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Wind velocity is of great importance for weather monitoring, aviation hazard alerting, wind energy exploring, etc. Doppler radar is widely used to measure wind under rainy condition by sensing the raindrops entrained by the background wind. However, the Doppler velocity, which is a reflection of the raindrops’ velocity in radial direction, is not coincident with the background wind because of the strong inertia of raindrops. Efforts should be made to distinguish the difference between the raindrops’ velocity and the background wind velocity. In this article, we try to establish a relationship between the background wind velocity and the raindrops’ velocity by introducing a definition of the raindrops’ characteristic size, which is related to the velocity characterized by the strongest Doppler spectral component. It is found that the fusion of differential reflectivity and the depolarization ratio can serve as a good proxy for the estimation of the characteristic size. Simulation results for $S$/$C$/$X$-band radars and radar measurements verify the good performance of the proposed retrieval model for the characteristic size, which lays a solid foundation for the retrieval of the background wind velocity.

Accurate precipitation estimation with weather radars is essential for hydrological and meteorological applications. The differential reflectivity (ZDR) is a crucial weather radar measurement that helps to improve quantitative precipitation estimates using polarimetric weather radars. However, a system bias between the horizontal and vertical channels generated by the radar produces an offset in ZDR. Existing methods to calibrate ZDR measurements rely on the intrinsic values of the ZDR of natural targets (e.g. drizzle or dry snow) collected at high elevation angles (e.g. higher than 40∘ or even at 90∘), in which ZDR values close to 0 dB are expected. However, not all weather radar systems can scan at such high elevation angles or point the antenna vertically to collect precipitation measurements passing overhead. Therefore, there is a need to develop new methods to calibrate ZDR measurements using lower-elevation scans. In this work, we present and analyse a novel method for correcting and monitoring the ZDR offset using quasi-vertical profiles computed from scans collected at 9∘ elevations. The method is applied to radar data collected through 1 year of precipitation events by two operational C-band polarimetric weather radars in the UK. The proposed method shows a relative error of 0.1 dB when evaluated against the traditional approach based on ZDR measurements collected at 90∘ elevations. Additionally, the method is independently assessed using disdrometers located near the radar sites. The results showed a reasonable agreement between disdrometer-derived and radar-calibrated ZDR measurements.

The accuracy required for a correct interpretation of differential reflectivity (ZDR) is typically estimated to be between 0.1 and 0.2 dB. This is achieved through calibration, defined as the identification of the constant or time-varying offset to be subtracted from the measurements in order to isolate the meteorological signals. We propose two innovative steps: the automated selection of sufficiently homogeneous sections of Plan Position Indicator (PPI) scans at 90∘ elevation, performed in both rain and snow, and the ordinary kriging interpolation of the median ZDR value of the chosen radar volumes. This technique has been successfully applied to five field campaigns in various climatic regions. The availability of overlapping scans from two nearby radars allowed us to evaluate the calibration approach, and demonstrated the benefits of defining a time-varying offset. Even though the method has been designed to work with both solid and liquid precipitation, it particularly benefits radar systems with limited access to rain measurements due to the deployment in mountainous or polar regions or to issues affecting the lowest range gates.

This paper uses the MaXPol dual-polarization radar data of WeiNing Meteorological Bureau of GuiZhou Province to analyze the hail weather process on September 13, 2019. The research shows that (1) Using the attenuation-corrected X-band data, it is analyzed by comparison method in the echo region and shows that the differential reflectivity (Zdr),the correlation coefficient (ρhv) are high but the differential phase (PhiDP) is low, when the reflectivity (Z) is 50 dBZ or more. (2) Particles of the process are classified by the fuzzy logic method with parameters of Z, Zdr, ρhv and PhiDP. (3) The hail region were identified from the radar echo map and found to be consistent with local weather phenomena.

Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D beam can appear prominently on radar users’ displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for automated algorithms to do the same. The WSR-88D network provides dual-polarimetric capabilities across the United States, leading to the collection of a large database of chaff cases. This database is analyzed to determine the characteristics of chaff in terms of the reflectivity factor and polarimetric variables on large scales. Particular focus is given to the dynamics of differential reflectivity ZDR in chaff and its dependence on height. In contrast to radar observations of chaff for a single event, this study is able to reveal a repeatable and new pattern of radar chaff observations. A discussion about the observed characteristics is presented, and hypotheses for the observed ZDR dynamics are put forth.

This study investigates the how riming in stratiform precipitation impacts polarimetric signatures. Using a vertically pointing Doppler X-band radar, cases can be separated into one of three groups: unrimed to lightly rimed, riming with no bimodal spectra and fall speeds greater than 2.0 m s−1, and riming with bimodal velocity spectra. By averaging polarimetric variables over a 20° by 10-km box near the X-band radar, different signatures were documented for each of the three groups. These polarimetric signatures were then compared with a simplified T-matrix scattering model. Differential reflectivity ZDR was the one polarimetric variable to consistently vary across all three groups. Unrimed to lightly rimed cases had profiles of polarimetric signatures similar to numerous previous studies. Riming cases without detectable bimodal spectra had ZDR values on the order of 0.2 dB lower than unrimed to lightly rimed cases, while cases with bimodal spectra had ZDR values about 0.2–0.4 dB higher than unrimed to lightly rimed cases. Both signatures were reproduced using populations of aggregates, dendrites, and needles in the T-matrix scattering model. While these signatures show the potential to identify riming, they are not enough larger than measurement biases and case-to-case variability to be confidently used without confirmation from other data sources, such as a vertically pointing radar.

