Search Results
You are looking at 11 - 20 of 76 items for
- Author or Editor: Dusan Zrnic x
- Refine by Access: All Content x
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
Probert-Jones' radar equation assumes receiver bandwidth large compared to the reciprocal of the transmitted pulse width τ. The advent of coherent radars with precise transmitter frequencies allows consideration of receiver bandwidth “matched” to and sometimes smaller than τ−1 in order to enhance measurement signal-to-noise ratio.
An extension to the radar equation has been made to show explicitly the dependence of echo power on the product of transmitter pulse width and receiver bandwidth. When receiver bandwidth is less than twice τ−1, there is significant loss in echo power. This should be accounted for when estimating reflectivities.
Considerable improvement in Doppler velocity estimation can often be obtained by matching range resolution to the angular one and this has implications of practical importance when moderately sensitive dual-Doppler radars are used to map the mesoscale wind in clear air.
Abstract
Probert-Jones' radar equation assumes receiver bandwidth large compared to the reciprocal of the transmitted pulse width τ. The advent of coherent radars with precise transmitter frequencies allows consideration of receiver bandwidth “matched” to and sometimes smaller than τ−1 in order to enhance measurement signal-to-noise ratio.
An extension to the radar equation has been made to show explicitly the dependence of echo power on the product of transmitter pulse width and receiver bandwidth. When receiver bandwidth is less than twice τ−1, there is significant loss in echo power. This should be accounted for when estimating reflectivities.
Considerable improvement in Doppler velocity estimation can often be obtained by matching range resolution to the angular one and this has implications of practical importance when moderately sensitive dual-Doppler radars are used to map the mesoscale wind in clear air.
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 radar polarimetric method for areal rainfall estimation is examined. In contrast to the polarimetric algorithm based on specific differential phase K DP, the proposed method does not require rain-rate estimation from K DP inside the area of interest, but it utilizes only values of total differential phase ΦDP on the areal contour. Even if the radar reflectivity and differential phase data inside the area are corrupted by ground clutter, anomalous propagation, biological scatterers, or hail contamination, reliable areal rainfall estimate is still possible, provided that correct ΦDP estimates are available at a relatively small number of range locations in or at the periphery of the contour of this area.
This concept of areal rainfall estimation has been tested on the Little Washita River watershed area in Oklahoma that contains 42 densely located rain gauges. The areal rainfall estimates obtained from the polarimetric data collected with the 10-cm Cimarron radar are in good agreement with the gauge data, with the standard error of about 18%. This accuracy is better than that obtained with the algorithm utilizing areal averaging of pointwise estimates of K DP inside the watershed area.
Abstract
A radar polarimetric method for areal rainfall estimation is examined. In contrast to the polarimetric algorithm based on specific differential phase K DP, the proposed method does not require rain-rate estimation from K DP inside the area of interest, but it utilizes only values of total differential phase ΦDP on the areal contour. Even if the radar reflectivity and differential phase data inside the area are corrupted by ground clutter, anomalous propagation, biological scatterers, or hail contamination, reliable areal rainfall estimate is still possible, provided that correct ΦDP estimates are available at a relatively small number of range locations in or at the periphery of the contour of this area.
This concept of areal rainfall estimation has been tested on the Little Washita River watershed area in Oklahoma that contains 42 densely located rain gauges. The areal rainfall estimates obtained from the polarimetric data collected with the 10-cm Cimarron radar are in good agreement with the gauge data, with the standard error of about 18%. This accuracy is better than that obtained with the algorithm utilizing areal averaging of pointwise estimates of K DP inside the watershed area.
Abstract
The following rainfall measurements are compared: 1) the reflectivity factor–rain rate or R(Z) relation, whereby the rain is estimated point by point for mapping or area integration; 2) use of a specific differential phase K DP (between vertical and horizontal polarization) in a relation with rainfall rate for point-by-point mapping and subsequent integration over areas and time; 3) use of a R(K DP) relation together with a relation between K DP and Z to derive a polarimetrically tuned or matched R(Z) relation; and 4) use of empirical relations between the rainfall volume and the time integral of the storm area in which reflectivity is larger than a selected threshold. These methods are tested on five cases—two summer-type convections, one winter convective case, and two events of stratiform rain with embedded convection. Accumulations of rain in a dense gauge network in Oklahoma are used as a standard for comparison with radar measurements. In four of the five cases the rain totals obtained from the R(K DP) relation agree very well with actual gauge accumulations. This is significantly better than the Marshall–Palmer R(Z) relation, which agrees well with gauges for only one event. Matching Z to K DP brought the R(Z) derived rain total to better agreement with gauges in three more cases.
