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Abstract
Demonstration of a method for improved Doppler spectral moment estimation is made on NOAA's research and development Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma. Time series data have been recorded using a commercial processor and digital receiver whereby the sampling frequency is several times larger than the reciprocal of the transmitted pulse width. The in-phase and quadrature-phase components of oversampled weather signals are used to estimate the first three spectral moments by suitably combining weighted averages in range with usual processing at fixed range locations. The weights are chosen in such a manner that the resulting signals become uncorrelated. Consequently, the variance of estimates decreases significantly as is verified by this experiment.
Abstract
Demonstration of a method for improved Doppler spectral moment estimation is made on NOAA's research and development Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma. Time series data have been recorded using a commercial processor and digital receiver whereby the sampling frequency is several times larger than the reciprocal of the transmitted pulse width. The in-phase and quadrature-phase components of oversampled weather signals are used to estimate the first three spectral moments by suitably combining weighted averages in range with usual processing at fixed range locations. The weights are chosen in such a manner that the resulting signals become uncorrelated. Consequently, the variance of estimates decreases significantly as is verified by this experiment.
Abstract
Specific differential propagation phase (K DP) is examined for estimating convective rainfall in Colorado and Kansas. Estimates are made at S band with K DP alone and in combination with radar reflectivity (Z H). Results are compared to gauge observations by computing bias factors, defined as the sum of gauge-measured rainfalls divided by the sum of radar estimates at gauges reporting rainfall, and the correlation coefficient between the gauge and radar-estimated amounts. Rainfall accumulations computed from positive-only values of K DP (provided Z H ≥ 25 dBZ) yield bias factors that vary from 0.76 to 2.42 for 3 storms in Colorado and from 0.78 to 1.46 for 10 storms in Kansas. Correlation coefficients between gauge-observed and radar-estimated rainfalls are 0.76 to 0.95. When negative K DP’s are included as negative rainfall rates, bias factors range from 0.81 to 3.00 in Colorado and from 0.84 to 2.31 in Kansas. In most storms, the correlation between gauge and radar rainfalls decreases slightly.
In an experiment with the K DP/Z H combination, rainfall rates are computed from K DP when K DP is ≥0.4° km−1 and from Z H for K DP < 0.4° km−1 and Z H ≥ 25 dBZ. Neglect of the negative K DP’s and substitution of the always positive Z H rainfall rates result in a tendency to overestimate rainfall. Bias factors are 0.63–1.46 for Colorado storms and 0.68–0.97 for Kansas storms, and correlation coefficients between gauge and radar amounts are 0.80–0.95. In yet another test with the K DP/Z H pair, rainfall estimates are computed from K DP when Z H ≥ 40 dBZ and from Z H when 25 ⩽ Z H < 40 dBZ. For this experiment, bias factors range from 0.90 to 1.91 in Colorado and from 0.88 to 1.46 in Kansas. Correlation coefficients are 0.80–0.96.
Since bias factors and correlation coefficients between estimated rainfalls and gauge observations for K DP are similar to those for radar reflectivity, there was no obvious benefit with K DP rainfalls for a well-calibrated radar. Large underestimates with K DP in two storms were attributed to rainfalls dominated by small drops. In one storm, the problem was aggravated by widespread negative K DP’s thought related to vertical gradients of precipitation. An advantage of K DP-derived rainfall estimates confirmed here is an insensitivity to anomalous propagation.
Abstract
Specific differential propagation phase (K DP) is examined for estimating convective rainfall in Colorado and Kansas. Estimates are made at S band with K DP alone and in combination with radar reflectivity (Z H). Results are compared to gauge observations by computing bias factors, defined as the sum of gauge-measured rainfalls divided by the sum of radar estimates at gauges reporting rainfall, and the correlation coefficient between the gauge and radar-estimated amounts. Rainfall accumulations computed from positive-only values of K DP (provided Z H ≥ 25 dBZ) yield bias factors that vary from 0.76 to 2.42 for 3 storms in Colorado and from 0.78 to 1.46 for 10 storms in Kansas. Correlation coefficients between gauge-observed and radar-estimated rainfalls are 0.76 to 0.95. When negative K DP’s are included as negative rainfall rates, bias factors range from 0.81 to 3.00 in Colorado and from 0.84 to 2.31 in Kansas. In most storms, the correlation between gauge and radar rainfalls decreases slightly.
In an experiment with the K DP/Z H combination, rainfall rates are computed from K DP when K DP is ≥0.4° km−1 and from Z H for K DP < 0.4° km−1 and Z H ≥ 25 dBZ. Neglect of the negative K DP’s and substitution of the always positive Z H rainfall rates result in a tendency to overestimate rainfall. Bias factors are 0.63–1.46 for Colorado storms and 0.68–0.97 for Kansas storms, and correlation coefficients between gauge and radar amounts are 0.80–0.95. In yet another test with the K DP/Z H pair, rainfall estimates are computed from K DP when Z H ≥ 40 dBZ and from Z H when 25 ⩽ Z H < 40 dBZ. For this experiment, bias factors range from 0.90 to 1.91 in Colorado and from 0.88 to 1.46 in Kansas. Correlation coefficients are 0.80–0.96.