The mean axis ratio (length/width) and the degree of orientation of cloud ice particles are retrieved from radar differential reflectivity (ZDR) and the copolar correlation coefficient (ρhv) measured with the S-band WSR-88D radar. Hardware differential phases and amplifications in the polarimetric channels affect measured ZDR and ρhv and are taken into consideration in the retrieval procedure. The retrieval is performed for particles in shapes of hexagonal prisms, which are closer to shapes of real cloud particles than frequently used spheroids. The median retrieved axis ratio for prisms is larger than that for spheroids. The statistical 1σ retrieval errors caused by fluctuations of radar returns are about 40% in areas of signal-to-noise ratios stronger than 10 dB. The values of the degree of orientation lie in an interval from 2° to 23°, which points to significant perturbations in the orientations of ice particles most likely caused by the wind field.

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 (ZDR) value near 0 dB, and thus CABS can be used as an assessment of ZDR calibration in the absence of excessive contamination from precipitation or biota. An automated algorithm to estimate ZDR 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 ZDR bias assessment tools, especially the use of other external targets, such as light rain and dry snow.The estimates of ZDR 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.

The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown that ZDR bias is time-dependent and can be significantly different on two adjacent days. This means that the frequent monitoring of ZDR bias is necessary, which is difficult to achieve with existing methods. As radar sensitivity has gradually been enhanced, large amounts of online solar echoes have begun to be observed in volume-scan data. Online solar echoes have a high frequency, and a known theoretical value of ZDR (0 dB) could thus allow the continuous monitoring of ZDR bias. However, online solar echoes are also affected by low signal-to-noise ratio and precipitation attenuation for short-wavelength radar. In order to understand the variation of ZDR bias in a C-band polarimetric radar at the Nanjing University of Information Science and Technology (NUIST-CDP), we analyzed the characteristics of online solar echoes from this radar, including the daily frequency of occurrence, the distribution along the radial direction, precipitation attenuation, and fluctuation caused by noise. Then, an automatic method based on online solar echoes was proposed to monitor the daily ZDR bias of the NUIST-CDP. In the proposed method, a one-way differential attenuation correction for solar echoes and a maximum likelihood estimation using a Gaussian model were designed to estimate the optimal daily ZDR bias. The analysis of three months of data from the NUIST-CDP showed the following: (1) Online solar echoes occurred very frequently regardless of precipitation. Under the volume-scan mode, the average number of occurrences was 15 per day and the minimum number was seven. This high frequency could meet the requirements of continuous monitoring of the daily ZDR bias under precipitation and no-rain conditions. (2) The result from the proposed online solar method was significantly linearly correlated with that from the vertical pointing method (observation at an elevation angle of 90&deg, ), with a correlation coefficient of 0.61, suggesting that the proposed method is feasible. (3) The day-to-day variation in the ZDR bias was relatively large, and 32% of such variations exceeded 0.2 dB, meaning that a one-time calibration was not representative in time. Accordingly, continuous calibration will be necessary. (4) The ZDR bias was found to be largely influenced by the ambient temperature, with a large negative correlation between the ZDR bias and the temperature.

Detection of atmospheric hazards that influence onto flight operation is important task of modern radar meteorology. It requires the development of real time methods and algorithms for operational atmospheric hazards detection including wind related phenomena. Many known approaches and algorithms to wind related phenomena detection and estimate operate with averaged data that complicate real-time measurements. For Doppler polarimetric radar, the most developed are models related with motions of water droplets in precipitation and clouds. In this paper the progress in model development introducing water-air-ice mixture additionally to the raindrops is done. Spectral-polarimetric parameters that include Doppler co-polarized spectra, spectral differential reflectivity and correspondent slope lines are studied and analyzed at different wetness parameters and different turbulence intensity values.

This study is the third part of a paper series investigating the polarimetric radar properties of melting hail and application of those properties for operational polarimetric hail detection and determination of its size. The results of theoretical simulations in Part I were used to develop a hail size discrimination algorithm (HSDA) described in Part II. The HSDA uses radar reflectivity Z, differential reflectivity ZDR, and cross-correlation coefficient ρhv along with melting-level height within a fuzzy-logic scheme to distinguish among three hail size classes: small hail (with diameter D < 2.5 cm), large hail (2.5 < D < 5.0 cm), and giant hail (D > 5.0 cm). The HSDA validation is performed using radar data collected by numerous WSR-88D sites and more than 3000 surface hail reports obtained from the Severe Hazards Analysis and Verification Experiment (SHAVE). The original HSDA version was modified in the process of validation, and the modified algorithm demonstrates probability of detection of 0.594, false-alarm ratio of 0.136, and resulting critical success index (CSI) equal to 0.543. The HSDA outperformed the current operational single-polarization hail detection algorithm, which only provides a single hail size estimate per storm and is characterized by CSI equal to 0.324. It is shown that HSDA is particularly sensitive to the quality of ZDR measurements, which might be affected by possible radar miscalibration and anomalously high differential attenuation.

For any quantitative applications that use reflectivity and/or differential reflectivity, radar observations need to be compensated for attenuation effects due to precipitation. This paper presents a robust attenuation correction system (ACS) for dual-polarization radars correcting the reflectivity factor as well as differential reflectivity profiles. The major advantage of the algorithm described in this paper is that the procedures are immune to the bias effect of reflectivity and differential reflectivity. In addition, this method is not very sensitive to the variation of temperature. The proposed ACS has been evaluated with X-band radar observations simulated from drop size distribution derived from high-resolution S-band measurements observed by the CSU-CHILL radar. The evaluation of the proposed retrieval algorithm shows that the retrieved reflectivity and differential reflectivity provide an improvement over the conventional self-consistent attenuation correction technique with the differential phase constraint.

Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on the August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, and unsuitable data. The results are as follows: (1) The radar rain rate equation including specific differential phase was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied.