Abstract
The following rainfall measurements are compared: 1) the reflectivity factor–rain rate or R(Z) relation, whereby the rain is estimated point by point for mapping or area integration; 2) use of a specific differential phase K DP (between vertical and horizontal polarization) in a relation with rainfall rate for point-by-point mapping and subsequent integration over areas and time; 3) use of a R(K DP) relation together with a relation between K DP and Z to derive a polarimetrically tuned or matched R(Z) relation; and 4) use of empirical relations between the rainfall volume and the time integral of the storm area in which reflectivity is larger than a selected threshold. These methods are tested on five cases—two summer-type convections, one winter convective case, and two events of stratiform rain with embedded convection. Accumulations of rain in a dense gauge network in Oklahoma are used as a standard for comparison with radar measurements. In four of the five cases the rain totals obtained from the R(K DP) relation agree very well with actual gauge accumulations. This is significantly better than the Marshall–Palmer R(Z) relation, which agrees well with gauges for only one event. Matching Z to K DP brought the R(Z) derived rain total to better agreement with gauges in three more cases.
Observations of Convective Thermals with Weather RadarAbstract
It is shown that the NEXRAD weather radar with enhanced detectability is capable of observing the evolution of convective thermals. The fields of radar differential reflectivity show that the upper parts of the thermals are observable due to Bragg scatter, whereas scattering from insects dominates in the lower parts. The thermal-top rise rate is between 1.5 and 3.7 m s−1 in the analyzed case. Radar observations of thermals also enable estimations of their maximum heights, horizontal sizes, and the turbulent dissipation rate within each thermal. These attributes characterize the intensity of convection.
Abstract
It is shown that the NEXRAD weather radar with enhanced detectability is capable of observing the evolution of convective thermals. The fields of radar differential reflectivity show that the upper parts of the thermals are observable due to Bragg scatter, whereas scattering from insects dominates in the lower parts. The thermal-top rise rate is between 1.5 and 3.7 m s−1 in the analyzed case. Radar observations of thermals also enable estimations of their maximum heights, horizontal sizes, and the turbulent dissipation rate within each thermal. These attributes characterize the intensity of convection.
Abstract
Herein are proposed novel estimators of differential reflectivity Z DR and correlation coefficient ρ hv between horizontally and vertically polarized echoes. The estimators use autocorrelations and cross correlations of the returned signals to avoid bias by omnipresent but varying white noise. These estimators are considered for implementation on the future polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) network. On the current network the reflectivity factor is measured at signal-to-noise ratios (SNRs) as low as 2 dB and the same threshold is expected to hold for the polarimetric variables. At such low SNR and all the way up to SNR = 15 dB, the conventional estimators of differential reflectivity and the copolar correlation coefficient are prone to errors due to uncertainties in noise levels caused by instability of radar devices, thermal radiations of precipitation and the ground, and wideband radiation of electrically active clouds. Noise variations at SNR less than 15 dB can bias the estimates beyond apparatus accuracy. For brevity the authors refer to the estimators of Z DR and ρ hv free from noise bias as the “1-lag estimators” because these are derived from 1-lag correlations. The estimators are quite robust and the only weak assumption for validity is that spectral widths of signals from vertically and horizontally polarized returns are equal. This assumption is verified on radar data. Radar observations demonstrate the validity of these estimator and lower sensitivity to interference signals than the conventional algorithms.
