Search Results
Abstract
A technique for tracking patterns of radial velocity and reflectivity data obtained with a single-Doppler radar is described. Application of the technique to two different scans of the same spatial region may lead to the extraction of a field of “wind” vectors with both radial and azimuthal components. This is accomplished by displacing, in range and azimuth, small volumes or “boxes” of data from the earlier scan and then correlating them with boxes of equal dimensions from the later scan. The displacements at which correlation coefficients maximize are assumed to be due to the advection of patterns existing at scales up to the “box” dimensions.
Correlation coefficients of radial velocities are shown, for the clear air cases analyzed, to be higher than those of reflectivity [dB(Z)]. “Winds” retrieved by correlating velocities and reflectivities independently are compared with each other and with winds synthesized from dual-Doppler radar data. Winds from radial velocity correlations agree better with the dual-Doppler winds than do winds from reflectivity correlations. Convective rolls spaced ∼5 km apart are revealed in the planetary boundary layer.
Abstract
A technique for tracking patterns of radial velocity and reflectivity data obtained with a single-Doppler radar is described. Application of the technique to two different scans of the same spatial region may lead to the extraction of a field of “wind” vectors with both radial and azimuthal components. This is accomplished by displacing, in range and azimuth, small volumes or “boxes” of data from the earlier scan and then correlating them with boxes of equal dimensions from the later scan. The displacements at which correlation coefficients maximize are assumed to be due to the advection of patterns existing at scales up to the “box” dimensions.
Correlation coefficients of radial velocities are shown, for the clear air cases analyzed, to be higher than those of reflectivity [dB(Z)]. “Winds” retrieved by correlating velocities and reflectivities independently are compared with each other and with winds synthesized from dual-Doppler radar data. Winds from radial velocity correlations agree better with the dual-Doppler winds than do winds from reflectivity correlations. Convective rolls spaced ∼5 km apart are revealed in the planetary boundary layer.
Abstract
Doppler velocity spectra of a combined Rankine model vortex are computed by assuming a Gaussian antenna pattern, various vortex sizes, pulse volume depths, and reflectivity profiles. Both very narrow and very broad antenna beamwidths may produce bimodal spectra. Most often, the theoretically derived spectra exhibit a rapid power decrease for spectral components near maximum velocity which agrees with an experimental observation previously reported.
In spring 1973, NSSL's 10 cm, high-resolution Doppler radar scanned the vicinity of a large tornado that devastated Union City, Okla. Digital radar samples were recorded and Fourier-analyzed to derive power spectra for sample volumes spaced about the vortex location. Power spectra were examined for white noise type signatures that indicated vortex rotation contained within the radar sample volume. Spectra were simulated using radar and tornado cyclone parameters matched to those existing during the observations to determine spectral features for comparison with those recorded by the pulse-Doppler radar. The reflectivity throughout and around the funnel was uniform and spectra compared well. Although the precise vortex center location could not be deduced its position was consistent with tornado position determined from film documentation. In the gates containing vortex signatures spectral standard deviations were consistently maximal.
Abstract
Doppler velocity spectra of a combined Rankine model vortex are computed by assuming a Gaussian antenna pattern, various vortex sizes, pulse volume depths, and reflectivity profiles. Both very narrow and very broad antenna beamwidths may produce bimodal spectra. Most often, the theoretically derived spectra exhibit a rapid power decrease for spectral components near maximum velocity which agrees with an experimental observation previously reported.
In spring 1973, NSSL's 10 cm, high-resolution Doppler radar scanned the vicinity of a large tornado that devastated Union City, Okla. Digital radar samples were recorded and Fourier-analyzed to derive power spectra for sample volumes spaced about the vortex location. Power spectra were examined for white noise type signatures that indicated vortex rotation contained within the radar sample volume. Spectra were simulated using radar and tornado cyclone parameters matched to those existing during the observations to determine spectral features for comparison with those recorded by the pulse-Doppler radar. The reflectivity throughout and around the funnel was uniform and spectra compared well. Although the precise vortex center location could not be deduced its position was consistent with tornado position determined from film documentation. In the gates containing vortex signatures spectral standard deviations were consistently maximal.