The Ministry of Land, Infrastructure and Transport (MOLIT) of South Korea operates two S-band dual-polarimetric radars, as of 2013, to manage water resources through quantitative rainfall estimations at the surface level. However, the radar measurements suffer from range ambiguity. In this study, an algorithm based on fuzzy logic is developed to identify range overlaid echoes using seven inputs: standard deviations of differential reflectivity SD(ZDR), differential propagation phase SD(ϕDP), correlation coefficient SD(ρHV) and spectrum width SD(συ), mean of ρHV and συ, and difference of ϕDP from the system offset ΔϕDP. An examination of the algorithm’s performance shows that these echoes can be well identified and that echoes strongly affected by second trip are highlighted by high probabilities, over 0.6; echoes weakly affected have probabilities from 0.4 to 0.6; and those with low probabilities, below 0.4, are assigned as echoes without range ambiguity. A quantitative analysis of a limited number of cases using the usual skill scores shows that when the probability of 0.4 is considered as a threshold for identifying the range overlaid echoes, they can be identified with a probability of detection of 90%, a false alarm rate of 6%, and a critical success index of 84%.

This paper uses RADARSAT-2 quad Polarimetric Synthetic Aperture Radar (PolSAR) and TerraSAR-X dual polarimetric SAR data to monitor agriculture crop growth stages. Two RADARSAT-2 Fine Quad Wide (FQW) beam modes FQ2W and FQ10W, each with 5 sets of data and 13 sets of Stripmap TerraSAR-X data were used in the study. Both RADARSAT-2 POLSAR data and TerraSARX data were acquired in summer 2012 outside Winnipeg, Manitoba, Canada. The study was carried out to two crop types: canola and wheat, each contains 5 regions of interest from ground truth crop classification map in the image scene. Polarimetric features such as differential reflectivity bands ratio, entropy, anisotropy, alpha angle, lambda, scattering diversity and polarization index were evaluated for two crop types. The results from both RADARSAT-2 and TerraSAR-X data were compared and they demonstrated clear relationships between crop growth stages and polarimetric parameters. It is observed that entropy, lambda and differential reflectivity from both data have similar responses to crop growth stages in their common coverage period. The results were also validated using ground truth information.

The effect of ship motion on shipborne polarimetric radar measurements is considered at C band. Calculations are carried out by (i) varying the “effective” mean canting angle and (ii) separately examining the elevation dependence. Scattering from a single oblate hydrometeor is considered at first. Equations are derived (i) to convert the measured differential reflectivity for nonzero mean canting angles to those for zero mean canting angle and (ii) to do the corresponding corrections for nonzero elevation angles. Scattering calculations are also performed using the T-matrix method with measured drop size distributions as input. Dependence on mean volume diameter is examined as well as variations of the four main polarimetric parameters. The results show that as long as the ship movement is limited to a roll of less than about 10°–15°, the effects are tolerable. Furthermore, the results from the scattering simulations have been used to provide equations for correction factors that can be applied to compensate for the “apparent” nonzero canting angles and nonzero elevation angles, so that drop size distribution parameters and rainfall rates can be estimated without any bias.

A method for forecasting very short-term rainfall to detect potentially hazardous convective cloud that produces heavy local rainfall was developed using actual volumetric C-band polarimetric radar data. Because the rainfall estimation algorithm used in this method removed the effect of ice particles based on polarimetric measurements, it was immune to the high reflectivity associated with hail. The reliability of the algorithm was confirmed by comparing the rainfall rate estimated from the polarimetric radar measurements at the lowest elevation angle with that obtained from an optical disdrometer on the ground. The rainfall rate estimated from polarimetric data agreed well with the results obtained from the disdrometer, and was much more reliable than results derived from reflectivity alone. Two small cumulus cells were analyzed, one of which developed and later produced heavy rainfall, whereas the other did not. Observations made by polarimetric radar with a volumetric scan revealed that a high vertical maximum intensity of rainfall rate and a vertical area of enhanced differential reflectivity extending above the freezing level, often termed a high ZDR column, were clearly formed about 10 min prior to the onset of heavy rainfall on the ground. The onset time of the heavy rainfall could be estimated in advance from the polarimetric data, which agreed fairly well with observations. These polarimetric characteristics were not observed for the cumulus cell that did not produce heavy rainfall. The results suggest that both the vertical maximum intensity of the rainfall rate and a high ZDR column, estimated from polarimetric measurements, can be used to identify potentially hazardous clouds. Furthermore, this study shows that polarimetric radar measurements with high spatial and temporal resolutions are invaluable for disaster reduction.

The method for the daily monitoring of the differential reflectivity bias for polarimetric weather radars is developed further. Improved quality control is applied to the solar signals detected during the operational scanning of the radar, which efficiently removes rain and clutter-contaminated gates occurring in the solar hits. The simultaneous reflectivity data are used as a proxy to determine which data points are to be removed. A number of analysis methods to determine the differential reflectivity bias are compared, and methods based on surface fitting are found superior to simple averaging. A separate fit to the reflectivity of the horizontal and vertical polarization channels is recommended because of stability. Separate fitting also provides, in addition to the differential reflectivity bias, the pointing difference of the polarization channels. Data from the Finnish weather radar network show that the pointing difference is less than 0.02° and that the differential reflectivity bias is stable and determined to better than 0.04 dB. The results are compared to those from measurements at vertical incidence, which allows us to determine the total differential reflectivity bias including the differential receiver bias and the transmitter bias.

To improve the understanding of high-latitude rain microphysics and its implications for the remote sensing of rainfall by ground-based and spaceborne radars, raindrop size measurements have been analyzed that were collected over five years with a Joss–Waldvogel disdrometer located in Järvenpää, Finland. The analysis shows that the regional climate is characterized by light rain and small drop size with narrow size distributions and that the mutual relations of drop size distribution parameters differ from those reported at lower latitudes. Radar parameters computed from the distributions demonstrate that the high latitudes are a challenging target for weather radar observations, particularly those employing polarimetric and dual-frequency techniques. Nevertheless, the findings imply that polarimetric ground radars can produce reliable “ground truth” estimates for space observations and identify dual-frequency radars utilizing a W-band channel as promising tools for observing rainfall in the high-latitude climate.

