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- Author or Editor: Dúsan S. Zrnić x
- Journal of Atmospheric and Oceanic Technology x
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Abstract
The concept of the polarimetric scattering matrix applicable to hydrometeors is reviewed to indicate the total number of measurands that is possible from a radar system with two orthogonal linear polarizations. It is shown how to obtain this complete set of polarimetric measurands together with Doppler spectral moments through a single receiver by proper choice of polarization in a transmit-receive sequence pair.
Abstract
The concept of the polarimetric scattering matrix applicable to hydrometeors is reviewed to indicate the total number of measurands that is possible from a radar system with two orthogonal linear polarizations. It is shown how to obtain this complete set of polarimetric measurands together with Doppler spectral moments through a single receiver by proper choice of polarization in a transmit-receive sequence pair.
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
Rainfall estimation from specific differential phases in meteorological situations with significant anomalous propagation (AP) is discussed. It is shown that the correlation coefficient between horizontally and vertically polarized backscatter signals and local variability of the total differential phase can be good identifiers of ground clutter–contaminated data. Further, it is suggested how to estimate rainfall in regions of ground clutter caused by AP.
Abstract
Rainfall estimation from specific differential phases in meteorological situations with significant anomalous propagation (AP) is discussed. It is shown that the correlation coefficient between horizontally and vertically polarized backscatter signals and local variability of the total differential phase can be good identifiers of ground clutter–contaminated data. Further, it is suggested how to estimate rainfall in regions of ground clutter caused by AP.
Abstract
A method for estimation of spectral moments on pulsed weather radars is presented. This scheme operates on oversampled echoes in range; that is, samples of in-phase and quadrature-phase components are collected at a rate several times larger than the reciprocal of the transmitted pulse length. The spectral moments are estimated by suitably combining weighted averages of these oversampled signals in range with usual processing of samples (spaced at the pulse repetition time) at a fixed range location. The weights in range are derived from a whitening transformation; hence, the oversampled signals become uncorrelated and, consequently, the variance of the estimates decreases significantly. Because the estimate errors are inversely proportional to the volume scanning times, it follows that storms can be surveyed much faster than is possible with current processing methods, or equivalently, for the current volume scanning time, accuracy of the estimates can be greatly improved. This significant improvement is achievable at large signal-to-noise ratios.
Abstract
A method for estimation of spectral moments on pulsed weather radars is presented. This scheme operates on oversampled echoes in range; that is, samples of in-phase and quadrature-phase components are collected at a rate several times larger than the reciprocal of the transmitted pulse length. The spectral moments are estimated by suitably combining weighted averages of these oversampled signals in range with usual processing of samples (spaced at the pulse repetition time) at a fixed range location. The weights in range are derived from a whitening transformation; hence, the oversampled signals become uncorrelated and, consequently, the variance of the estimates decreases significantly. Because the estimate errors are inversely proportional to the volume scanning times, it follows that storms can be surveyed much faster than is possible with current processing methods, or equivalently, for the current volume scanning time, accuracy of the estimates can be greatly improved. This significant improvement is achievable at large signal-to-noise ratios.
Abstract
A method to reduce errors in estimates of polarimetric variables beyond those achievable with standard estimators is suggested. It consists of oversampling echo signals in range, applying linear transformations to decorrelate these samples, processing in time the sequences at fixed range locations to obtain various second-order moments, averaging in range these moments, and, finally, combining them into polarimetric variables. The polarimetric variables considered are differential reflectivity, differential phase, and the copolar correlation coefficient between the horizontally and vertically polarized echoes. Simulations and analytical formulas confirm a reduction in variance proportional to the number of samples within the pulse compared to standard processing of signals behind a matched filter. This reduction is possible, however, if the signal-to-noise ratios (SNRs) are larger than a critical value. Plots of the critical SNRs for various estimates as functions of Doppler spectrum width and other parameters are provided.