Abstract
A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The information is valid for a 10-cm wavelength and consists of relations that are based on an extensive list of previous and recent observational and modeling studies of polarimetric signatures of hydrometeors. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (size, concentrations, etc.), and quantification of bulk hydrometeor contents (amounts). A fuzzy classification algorithm that builds upon this foundation will be discussed in a forthcoming paper.
Abstract
A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The information is valid for a 10-cm wavelength and consists of relations that are based on an extensive list of previous and recent observational and modeling studies of polarimetric signatures of hydrometeors. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (size, concentrations, etc.), and quantification of bulk hydrometeor contents (amounts). A fuzzy classification algorithm that builds upon this foundation will be discussed in a forthcoming paper.
Abstract
An analysis of drop size distributions (DSDs) measured in four very different precipitation regimes is presented and is compared with polarimetric radar measurements. The DSDs are measured by a 2D video disdrometer, which is designed to measure drop size, shape, and fall speed with unprecedented accuracy. The observations indicate that significant DSD variability exists not only from one event to the next, but also within each system. Also, despite having vastly different storm structures and maximum rain rates, large raindrops with diameters greater than 5 mm occurred with each system. By comparing the occurrence of large drops with rainfall intensity, the authors find that the largest median diameters are not always associated with the heaviest rainfall, but are sometimes located either in advance of convective cores or, occasionally, in stratiform regions where rainfall rates are relatively low. Disdrometer and polarimetric radar measurements of radar reflectivity Z, differential reflectivity Z DR, specific differential phase K DP, and R(Z) and R(K DP) rain-rate estimators are compared in detail. Overall agreement is good, but it is found that both R(Z) and R(K DP) underestimate rain rate when the DSD is dominated by small drops and overestimate rain rate when the DSD is dominated by large drops. The results indicate that a classification of different rain types (associated with different DSDs) should be an essential part of polarimetric rainfall estimation. Furthermore, observations suggest that Z DR is a key parameter for making such a distinction. Last, the authors compute and compare maximum and average of gamma shape, slope, and intercept parameters for all four precipitation events. Potential measurement errors with the 2D video disdrometer are also discussed.
Abstract
An analysis of drop size distributions (DSDs) measured in four very different precipitation regimes is presented and is compared with polarimetric radar measurements. The DSDs are measured by a 2D video disdrometer, which is designed to measure drop size, shape, and fall speed with unprecedented accuracy. The observations indicate that significant DSD variability exists not only from one event to the next, but also within each system. Also, despite having vastly different storm structures and maximum rain rates, large raindrops with diameters greater than 5 mm occurred with each system. By comparing the occurrence of large drops with rainfall intensity, the authors find that the largest median diameters are not always associated with the heaviest rainfall, but are sometimes located either in advance of convective cores or, occasionally, in stratiform regions where rainfall rates are relatively low. Disdrometer and polarimetric radar measurements of radar reflectivity Z, differential reflectivity Z DR, specific differential phase K DP, and R(Z) and R(K DP) rain-rate estimators are compared in detail. Overall agreement is good, but it is found that both R(Z) and R(K DP) underestimate rain rate when the DSD is dominated by small drops and overestimate rain rate when the DSD is dominated by large drops. The results indicate that a classification of different rain types (associated with different DSDs) should be an essential part of polarimetric rainfall estimation. Furthermore, observations suggest that Z DR is a key parameter for making such a distinction. Last, the authors compute and compare maximum and average of gamma shape, slope, and intercept parameters for all four precipitation events. Potential measurement errors with the 2D video disdrometer are also discussed.