Since bias factors and correlation coefficients between estimated rainfalls and gauge observations for K DP are similar to those for radar reflectivity, there was no obvious benefit with K DP rainfalls for a well-calibrated radar. Large underestimates with K DP in two storms were attributed to rainfalls dominated by small drops. In one storm, the problem was aggravated by widespread negative K DP’s thought related to vertical gradients of precipitation. An advantage of K DP-derived rainfall estimates confirmed here is an insensitivity to anomalous propagation.
Abstract
A calibration procedure of differential reflectivity on the Weather Surveillance Radar-1988 Doppler (WSR-88D) is described. It has been tested on NOAA's modified WSR-88D research and development polarimetric radar and is directly applicable to radars that simultaneously transmit and receive waves having horizontal and vertical polarization.
Abstract
A calibration procedure of differential reflectivity on the Weather Surveillance Radar-1988 Doppler (WSR-88D) is described. It has been tested on NOAA's modified WSR-88D research and development polarimetric radar and is directly applicable to radars that simultaneously transmit and receive waves having horizontal and vertical polarization.
Abstract
Characteristics of the magnitude and phase of correlation coefficients between horizontally and vertically polarized returns from ground clutter echoes are quantified by analyzing histograms obtained with an 11-cm wavelength weather surveillance radar in Norman, Oklahoma. The radar receives simultaneously horizontal and vertical (SHV) electric fields and can transmit either horizontal fields or both vertical and horizontal fields. The differences between correlations obtained in this SHV mode and correlations measured in alternate H, V mode are reviewed; a histogram of differential phase obtained in Florida using alternate H, V mode is also presented. Data indicate that the backscatter differential phase of clutter has a broad histogram that completely overlaps the narrow histogram of precipitation echoes. This is important as it implies that a potent discriminator for separating clutter from meteorological echoes is the texture of the differential phase. Values of the copolar cross-correlation coefficient from clutter overlap completely those from precipitation, and effective discrimination is possible only if averages in range are taken. It is demonstrated that the total differential phase (system and backscatter) depends on the polarimetric measurement technique and the type of scatterers. In special circumstances, such as calibrating or monitoring the radar, clutter signal can be beneficial. Specifically, system differential phase can be estimated from histograms of ground clutter, receiver differential phase can be estimated from precipitation returns, and from these two, the differential phase of transmitted waves is easily computed.
Abstract
Characteristics of the magnitude and phase of correlation coefficients between horizontally and vertically polarized returns from ground clutter echoes are quantified by analyzing histograms obtained with an 11-cm wavelength weather surveillance radar in Norman, Oklahoma. The radar receives simultaneously horizontal and vertical (SHV) electric fields and can transmit either horizontal fields or both vertical and horizontal fields. The differences between correlations obtained in this SHV mode and correlations measured in alternate H, V mode are reviewed; a histogram of differential phase obtained in Florida using alternate H, V mode is also presented. Data indicate that the backscatter differential phase of clutter has a broad histogram that completely overlaps the narrow histogram of precipitation echoes. This is important as it implies that a potent discriminator for separating clutter from meteorological echoes is the texture of the differential phase. Values of the copolar cross-correlation coefficient from clutter overlap completely those from precipitation, and effective discrimination is possible only if averages in range are taken. It is demonstrated that the total differential phase (system and backscatter) depends on the polarimetric measurement technique and the type of scatterers. In special circumstances, such as calibrating or monitoring the radar, clutter signal can be beneficial. Specifically, system differential phase can be estimated from histograms of ground clutter, receiver differential phase can be estimated from precipitation returns, and from these two, the differential phase of transmitted waves is easily computed.
A detailed and unique multisensor observation of an undular bore is presented. The data include those from rawinsonde, satellite, two Doppler radars, and a tall instrumented tower. Noteworthy are Doppler radar images that resolve the wave's characteristics and capture a good part of its spatial extent. The basic parameters of the wave train are established from the observations.
A detailed and unique multisensor observation of an undular bore is presented. The data include those from rawinsonde, satellite, two Doppler radars, and a tall instrumented tower. Noteworthy are Doppler radar images that resolve the wave's characteristics and capture a good part of its spatial extent. The basic parameters of the wave train are established from the observations.
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.
Electrified Cloud Areas Observed in the SHV and LDR Radar ModesAbstract
Strong in-cloud electric fields align ice particles that can be observed with polarization diversity radars. Radar data collected in the simultaneous transmission mode, wherein horizontally and vertically polarized waves are simultaneously transmitted and received (SHV), and in a mode whereby a single-polarization wave is transmitted and dual (orthogonal)-polarization waves are received simultaneously [linear depolarization (LDR) mode] are analyzed. The necessary time delay between the SHV and LDR modes for our radar was about 1–4 min. The data show that the areas of canted crystals from the LDR mode are larger than those from the SHV mode, thereby indicating that the LDR mode is more sensitive to canted ice cloud particles than the SHV mode. The data also demonstrate that the differential phase and correlation coefficient in the LDR mode are indicative of canted cloud crystals and that these variables often are more sensitive to canted crystals than the linear depolarization ratio studied earlier. Rapidly scanning radars such as those with a phased array antenna could operate sequentially in the SHV and LDR modes and thus better detect cloud volumes characterized by enhanced electric fields.