Abstract
A method to reduce errors in estimates of polarimetric variables beyond those achievable with standard estimators is suggested. It consists of oversampling echo signals in range, applying linear transformations to decorrelate these samples, processing in time the sequences at fixed range locations to obtain various second-order moments, averaging in range these moments, and, finally, combining them into polarimetric variables. The polarimetric variables considered are differential reflectivity, differential phase, and the copolar correlation coefficient between the horizontally and vertically polarized echoes. Simulations and analytical formulas confirm a reduction in variance proportional to the number of samples within the pulse compared to standard processing of signals behind a matched filter. This reduction is possible, however, if the signal-to-noise ratios (SNRs) are larger than a critical value. Plots of the critical SNRs for various estimates as functions of Doppler spectrum width and other parameters are provided.
Abstract
This paper deals with the recovery of Doppler velocities in the presence of range overlaid echoes. Transmitted pulses are phase shifted to tag the echoes from scatterers, which are separated by the unambiguous range. A new systematic phase code and an algorithm for estimating the mean velocities of overlaid first- and second-trip signals are presented. The return samples are phase corrected to cohere the first- or the second-trip signal, leaving the other signal power spread in a deterministic manner across the Doppler spectrum. An algorithm has been developed to recover the velocity of the weaker signal even if the power ratio of overlaid signals is as large as 40 dB, for spectrum widths of 4 m s−1 or less, and an unambiguous velocity of 32 m s−1. Tests on simulated weather signals indicate that the method, employed in surveillance Doppler radars, can effectively double the unambiguous range without the sacrifice of the unambiguous velocity interval.
Abstract
This paper deals with the recovery of Doppler velocities in the presence of range overlaid echoes. Transmitted pulses are phase shifted to tag the echoes from scatterers, which are separated by the unambiguous range. A new systematic phase code and an algorithm for estimating the mean velocities of overlaid first- and second-trip signals are presented. The return samples are phase corrected to cohere the first- or the second-trip signal, leaving the other signal power spread in a deterministic manner across the Doppler spectrum. An algorithm has been developed to recover the velocity of the weaker signal even if the power ratio of overlaid signals is as large as 40 dB, for spectrum widths of 4 m s−1 or less, and an unambiguous velocity of 32 m s−1. Tests on simulated weather signals indicate that the method, employed in surveillance Doppler radars, can effectively double the unambiguous range without the sacrifice of the unambiguous velocity interval.
Abstract
This paper explores ground clutter filtering with a class of cancelers that use regression. Regression filters perform this task in a simple manner, resulting in similar or better performance than the fifth-order elliptic filter implemented in the WSR-88D. Assuming a slowly varying clutter signal, a suitable projection of the composite signal is used to notch a band of frequencies at either side of zero Doppler frequency. The complexity of this procedure is reduced by using a set of orthogonal polynomials. The frequency response of the resulting filter is related to the number of samples in each input block and the maximum order of approximating polynomials. Through simulations, it is demonstrated that the suppression characteristic of this filter is better than that of step-initialized infinite impulse response filters, whereby transients degrade the theoretical frequency response. The performance of regression filters is tested with an actual weather signal, and their efficiency in ground clutter canceling is demonstrated.
Abstract
This paper explores ground clutter filtering with a class of cancelers that use regression. Regression filters perform this task in a simple manner, resulting in similar or better performance than the fifth-order elliptic filter implemented in the WSR-88D. Assuming a slowly varying clutter signal, a suitable projection of the composite signal is used to notch a band of frequencies at either side of zero Doppler frequency. The complexity of this procedure is reduced by using a set of orthogonal polynomials. The frequency response of the resulting filter is related to the number of samples in each input block and the maximum order of approximating polynomials. Through simulations, it is demonstrated that the suppression characteristic of this filter is better than that of step-initialized infinite impulse response filters, whereby transients degrade the theoretical frequency response. The performance of regression filters is tested with an actual weather signal, and their efficiency in ground clutter canceling is demonstrated.