One of the most important avenues of recent meteorological radar research is the application of polarization techniques to improve radar rainfall estimation. A keystone in many of these methods is the so-called differential reflectivity ZDR, the ratio of the reflectivity factor ZH at horizontal polarization backscattered from a horizontally polarized transmission to that corresponding to a vertically polarized transmission ZV. For such quantitative applications, it is important to understand the statistical accuracy of observations of ZDR. The underlying assumption of all past estimations of meteorological radar uncertainties is that the signals obey Rayleigh statistics. It is now evident, however, that as a radar scans, the meteorological conditions no longer always satisfy the requirements for Rayleigh statistics. In this work, ZDR is reconsidered, but this time within the new framework of non-Rayleigh signal statistics. Using Monte Carlo experiments, it is found that clustering of the scatterers multiplies the standard deviation of ZDR beyond what is always calculated assuming Rayleigh statistics. The magnitude of this enhancement depends on the magnitudes of the clustering index and of the cross correlation between ZH and ZV. Also, it does not depend upon the number of independent samples in an ensemble estimate. An example using real radar data in convective showers suggests that non-Rayleigh signal statistics should be taken into account in future implementations of polarization radar rainfall estimation techniques using ZDR. At the very least, it is time to begin to document the prevalence and magnitude of the clustering index in a wide variety of meteorological conditions.

The conventional technique for calibrating Zdr using natural scatterers is based on vertical-looking observations. In some operational weather radar, this method is not applicable because of mechanical constraints that prohibit vertical measurement or choices in the scanning strategies. A technique for calibrating Zdr based on properties of rain returns is proposed and analyzed. The technique is based on an examination of properties of differential reflectivity measurements collected at increasing elevations. Differential reflectivity observed in rain decreases with increasing elevation due to the increasing view angle. Using the hypothesis of uniform microphysical profiles below the bright band, deviations of the profile of differential reflectivity with elevation with respect to the theoretical profile can be used to detect and quantify the presence of a bias on differential reflectivity. To apply this concept in the presence of a nonuniform microphysical profile, the contribution of vertical changes in microphysics to Zdr variation in height is also accounted for. An error parameter associated with the estimated Zdr bias can be used as a quality indicator of the bias estimation; it allows definition of a criterion based on a threshold of root-mean-square error that permits acceptance or rejection of a Zdr bias estimation obtained with the proposed method. The technique is demonstrated using data collected by an operational weather radar at Arpa Piemonte (Italy) and evaluated using independent disdrometer measurement. Results show that under certain conditions discussed in the paper, this method can provide Zdr calibration within an accuracy of 0.1 dB.

Improvement of quantitative precipitation estimation (QPE) is one of the primary benefits providedbypolarization radars. Ministryof Land, Infrastructure and Transportation Japan (MLIT) put Shakadakeoperational Cband Radar to practical use in1992. However, large improvement hadnotbeenrealizedbecause of its initial technical stage.Under these circumstances, first, this paper compares the performance of the conventional R (ZHH) relation and three polarimetric relations, which are R (ZHH, ZDR), R (KDP), R (KDP, ZDR) . At lower rainrates, the combinationof KDP and ZDR is less efficient because KDP becomes noisy. Next in order to improveQPE, a few combinations of estimation equations for operational purpose is proposed, considering thecharacteristic ofthose relations. Also validations with some other algorithms are conducted. As a result, the proposed algorithms improve the estimationof hourly rainfall and accumulated total rainfall.

A series of poststorm surveys were conducted in the wake of hailstorms observed by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU-CHILL) S-Band polarimetric radar. Information on hail characteristics (maximum diameter, building damage, apparent hailstone density, etc.) was solicited from the general-public storm observers that were contacted during the surveys; the locations of their observations were determined using GPS equipment. Low-elevation angle radar measurements of reflectivity, differential reflectivity ZDR, and linear depolarization ratio (LDR) were interpolated to the ground-observer locations. Relationships between the hail differential reflectivity parameter HDR and the observer-reported hail characteristics were examined. It was found that HDR thresholds of 21 and 30 dB were reasonably successful (critical success index values of ∼0.77) in respectively identifying regions where large (>19 mm in diameter) and structurally damaging hail were observed. The LDR characteristics in the observed hail areas were also examined. Because of sensitivities to variations in the hailstone bulk ice density, degree of surface wetness, and shape irregularities, the basic correlation between LDR magnitude and hail diameter was poor. However, when the reported hail diameters exceeded ∼25 mm, LDR levels below ∼−24 dB were uncommon.

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.

In this paper, the attenuation-correction methodology presented in Part I is applied to radar measurements observed by the multiparameter radar at the X-band wavelength (MP-X) of the National Research Institute for Earth Science and Disaster Prevention (NIED), and is evaluated by comparison with scattering simulations using ground-based disdrometer data. Further, effects of attenuation on the estimation of rainfall amounts and drop size distribution parameters are also investigated. The joint variability of the corrected reflectivity and differential reflectivity show good agreement with scattering simulations. In addition, specific attenuation and differential attenuation, which are derived in the correction procedure, show good agreement with scattering simulations. In addition, a composite rainfall-rate algorithm is proposed and evaluated by comparison with eight gauges. The radar-rainfall estimates from the uncorrected (or observed) ZH produce severe underestimation, even at short ranges from the radar and for stratiform rain events. On the contrary, the reflectivity-based rainfall estimates from the attenuation-corrected ZH does not show such severe underestimation and does show better agreement with rain gauge measurements. More accurate rainfall amounts can be obtained from a simple composite algorithm based on specific differential phase KDP, with the R(ZH_cor) estimates being used for low rainfall rates (KDP ≤ 0.3° km−1 or ZH_cor ≤ 35 dBZ). This improvement in accuracy of rainfall estimation based on KDP is a result of the insensitivity of the rainfall algorithm to natural variations of drop size distributions (DSDs). The ZH, ZDR, and KDP data are also used to infer the parameters (median volume diameter D0 and normalized intercept parameter Nw) of a normalized gamma DSD. The retrieval of D0 and Nw from the corrected radar data show good agreement with those from disdrometer data in terms of the respective relative frequency histograms. The results of this study demonstrate that high-quality hydrometeorological information on rain events such as rainfall amounts and DSDs can be derived from X-band polarimetric radars.