Abstract
Herein are proposed novel estimators of differential reflectivity Z DR and correlation coefficient ρ hv between horizontally and vertically polarized echoes. The estimators use autocorrelations and cross correlations of the returned signals to avoid bias by omnipresent but varying white noise. These estimators are considered for implementation on the future polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) network. On the current network the reflectivity factor is measured at signal-to-noise ratios (SNRs) as low as 2 dB and the same threshold is expected to hold for the polarimetric variables. At such low SNR and all the way up to SNR = 15 dB, the conventional estimators of differential reflectivity and the copolar correlation coefficient are prone to errors due to uncertainties in noise levels caused by instability of radar devices, thermal radiations of precipitation and the ground, and wideband radiation of electrically active clouds. Noise variations at SNR less than 15 dB can bias the estimates beyond apparatus accuracy. For brevity the authors refer to the estimators of Z DR and ρ hv free from noise bias as the “1-lag estimators” because these are derived from 1-lag correlations. The estimators are quite robust and the only weak assumption for validity is that spectral widths of signals from vertically and horizontally polarized returns are equal. This assumption is verified on radar data. Radar observations demonstrate the validity of these estimator and lower sensitivity to interference signals than the conventional algorithms.
Abstract
Chaff contaminates estimates of precipitation amounts; hence, it is important to remove (or censor) its presence from the fields of radar reflectivity. It is demonstrated that efficient and direct identification of chaff is possible with a polarimetric radar. Specifically considered are the horizontal and vertical polarization basis and covariances of corresponding returned signals. Pertinent polarimetric variables are the copolar correlation coefficient, differential reflectivity, and the linear depolarization ratio. Two models are used to compute the expected values of these variables. In one, chaff is approximated with a Hertzian dipole and, in the other, with a thin wire antenna. In these models chaff is assumed to have a uniform distribution of flutter angles (angle between the horizontal plane and chaff axis). The two models produce nearly equivalent results. Also shown are polarimetric signatures of chaff observed in the presence of precipitation. Inferences about chaff's orientation are made from comparisons between measured and observed differential reflectivity and the cross-correlation coefficient.
Abstract
Chaff contaminates estimates of precipitation amounts; hence, it is important to remove (or censor) its presence from the fields of radar reflectivity. It is demonstrated that efficient and direct identification of chaff is possible with a polarimetric radar. Specifically considered are the horizontal and vertical polarization basis and covariances of corresponding returned signals. Pertinent polarimetric variables are the copolar correlation coefficient, differential reflectivity, and the linear depolarization ratio. Two models are used to compute the expected values of these variables. In one, chaff is approximated with a Hertzian dipole and, in the other, with a thin wire antenna. In these models chaff is assumed to have a uniform distribution of flutter angles (angle between the horizontal plane and chaff axis). The two models produce nearly equivalent results. Also shown are polarimetric signatures of chaff observed in the presence of precipitation. Inferences about chaff's orientation are made from comparisons between measured and observed differential reflectivity and the cross-correlation coefficient.
Abstract
The authors contrast rainfall in two Oklahoma squall lines: one with deep convection occurred in the spring and the other with shallower convection in the winter. Both passed over a micronetwork of densely spaced rain gauges and were observed with the National Severe Storm Laboratory's polarimetric weather radar. Polarimetric measurements reveal differences in storm structure that in turn imply that microphysical processes caused the drop size distributions to be quite distinct for the two events. In the winter squall line the conventional R(Z) algorithm for estimating rainfall fails badly, whereas in the summer squall line it performs well. The method based on specific differential phase measurements, however, yields a very good match between radar-derived areal precipitation amount and rain depth obtained from the micronetwork of densely located rain gauges for both events.
Abstract
The authors contrast rainfall in two Oklahoma squall lines: one with deep convection occurred in the spring and the other with shallower convection in the winter. Both passed over a micronetwork of densely spaced rain gauges and were observed with the National Severe Storm Laboratory's polarimetric weather radar. Polarimetric measurements reveal differences in storm structure that in turn imply that microphysical processes caused the drop size distributions to be quite distinct for the two events. In the winter squall line the conventional R(Z) algorithm for estimating rainfall fails badly, whereas in the summer squall line it performs well. The method based on specific differential phase measurements, however, yields a very good match between radar-derived areal precipitation amount and rain depth obtained from the micronetwork of densely located rain gauges for both events.
