. Experiments with two passes and three passes of the Barnes filter were performed, in addition to a single-pass objective analysis. Comparison of the analyzed three-dimensional wind fields to the model wind fields suggests that multipass objective analysis of radial velocity data prior to dual-Doppler wind synthesis is probably worth the added computational cost. The improvements in the wind syntheses derived from multipass objective analyses are even more apparent for higher-order fields such as vorticity and divergence, and for trajectory calculations and pressure/buoyancy retrievals.
Abstract
This note assesses the improvements in dual-Doppler wind syntheses by employing a multipass Barnes objective analysis in the interpolation of radial velocities to a Cartesian grid, as opposed to a more typical single-pass Barnes objective analysis. Steeper response functions can be obtained by multipass objective analyses; that is, multipass objective analyses are less damping at well-resolved wavelengths (e.g., 8–20Δ, where Δ is the data spacing) than single-pass objective analyses, while still suppressing small-scale (<4Δ) noise. Synthetic dual-Doppler data were generated from a three-dimensional numerical simulation of a supercell thunderstorm in a way that emulates the data collection by two mobile radars. The synthetic radial velocity data from a pair of simulated radars were objectively analyzed to a grid, after which the three-dimensional wind field was retrieved by iteratively computing the horizontal divergence and integrating the anelastic mass continuity equation. Experiments with two passes and three passes of the Barnes filter were performed, in addition to a single-pass objective analysis. Comparison of the analyzed three-dimensional wind fields to the model wind fields suggests that multipass objective analysis of radial velocity data prior to dual-Doppler wind synthesis is probably worth the added computational cost. The improvements in the wind syntheses derived from multipass objective analyses are even more apparent for higher-order fields such as vorticity and divergence, and for trajectory calculations and pressure/buoyancy retrievals.
Bragg Scatter Detection by the WSR-88D. Part I: Algorithm DevelopmentAbstract
Studies have shown that echo returns from clear-air Bragg scatter (CABS) can be used to detect the height of the convective boundary layer and to assess the systematic differential reflectivity (Z DR) bias for a radar site. However, these studies did not use data from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) or data from a large variety of sites. A new algorithm to automatically detect CABS from any operational WSR-88D with dual-polarization capability while excluding contamination from precipitation, biota, and ground clutter is presented here. Visual confirmation and tests related to the sounding parameters’ relative humidity slope, refractivity gradient, and gradient Richardson number are used to assess the algorithm. Results show that automated detection of CABS in operational WSR-88D data gives useful Z DR bias information while omitting the majority of contaminated cases. Such an algorithm holds potential for radar calibration efforts and Bragg scatter studies in general.
Abstract
Studies have shown that echo returns from clear-air Bragg scatter (CABS) can be used to detect the height of the convective boundary layer and to assess the systematic differential reflectivity (Z DR) bias for a radar site. However, these studies did not use data from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) or data from a large variety of sites. A new algorithm to automatically detect CABS from any operational WSR-88D with dual-polarization capability while excluding contamination from precipitation, biota, and ground clutter is presented here. Visual confirmation and tests related to the sounding parameters’ relative humidity slope, refractivity gradient, and gradient Richardson number are used to assess the algorithm. Results show that automated detection of CABS in operational WSR-88D data gives useful Z DR bias information while omitting the majority of contaminated cases. Such an algorithm holds potential for radar calibration efforts and Bragg scatter studies in general.
Abstract
Clear-air Bragg scatter (CABS) is a refractivity gradient return generated by turbulent eddies that operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems can detect. The randomly oriented nature of the eddies results in a differential reflectivity (Z DR) value near 0 dB, and thus CABS can be used as an assessment of Z DR calibration in the absence of excessive contamination from precipitation or biota. An automated algorithm to estimate Z DR bias from CABS was developed by the Radar Operations Center and can be used to assess the calibration quality of the dual-polarized WSR-88D fleet. This technique supplements existing Z DR bias assessment tools, especially the use of other external targets, such as light rain and dry snow.
The estimates of Z DR bias from CABS using a 1700–1900 UTC time window were compared to estimates from the light rain and dry snow methods. Output from the automated CABS algorithm had approximately the same amount of bias reported as the light rain and dry snow estimates (within ±0.1 dB). As the 1700–1900 UTC time window appeared too restrictive, a modified version of the algorithm was tested to detect CABS diurnally on a volume-by-volume basis (continuous monitoring). Continuous monitoring resulted in a two- to fourfold increase in the number of days with CABS detections. Results suggest estimates from CABS are viable for many sites throughout the year and provide an important addition to existing bias estimation techniques.
Abstract
Clear-air Bragg scatter (CABS) is a refractivity gradient return generated by turbulent eddies that operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems can detect. The randomly oriented nature of the eddies results in a differential reflectivity (Z DR) value near 0 dB, and thus CABS can be used as an assessment of Z DR calibration in the absence of excessive contamination from precipitation or biota. An automated algorithm to estimate Z DR bias from CABS was developed by the Radar Operations Center and can be used to assess the calibration quality of the dual-polarized WSR-88D fleet. This technique supplements existing Z DR bias assessment tools, especially the use of other external targets, such as light rain and dry snow.
The estimates of Z DR bias from CABS using a 1700–1900 UTC time window were compared to estimates from the light rain and dry snow methods. Output from the automated CABS algorithm had approximately the same amount of bias reported as the light rain and dry snow estimates (within ±0.1 dB). As the 1700–1900 UTC time window appeared too restrictive, a modified version of the algorithm was tested to detect CABS diurnally on a volume-by-volume basis (continuous monitoring). Continuous monitoring resulted in a two- to fourfold increase in the number of days with CABS detections. Results suggest estimates from CABS are viable for many sites throughout the year and provide an important addition to existing bias estimation techniques.