Techniques for the absolute calibration of radar reflectivity Z and differential reflectivity ZDR measured with dual-polarization weather radars are examined herein. Calibration of Z is based on the idea of self-consistency among Z, ZDR, and the specific differential phase KDP in rain. Extensive spatial and temporal averaging is used to derive the average values of ZDR and KDP for each 1 dB step in Z. Such averaging substantially reduces the standard error of the KDP estimate so the technique can be used for a wide range of rain intensities, including light rain. In this paper, the performance of different consistency relations is analyzed and a new self-consistency methodology is suggested. The proposed scheme substantially reduces the impact of variability in the drop size distribution and raindrop shape on the quality of the Z calibration. The new calibration technique was tested on a large polarimetric dataset obtained during the Joint Polarization Experiment in Oklahoma and yielded an accuracy of Z calibration within 1 dB. Absolute calibration of ZDR is performed using solar measurements at orthogonal polarizations and polarimetric properties of natural targets like light rain and dry aggregated snow that are probed at high elevation angles. Because vertical sounding is prohibited for operational Weather Surveillance Radar-1988 Doppler (WSR-88D) radars because of mechanical constraints, the existing methodology for ZDR calibration is modified for nonzenith elevation angles. It is shown that the required 0.1–0.2-dB accuracy of the ZDR calibration is potentially achievable.

Error characteristics of rainfall measurements were studied using six collocated Joss–Waldvogel (JW) disdrometers that are located at NASA’s Wallops Flight Facility. The six disdrometer means of rain rate R, reflectivity Z, and differential reflectivity ZDR, for a given minute were considered as a reference. The maximum deviations of R, Z, and ZDR from the mean in a rain event were 0.6 mm h−1, 1.3 dB, and 0.05 dB, respectively. Rainfall statistics were then examined between disdrometer pairs. The root-mean-square (rms) difference of R, Z, and ZDR between paired disdrometers in a rain event were as high as 3.2 mm h−1, 3.7 dB, and 0.3 dB, respectively. The rms difference of R and ZDR were even higher when the disdrometer observations were stratified based on reflectivity intervals. The differences in disdrometer rainfall measurements have a potential impact when the disdrometers are considered as calibration tools for vertically pointing and scanning radars. The differences between the disdrometer measurements also result in differences in coefficients and exponents of the derived relations between radar parameters and rain rate. Among the four different relations between radar parameters and rain rate, the absolute difference in rain rate |ΔR| from two different JW disdrometers was highest in R(ZH, ZDR) and lowest in R(KDP, ZDR). The other two relations were R(Z) and R(KDP). The |ΔR| increases with increasing horizontally polarized reflectivity ZH, and differential specific phase KDP in both single- and dual-parameter rainfall estimators, while the |ΔR| increases with decreasing ZDR in dual-parameter rainfall estimators. Several sources of JW disdrometer malfunctions were also presented. The hardware problems were the leading cause for the malfunction of the JW disdrometers, as identified by the manufacturer. A single JW disdrometer could have inherent measurement errors that can only be identified in the presence of collocated (preferably two) rain-measuring instruments.

This article presents an algorithm to correct the increase in reflectivity in the melting layer using weather radars. The correction starts with a fuzzy logic system (FLS) to classify rain, snow and melting snow using the reflectivity factor, the differential reflectivity, the linear depolarisation ratio and the height of the measurement from the ground surface. Using the output of the FLS, a correction is performed on the bright band contaminated reflectivity data assuming an idealised vertical reflectivity profile typical from stratiform precipitation and obtained from a considerable number of observations at S-band frequencies. Copyright © 2005 Royal Meteorological Society

Original article can be found at : http://www3.interscience.wiley.com/ Copyright Royal Meterological Society / John Wiley & Sons [Full text of this article is not available in the UHRA]

The paper presents a rainfall estimation technique based on algorithms that couple, along a radar ray, profiles of horizontal polarization reflectivity (ZH), differential reflectivity (ZDR), and differential propagation phase shift (ΦDP) from X-band polarimetric radar measurements. Based on in situ raindrop size distribution (DSD) data and using a three-parameter “normalized” gamma DSD model, relationships are derived that correct X-band reflectivity profiles for specific and differential attenuation, while simultaneously retrieving variations of the normalized intercept DSD parameter (Nw). The algorithm employs an iterative scheme to intrinsically account for raindrop oblateness variations from equilibrium condition. The study is facilitated from a field experiment conducted in the period October–November 2001 in Iowa City, Iowa, where observations from X-band dual-polarization mobile radar (XPOL) were collected simultaneously with high-resolution in situ disdrometer and rain-gauge rainfall meas...

Multiparameter radar measurements of rainfall, namely, reflectivity factor Z/sub H/, differential reflectivity Z/sub DR/, and specific differential phase K/sub DP/ lie in a constrained three-dimensional (3D) space and therefore measurement of Z/sub H/, Z/sub DR/, or, K/sub DP/ should be consistent with the other two. This self-consistency relationship between Z/sub H/, Z/sub DR/, and K/sub DP/ is valid when the radar resolution volume is homogeneous. When there are reflectivity gradients within the radar resolution cell, the self-consistency relation is perturbed. This perturbation can be utilized to detect the presence of gradients in the radar resolution volume. This paper presents a technique to detect and estimate reflectivity gradients in the resolution cell. The technique is evaluated using theoretical analysis as well as experimental data collected by the NCAR CP-2 radar. It is demonstrated that the presence of reflectivity gradients larger than a few decibels can be detected using the algorithm developed in this paper.