Abstract
Compelling in situ and polarimetric radar observations from a severe Oklahoma supercell storm are presented. The in situ observations are from an aircraft that entered the storm above the main inflow region, sampling the embryo curtain, main updraft, its western fringe (very close to the center of mesocyclonic circulation), and the hail cascade region. At the same time, the Cimarron polarimetric radar observed enhanced signatures in specific differential phase K dp and differential reflectivity Z dr straddling the main updraft and extending several kilometers above the melting layer. The distance of the storm from the radar balances the novelty of this dataset, however, which is on the order of 100 km. The authors therefore rely heavily on the in situ data, including calculation of polarimetric variables, on comparisons with other in situ datasets, and on accepted conceptual models of hail growth in supercell storms to clarify hydrometeor processes in light of the intriguing polarimetric signatures near the updraft. The relation of enhanced K dp to the main updraft, to the Z dr “column,” and to precipitation is discussed. Strong evidence points to melting ice particles (>3 mm) below the aircraft height as the origin of the K dp column in the region where an abundant number of small (<2 mm) drops are also observed. To support the notion that these drops are shed by melting and perhaps wet growth, results of calculations on aircraft data are discussed. Resolution issues are invoked, leading to possible reconciliation of radar measurements with in situ observations.
Abstract
Compelling in situ and polarimetric radar observations from a severe Oklahoma supercell storm are presented. The in situ observations are from an aircraft that entered the storm above the main inflow region, sampling the embryo curtain, main updraft, its western fringe (very close to the center of mesocyclonic circulation), and the hail cascade region. At the same time, the Cimarron polarimetric radar observed enhanced signatures in specific differential phase K dp and differential reflectivity Z dr straddling the main updraft and extending several kilometers above the melting layer. The distance of the storm from the radar balances the novelty of this dataset, however, which is on the order of 100 km. The authors therefore rely heavily on the in situ data, including calculation of polarimetric variables, on comparisons with other in situ datasets, and on accepted conceptual models of hail growth in supercell storms to clarify hydrometeor processes in light of the intriguing polarimetric signatures near the updraft. The relation of enhanced K dp to the main updraft, to the Z dr “column,” and to precipitation is discussed. Strong evidence points to melting ice particles (>3 mm) below the aircraft height as the origin of the K dp column in the region where an abundant number of small (<2 mm) drops are also observed. To support the notion that these drops are shed by melting and perhaps wet growth, results of calculations on aircraft data are discussed. Resolution issues are invoked, leading to possible reconciliation of radar measurements with in situ observations.
Abstract
Polarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity Z DR and specific differential phase shift K DP, collocated with reduced copolar correlation coefficient ρ hv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The Z DR maximum and ρ hv minimum are located within the temperature range between −10° and −15°C, whereas the K DP maximum is located just below the Z DR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH , Z DR, K DP, and ρ hv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρ hv and the correct shape (but not magnitude) of Z DR and K DP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.
Abstract
Polarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity Z DR and specific differential phase shift K DP, collocated with reduced copolar correlation coefficient ρ hv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The Z DR maximum and ρ hv minimum are located within the temperature range between −10° and −15°C, whereas the K DP maximum is located just below the Z DR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH , Z DR, K DP, and ρ hv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρ hv and the correct shape (but not magnitude) of Z DR and K DP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.
Abstract
Polarimetric radars are shown to be capable of tornado detection through the recognition of tornadic debris signatures that are characterized by the anomalously low cross-correlation coefficient ρ hv and differential reflectivity Z DR. This capability is demonstrated for three significant tornadic storms that struck the Oklahoma City, Oklahoma, metropolitan area. The first tornadic debris signature, based on the measurements with the National Severe Storms Laboratory’s Cimarron polarimetric radar, was reported for a storm on 3 May 1999. Similar signatures were identified for two significant tornadic events during the Joint Polarization Experiment (JPOLE) in May 2003. The data from these storms were collected with a polarimetric prototype of the Next-Generation Weather Radar (NEXRAD). In addition to a small-scale debris signature, larger-scale polarimetric signatures that might be relevant to tornadogenesis were persistently observed in tornadic supercells. The latter signatures are likely associated with lofted light debris (leaves, grass, dust, etc.) in the inflow region and intense size sorting of hydrometeors in the presence of strong wind shear and circulation.