Abstract
Strong in-cloud electric fields align ice particles that can be observed with polarization diversity radars. Radar data collected in the simultaneous transmission mode, wherein horizontally and vertically polarized waves are simultaneously transmitted and received (SHV), and in a mode whereby a single-polarization wave is transmitted and dual (orthogonal)-polarization waves are received simultaneously [linear depolarization (LDR) mode] are analyzed. The necessary time delay between the SHV and LDR modes for our radar was about 1–4 min. The data show that the areas of canted crystals from the LDR mode are larger than those from the SHV mode, thereby indicating that the LDR mode is more sensitive to canted ice cloud particles than the SHV mode. The data also demonstrate that the differential phase and correlation coefficient in the LDR mode are indicative of canted cloud crystals and that these variables often are more sensitive to canted crystals than the linear depolarization ratio studied earlier. Rapidly scanning radars such as those with a phased array antenna could operate sequentially in the SHV and LDR modes and thus better detect cloud volumes characterized by enhanced electric fields.
Abstract
The recently installed S-band phased-array radar (PAR) at the National Weather Radar Testbed (NWRT) offers fast and flexible beam steering through electronic beam forming. This capability allows the implementation of a novel scanning strategy termed beam multiplexing (BMX), with the goal of providing fast updates of weather information with high statistical accuracy. For conventional weather radar the data acquisition time for a sector scan or a volume coverage pattern (VCP) can be reduced by increasing the antenna’s rotation rate to the extent that the pedestal allows. However, statistical errors of the spectral moment estimates will increase due to the fewer samples that are available for the estimation. BMX is developed to exploit the idea of collecting independent samples and maximizing the usage of radar resources. An improvement factor is introduced to quantify the BMX performance, which is defined by the reduction in data acquisition time using BMX when the same data accuracy obtained by a conventional scanning strategy is maintained. It is shown theoretically that a fast update without compromising data quality can be achieved using BMX at small spectrum widths and a high signal-to-noise ratio (SNR). Applications of BMX to weather observations are demonstrated using the PAR, and the results indicate that an average improvement factor of 2–4 can be obtained for SNR higher than 10 dB.
Abstract
The recently installed S-band phased-array radar (PAR) at the National Weather Radar Testbed (NWRT) offers fast and flexible beam steering through electronic beam forming. This capability allows the implementation of a novel scanning strategy termed beam multiplexing (BMX), with the goal of providing fast updates of weather information with high statistical accuracy. For conventional weather radar the data acquisition time for a sector scan or a volume coverage pattern (VCP) can be reduced by increasing the antenna’s rotation rate to the extent that the pedestal allows. However, statistical errors of the spectral moment estimates will increase due to the fewer samples that are available for the estimation. BMX is developed to exploit the idea of collecting independent samples and maximizing the usage of radar resources. An improvement factor is introduced to quantify the BMX performance, which is defined by the reduction in data acquisition time using BMX when the same data accuracy obtained by a conventional scanning strategy is maintained. It is shown theoretically that a fast update without compromising data quality can be achieved using BMX at small spectrum widths and a high signal-to-noise ratio (SNR). Applications of BMX to weather observations are demonstrated using the PAR, and the results indicate that an average improvement factor of 2–4 can be obtained for SNR higher than 10 dB.
Abstract
This paper suggests a cylindrical configuration for agile beam polarimetric phased-array radar (PPAR) for weather surveillance. The most often used array configuration for PAR is a planar array antenna. The planar configuration, however, has significant deficiencies for polarimetric measurements, as well as other limitations, such as increases in beamwidth, decreases of sensitivity, and changes in the polarization basis when the beam scans off its broadside. The cylindrical polarimetric phased-array radar (CPPAR) is proposed to avoid these deficiencies. The CPPAR principle and potential performance are demonstrated through theoretical analysis and simulation. It is shown that the CPPAR has the advantage of a scan-invariant polarization basis, and thus avoids the inherent limitations of the planar PPAR (i.e., PPPAR).
Abstract
This paper suggests a cylindrical configuration for agile beam polarimetric phased-array radar (PPAR) for weather surveillance. The most often used array configuration for PAR is a planar array antenna. The planar configuration, however, has significant deficiencies for polarimetric measurements, as well as other limitations, such as increases in beamwidth, decreases of sensitivity, and changes in the polarization basis when the beam scans off its broadside. The cylindrical polarimetric phased-array radar (CPPAR) is proposed to avoid these deficiencies. The CPPAR principle and potential performance are demonstrated through theoretical analysis and simulation. It is shown that the CPPAR has the advantage of a scan-invariant polarization basis, and thus avoids the inherent limitations of the planar PPAR (i.e., PPPAR).