The joint distribution characteristics of size and shape of raindrops directly translate into features of polarization diversity measurements in rainfall. Theoretical calculations as well as radar observations indicate that the three polarization diversity measurements, namely, reflectivity, differential reflectivity, and specific differential propagation phase, lie in a constrained space that can be approximated by a three-dimensional (3D) surface. This feature as well as the vertical-looking observation of raindrops are used to determine biases in calibration of the radar system. A simple procedure is developed to obtain the bias in the absolute calibration from polarization diversity observation in rainfall. Simulation study as well as data analysis indicate that calibration errors can be estimated to an accuracy of 1 dB.

The Communications Research Laboratory (CRL) has developed a simultaneous reception Ku-band dual-polarization radar. Simultaneous reception can give high accuracy of the differential reflectivity (ZDR) measurement from fewer averaged samples because of a good correlation between simultaneously sampled horizontal and vertical reflectivity. This paper pursues the possibility of estimating the rainfall rate using ZDR alone by comparison with a conventional polarimetric radar algorithm using ZDR and ZH on the assumption of the data handling of a CRL's dual-polarization radar. A computer simulation based on a physical raindrop model is used to pursue this possibility. The results show that estimating the rainfall rate using ZDR alone is not a good method.

Combined measurements of differential reflectivity and cross-correlation coefficient between linear copolar components of weather radar returns have been obtained with a noncoherent X-band polarimetric meteorological radar. In examining these data, special attention is devoted to the problem of discrimination between liquid and solid hydrometeors and to identification of the areas of strong ground-clutter contamination. Furthermore, polarization parameters of backscattered signals are used to locate updrafts.

The estimates of rainfall rate derived from a multiparameter radar based on reflectivity factor (R sub ZH), differential reflectivity (R sub DR), and specific differential propagation phase (R sub DP) have widely varying accuracies over the dynamic range of the natural occurrence of rainfall. This paper presents a framework to optimally combine the three estimates, R sub zH, R sub DR, and R sub DP, to derive the best estimate of rainfall using coherent multiparameter radars. The optimization procedure is demonstrated for application to multiparameter radar measurements at C band.

Several types of remote sensing data are applied synergistically to evaluate the chain of microphysical processes leading to precipitation in a high-resolution numerical weather prediction model. The data provides information relating to (i) cloud-top temperature and optical depth (SEVERI), (ii) ice cloud amount (AMSUB), (iii) type and amount of precipitation particles (polarimetric radar), and (iv) surface precipitation (raingauge-calibrated radar data). Forecasts are produced by the COSMO-DE model of the German weather service, with a horizontal resolution of 2.8 km. The comparison with data is done in a model-to-observation framework, that is, forward operators are applied to the model output to produce synthetic data sets that can be directly compared to the observations. Additional diagnostics based on diurnal cycle and system tracking are also considered. Two case studies over Germany from the summer of 2006 are examined. The first case is dominated by widespread stratiform precipitation. Together the various data sets show that the model overestimates the amount of high cloud, while underestimating the concentration of ice scatterers and overestimating reflectivity and differential reflectivity (ZDR). This indicates errors in both the amount and the size distributions of cloud and precipitation particles in the model’s microphysical parameterization. In the second case a narrow band of convective precipitation is embedded in a cold front, with significant modulation by the diurnal cycle. The model fails to show a significant diurnal cycle in cloud amount, and the timing and duration of convective cells is incorrect. In this case, both the microphysical parameterization, and errors in the interaction of the simulated front with the orography of the Alps appear to contribute. These results demonstrate the potential of combinations of remote sensing data for model evaluation, although a long-term trial will be required to determine whether the errors seen in the case studies are characteristic for COSMO-DE. Zusammenfassung Verschiedene Fernerkundungsdaten werden synergetisch zur Evaluierung der mikrophysikalischen Prozesskette der Niederschlagsgenerierung in einem hochaufgelosten numerischen Wettervorhersagemodell genutzt. Die Daten beinhalten Informationen uber (i) Wolkenobergrenzentemperatur und optische Dicke (SEVIRI), (ii) Vorkommen von Eis und Schnee (AMSU), (iii) Art und Gehalt an Niederschlagspartikeln (polarimetrisches Radar) und (iv) Bodenniederschlag (Radar mit Niederschlagssammler kalibriert). Die Vorhersagen stammen vom COSMO-DE des Deutschen Wetterdiensts mit einer horizontalen Auflosung von 2,8 km. Der Vergleich wird mittels eines “Modell zu Beobachtung”-Ansatzes durchgefuhrt, d. h. Vorwartsoperatoren werden auf den Modelloutput angewendet, um synthetische Beobachtungen zu generieren, die direkt mit den Beobachtungen verglichen werden konnen. Zusatzliche Diagnostiken basierend auf Tagesgang und Verfolgung einzelner Konvektionszellen werden ebenfalls angewendet. Zwei Fallstudien uber Deutschland aus dem Sommer 2006 werden untersucht. Die erste Fallstudie wird von ausgedehntem Niederschlag dominiert. Die verschiedenen Daten zeigen, dass das Modell den Anteil hoher, stratiformer Wolken uberschatzt, wahrend die Konzentration groserer streuender Eispartikel unter- und die bodennahe Reflektivitat und die differentielle Reflektivitat (ZDR) uberschatzt werden. Dies deutet auf Fehler in den mikrophysikalischen Parameterisierungen sowie in den Annahmen zur Grosenverteilung von Wolken- und Niederschlagspartikeln im Modell hin. In der zweiten Fallstudie ist ein enges Band konvektiven Niederschlages eingebettet in eine Kaltfront, mit signifikanter Modulation durch den Tagesgang. Dem Modell gelingt es nicht einen deutlichen Tagesgang in der Wolkenbedeckung zu reproduzieren und Einsetzen sowie Lebensdauer der konvektiven Zellen werden nicht getroffen. In diesem Fall scheinen sowohl die mikrophysikalischen Parametrisierungen als auch die Wechselwirkung der Front mit der Orographie der Alpen zum Fehler der Vorhersage beizutragen. Diese Resultate zeigen das Potential der Kombination verschiedener Fernerkundungsdaten fur die Modellevaluierung. Um zu uberprufen, dass diese Fehler charakteristisch fur das COSMO-DE sind, ist jedoch eine langfristige Vergleichsstudie notig.