Abstract
Polarimetric radars are shown to be capable of tornado detection through the recognition of tornadic debris signatures that are characterized by the anomalously low cross-correlation coefficient ρ hv and differential reflectivity Z DR. This capability is demonstrated for three significant tornadic storms that struck the Oklahoma City, Oklahoma, metropolitan area. The first tornadic debris signature, based on the measurements with the National Severe Storms Laboratory’s Cimarron polarimetric radar, was reported for a storm on 3 May 1999. Similar signatures were identified for two significant tornadic events during the Joint Polarization Experiment (JPOLE) in May 2003. The data from these storms were collected with a polarimetric prototype of the Next-Generation Weather Radar (NEXRAD). In addition to a small-scale debris signature, larger-scale polarimetric signatures that might be relevant to tornadogenesis were persistently observed in tornadic supercells. The latter signatures are likely associated with lofted light debris (leaves, grass, dust, etc.) in the inflow region and intense size sorting of hydrometeors in the presence of strong wind shear and circulation.
Abstract
Sounding of nonprecipitating clouds with the 10-cm wavelength Weather Surveillance Radar-1988 Doppler (WSR-88D) is discussed. Readily available enhancements to signal processing and volume coverage patterns of the WSR-88D allow observations of a variety of clouds with reflectivities as low as −25 dBZ (at a range of 10 km). The high sensitivity of the WSR-88D, its wide velocity and unambiguous range intervals, and the absence of attenuation allow accurate measurements of the reflectivity factor, Doppler velocity, and spectrum width fields in clouds to ranges of about 50 km. Fields of polarimetric variables in clouds, observed with a research polarimetric WSR-88D, demonstrate an abundance of information and help to resolve Bragg and particulate scatter. The scanning, Doppler, and polarimetric capabilities of the WSR-88D allow real-time, three-dimensional mapping of cloud processes, such as transformations of hydrometeors between liquid and ice phases. The presence of ice particles is revealed by high differential reflectivities and the lack of correlation between reflectivity and differential reflectivity in clouds in contrast to that found for rain. Pockets of high differential reflectivities are frequently observed in clouds; maximal values of differential reflectivity exceed 8 dB, far above the level observed in rain. The establishment of the WSR-88D network consisting of 157 polarimetric radars can be used to collect cloud data at any radar site, making the network a potentially powerful tool for climatic studies.
Abstract
Sounding of nonprecipitating clouds with the 10-cm wavelength Weather Surveillance Radar-1988 Doppler (WSR-88D) is discussed. Readily available enhancements to signal processing and volume coverage patterns of the WSR-88D allow observations of a variety of clouds with reflectivities as low as −25 dBZ (at a range of 10 km). The high sensitivity of the WSR-88D, its wide velocity and unambiguous range intervals, and the absence of attenuation allow accurate measurements of the reflectivity factor, Doppler velocity, and spectrum width fields in clouds to ranges of about 50 km. Fields of polarimetric variables in clouds, observed with a research polarimetric WSR-88D, demonstrate an abundance of information and help to resolve Bragg and particulate scatter. The scanning, Doppler, and polarimetric capabilities of the WSR-88D allow real-time, three-dimensional mapping of cloud processes, such as transformations of hydrometeors between liquid and ice phases. The presence of ice particles is revealed by high differential reflectivities and the lack of correlation between reflectivity and differential reflectivity in clouds in contrast to that found for rain. Pockets of high differential reflectivities are frequently observed in clouds; maximal values of differential reflectivity exceed 8 dB, far above the level observed in rain. The establishment of the WSR-88D network consisting of 157 polarimetric radars can be used to collect cloud data at any radar site, making the network a potentially powerful tool for climatic studies.