Dual polarization radar measurements of rainfall parameters are based on the assumption of a mean shape-size relationship of raindrops. This paper focuses on retrieving and interpreting the mean raindrop shape-size relation from polarimetric radar observations. A procedure to retrieve the drop shape-size relation that governs the polarimetric radar observations of reflectivity (Z h ) differential reflectivity (Z dr ) and specific differential propagation phase (K dp ) is presented. The mean drop shape-size relations retrieved from measurements collected by the NCAR SPOL radar during three campaigns are analyzed to explore whether the natural raindrop shape-size relation can be described by a unique model.

Dual-polarization radar measurements of precipitation are primarily influenced by the size, shape, orientation, and phase of scattering hydrometeors. As a result, these measurements can serve as a tool for remote identification of hydrometeor characteristics. This paper presents an overview of the definitions, observed values, and applications of differential reflectivity (ZDR) and linear depolarization ratio (LDR) measurements. Brief examples of these measurements are given for widespread stratiform precipitation, a rapidly developing convective cell, and a severe hailstorm. The results outline the role that ZDR can play in the differentiation of rain and solid precipitation, identification of supercooled raindrops above the 0°C level, and identification of hail at the surface. LDR measurements are seen to reveal contrasts in ice-particle shape, orientation, and particle phase. These contrasts are of particular benefit toward delineation of hail regions aloft and identification of mixed-phase particle gr...

Recent advances in the radar system design allow to perform Doppler and polarimetric measurements simultaneously. This paper considers behavior of a Doppler-polarimetric parameter - spectral differential reflectivity and its characteristics. Slope of differential reflectivity which is connected with turbulence intensity in rain zone is considered using real data processing.

We examine the utility of the correlation coefficient between linear orthogonally polarized echoes for determining precipitation type and gauging hail size. Models and measurements from pure rain coincide in predicting very high correlations (0.98); similar results are obtained with pure hail. Several mechanisms could cause the lowering of correlation but the behavior of the examined data is definitely attributed to a mixture of hydrometeor types. This decrease is an indicator of hail size; it is shown theoretically that in at least two other realistic situations the correlation would decrease with hail size. For the examined case a model of hail shape and orientation during fall is able to reproduce the essential features of polarimetric measurements. It suggests, together with our data and data from other investigators, that substantial negative differential reflectivity (about −1 dB) in a region of high reflectivity factor values is caused by hailstones larger than about 2 cm in diameter.

[1] Several authors have reported the correlation between the shape (μ) and slope (Λ) of the gamma distribution of raindrops to reduce the number of parameters required to measure rainfall by remote sensing methods. However, we find that there are no well-defined μ-Λ, or associated relations between reflectivity (Z) and rain rate (R) or differential reflectivity for all storms or portions thereof. Rather, there is a general behavior such that A and b (in the Z = ARb relation) and median volume drop diameter Do all decrease from convective (C) to stratiform (S) to transition (T) rains. The μ-Λ correlation of the investigators in question appears to be limited to rainfall events which do not include convective rain; it is biased toward S and T rains. They miss the narrow (large μ), large Do DSDs of convective rain that are often found to have equilibrium spectra. The dependence of Do on the strength of the updraft and the findings of others concerning the association with the physics, dynamics, and climate regime strongly suggests that it is necessary to characterize the physical and dynamic nature of the storms in order to select the appropriate remote sensing algorithms.

Strong radar echoes from targets a few kilometres across have been found in the absence of rain, and were attributable to burnt straw particles rising from large field fires. The echoes showed a marked difference of reflectivity between horizontally and vertically polarised radar transmissions. This paper describes the way the reflectivity and differential reflectivity with polarisation are distributed in space, gives a theoretical model to explain these effects, and analyses the basic propagation characteristics.

The polarimetric technique consists of simultaneous transmission and reception of Horizontally and Vertically polarized waves. Thus, transmitted polarization will be elliptical with equal horizontal and vertical components and arbitrary phase between the two. This scheme has been tested at NSSL on the NOAA research and development WSR-88D radar. Here reports on backscatter differential phase measurements with this radar. The radar also has a mode of transmitting horizontal polarization and receiving both the strong H and the weak V component (for short we refer to this mode as Linear Depolarization Ratio mode, LDR). Backscatter differential phase is considered a secondary polarimetric variable of lesser value for precipitation measurements than (the forward) specific differential phase or differential reflectivity. This is because backscatter differential phase is seldom significant. At 10 cm wavelength the only precipitation that can cause appreciable backscatter differential phase is hail. But it turns out that backscatter differential phase from other scatters provides two benefits. (1) it is suitable for discrimination between nonmeteorological scatters and precipitation and (2) it offers a way to calibrate (measure) the system differential phase. Of relevant and special importance is that, for some scatters, the measured total differential phase in the SHV scheme can differ from the value obtained in the sequential H, V scheme. The radar system contributes two distinct phases to the total differential phase. One is the differential phase in the transmission channel, the other is the differential phase in the receiver channel

estimated from power measurements. Comparison of the direct estimate of propagation phase (F m ) measurement, which is unaffected by absolute calibration of the radar system, with the estimated propagation phase (F e ) from power measurements is the basis for the calibration method. Polarization measurements such as reflectivity (Z ), differential reflectivity (ZDR), and differential propagation phase (FDP) are sensitive to drop size distribution (DSD) and mean drop shape. It is important to devise a calibration technique relatively unperturbed by changes in DSD and drop shape. Statistical fluctuation in F e is derived to estimate the accuracy of the calibration procedure, raindrop shape, and attenuation. The proposed method is applied for calibrating reflectivity measurements of the National Center for Atmospheric Research (NCAR) S-band polarization radar (S-Pol) in midlatitude, subtropical, and tropical rain events. INDEX TERMS: 3354 Meteorology and Atmospheric Dynamics: Precipitation (1854); 3360 Meteorology and Atmospheric Dynamics: Remote sensing; 3394 Meteorology and Atmospheric Dynamics: Instruments and techniques; 6904 Radio Science: Atmospheric propagation; 6969 Radio Science: Remote sensing; KEYWORDS: polarization radar calibration, reflectivity, differential reflectivity, differential phase, raindrop size distribution

The purpose of this paper is to present details of the meteorological radar algorithm for classification of hydrometeors and a methodology for sensitivity analysis to the various polarimetric variables used for classification. The classification algorithm described belongs to the "fuzzy logic" family. In its essence a classifier assigns (maps) an observed point X in the multiparameter space to a class j (which refers to the bulk hydrometeor type such as rain, hail, graupel, snow, etc.). In this paper the point X has for coordinates the following six variables: (1) the reflectivity factor for horizontally polarized waves Z/sub h/, (2) the differential reflectivity Z/sub DR/, (3) the specific differential phase K/sub DP/, (4) the cross correlation coefficient between the horizontally and vertically polarized (copolar) waves /spl rho//sub hv/(0), (5) the linear depolarization ratio L/sub DR/, and (6) the environmental temperature T. The crux of a hydrometeor classification scheme is to partition this six-dimensional space of observed variables into subsets such that each can be associated with a specific hydrometeor type (j). An obvious solution is to decouple the variables and consider each individually and then make a final judgement on the basis of weighted averages.

Errors arise when using conventional radar reflectivity, Z, to estimate rainfall rate, R, and these can be particularly severe during severe convective storms; the very events when accurate estimates are needed so that action can be taken to mitigate the effects of flooding. Concentration is on three problems associated with heavy rainfall: hail, attenuation and absolute calibration of the radar, and consider how polarisation radar parameters, differential reflectivity, ZDR, and specific differential phase shift KDP, might lead to their alleviation. It is essential to consider the fundamental limits to the accuracy with which these parameters can be estimated. If ZDR can be measured to an accuracy of 0.2 dB, then it provides a measure of mean raindrop shape which is sufficiently precise to improve rainrate estimates. This can be achieved at S-band (10 cm), but seems very difficult for operational C-band (5 cm) radars; differential attenuation by the heavy rain introduces a negative bias into ZDR which increases with range. However, the magnitude of this bias at C-band can then be used to correct for the total attenuation of Z. Differential phase, KDP has the advantage that it is a phase measurement and so is unaffected by attenuation. It only responds to the rainfall and is unaffected by the hail, but KDP is a noisy parameter and is only useful for heavy rainfall above 30 – 60 mm hr-1. Fortuitously, KDP and ZDR are not independent and one use of KDP and ZDR may well be to exploit this redundancy to identify rain areas as opposed to hail, and in rainfall to use the redundancy to provide an automatic calibration of the absolute reflectivity, Z, to 0.5 dB (12%). Finally, the noisy character of both ZDR and KDP together with the low level of the co-polar correlation coefficient provide the first reliable means of detecting and removing anomalous propagation which is a major operational problem for all weather radars. Keywords: polarisation radar, rainfall calibration, attenuation, hail, anomalous propagation

For a long time, radars have been used extensively for both meteorological and hydrological applications, including remote-sensing of rainfall, warning of severe weather and flash flood prediction. Today, most weather radars installed in European countries operate at C-band, mainly to reduce costs. However, at this frequency, the advantage is often offset by the effect of attenuation caused by the intervening rainfall. An improved method to correct attenuation using reflectivity (Z/sub H/) and differential reflectivity (Z/sub DR/) is developed and described. The technique relies on the fact that, for an exponential raindrop size distribution, the measured Z/sub DR/ results in an overestimated median drop diameter (D/sub 0/), whereas the measured Z/sub H/ yields a under-estimated N/sub 0/. The estimated (N/sub 0/D/sub 0/) pair can then be used to obtained attenuation parameters which are close to those that would have been derived from true Z/sub H//Z/sub DR/ values.

Small time (1 to 15 min) and space (0.5 to 1.5 km) measurements of the mean rainfall rate have been made within 10 km from a dual polarization radar, during several stratiform and convective precipitation events. At first, the time and space characteristic scales of the gage and of the radar data are evaluated in order to find the minimum time interval Δt and spatial resolution Δx for which the mean rainfall rate values have a large enough statistical significance. Then, the quantitative comparisons are made between the mean rainfall rate deduced from the gage data and that deduced from the radar measurements, either without or with using the differential reflectivity Z DR . During the same experiments, the hailfall parameters (total hailstone number N t , total hailfall kinetic energy E t ) have been estimated from the data of a hailpad network situated within 30 km from the radar. The values of these hailfall parameters have been approximated by functions of several radar parameters, deduced from the time evolution of the radar reflectivities (Z H and Z DR ) above each hailpad.

The performance of an S-band dual-polarisation meteorological radar is investigated using a physically-based radar simulator, in particular, the impact of the drop size distribution on the variance of the estimate of differential reflectivity (Z/sub DR/) is addressed and discussed.