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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.

On the evening of 30 April 2021, a severe hailstorm swept across eastern China, causing catastrophic gale and damaging hailstones. This hailstorm event was directly caused by two mesoscale convective systems associated with strong squall lines, with mid-level cold advection from the northeast cold vortex, and strong low-level convergence associated with the low-level vortex and wind shear line. Double nesting of the high-resolution weather research and forecasting model (9–1 km) is utilized to simulate this hailstorm with five microphysics schemes. The radar-based maximum estimated size of hail (MESH) algorithm, differential reflectivity and fractions skill scores were used to quantitatively evaluate the precision. All schemes basically captured the two squall lines that swept through eastern China, although they appeared one or two hours earlier than observation. Particularly, Goddard and Thompson performed better in the MESH swath and fractions skill scores among the five different schemes. However, Thompson most realistically captured the reflectivity pattern, intensity and vertical structure of mesoscale convective systems. Its high-reflectivity column corresponded to the maximum center of the hail mixing ratio within the updraft region, which is consistent with the characteristics of a pulse-type hailstorm in its mature phase.

This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. In the present study, two experiments are performed, one assimilating only Z and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the forecast of the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which deserves more research in the future.

A water-logging disaster occurred in Eastern China on 1 June 2016 was utilized to investigate the practical performance of six radar rainfall estimators based on horizontal reflectivity ( $Z_{\mathrm{H}}$ ), specific attenuation ( $A_{\mathrm{H}}$ ), specific differential phase ( $K_{\text{DP}}$ ), and multi-variable estimators that integrate differential reflectivity ( $Z_{\text{DR}}$ ), namely $R(Z_{\mathrm{H}},\, Z_{\text{DR}}), R(K_{\text{DP}}, Z_{\text{DR}})$ and $R(A_{\mathrm{H}}, Z_{\text{DR}})$ . Detailed evaluation with a local rain gauge network and drop size distribution (DSD) measurements shows that (i) $R(A_{\mathrm{H}},\, Z_{\text{DR}})$ underestimates the light rain pattern, but it achieves the best scores and performs the best among the various estimators; (ii) each radar rainfall estimator can outperform other estimators at a certain period of time determined by the rainfall patterns; (iii) both the optimal radar rainfall relationship and high calibration accuracy are required to obtain accurate rainfall estimates; (iv) the contamination of melting solid hydrometeors on $A_{\mathrm{H}} \text{and}/\text{or}K_{\text{DP}}$ may make them less effective than $Z_{\mathrm{H}}$ . In addition, with appropriate adjustment of $\alpha$ coefficient, $R(A_{\mathrm{H}})$ can perform better than $R(K_{\text{DP}})$ .

Conventionally, the short term prediction of precipitation (or nowcast) observed by a network of weather radars is conducted by means of advection schemes. Such schemes often lead to underestimated areas of predicted precipitation cells and they do not include the vertical structure of the cells, which can carry important information on the evolution of precipitation. To mitigate such limitations on nowcasts, storm cells have been treated as 3D targets, allowing the exploitation of their vertical and dynamic structure. In this work, storm cell targets are identified and tracked from 2D reflectivity nationwide fields collected by the German meteorological service DWD. Then, the vertical structure of the cells are analyzed in terms of the polarimetric-based differential reflectivity Z DR -column, which is a predictor of potential changes in precipitation. Knowing the location and tendency of storm cells and their associated Z DR columns, the nowcast skills can be further improved, mainly in localized regions.

This paper discusses the effects of cross-polar radiation on the calibration methods usually employed for the calibration of the differential reflectivity. It is shown that cross-polar radiation has significant effects when simultaneous transmission and reception of horizontal and vertical polarizations are used to obtain polarimetric measurements. Additionally, it is shown that propagation through a transpolarizing medium considerably affects the results.

Based on Jiangsu X-band dual-line polarization radar data, $\mathrm{Z}_{\mathrm{H}}$ (radar horizontal reflectance factor), $\mathrm{Z}_{\mathrm{D}\mathrm{R}}$ (differential reflectivity factor), $\mathrm{K}_{\mathrm{D}\mathrm{P}}$ (differential propagation phase shift), $\mathrm{p}_{\mathrm{H}\mathrm{V}}(0)$ (zero lag) are selected using a fuzzy logic algorithm The number of correlations) and other four parameters were used to establish a precipitation particle phase recognition algorithm, and a typical case was used to test and evaluate the effect of the algorithm's phase recognition. Through analysis, the author believes that: (1) The algorithm can basically reflect the phase states of various precipitation particles, indicating that the precipitation particle recognition algorithm established in this paper has strong applicability and the recognition results are credible. (2) This algorithm does not consider the zero-degree layer height and the ambient temperature of each layer, which results in a large recognition error in individual areas. The next step is to use the ambient temperature as an input and use $\mathrm{Z}_{\mathrm{H}}$, $\mathrm{Z}_{\mathrm{D}\mathrm{R}}$, $\mathrm{K}_{\mathrm{D}\mathrm{P}}$, The construction of membership function with $\mathrm{p}_{\mathrm{H}\mathrm{V}}(0)$ and ambient temperature T should further improve the accuracy of phase identification. (3) The results of the precipitation particle identification are closely related to the parameter settings of the membership functions of the 10 types of water condensate types, and the setting of these parameters is very subjective. A large number of individual statistics are needed to obtain more reliable parameter values.

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.

In this study, empirical A H -K DP and A DP -K DP relationship-based and self-consistent methods were used to correct the attenuation of reflectivity (z h ) and differential reflectivity (Z DR ) acquired from C- and X-bands dualpolarization radars, and the Z h of S-band Doppler radar was used to evaluate the results. The results indicated that, for Xband dual-polarization radar, the attenuation of Z h and Z DR could be corrected by two methods for heavy and moderate rain, and the distribution of Z h -Z DR scatters were closer to the theoretical relationship after self-consistent correction than that after empirical A H -K DP and A DP -K DP relationship-based correction. For light rain, similar results were obtained for two methods. For C-band dual-polarization radar, the degree of attenuation was less than X-band dual-polarization radar for the same intensity of rainfall, and the attenuation was need to be considered in heavy and moderate rain. For heavy rain, the distribution of Z h -Z DR scatters were closer to the theoretical relationship after empirical A H -K DP and A DP -K DP relationship based correction than that after self-consistent correction. For moderate rain, similar results were obtained for two methods. The corrected reflectivity of C-band dual-polarization radar was closer to that of S-band Doppler radar, however, for X-band dual-polarization radar, it was 5.10 dB larger than that of Sband Doppler radar in heavy rain, 4.64 dB in moderate rain, and 3.34 dB in light rain. It was consistent with the scattering simulation results of other scholars.

This study investigates Bragg scatter signatures in dual-polarization radar observations, which are defined by low differential reflectivity values, as a proxy for convective boundary layer (CBL) depth. Using data from the WSR-88D in Twin Lakes, Oklahoma (KTLX), local minima in quasi-vertical profiles of are found to provide a reasonable estimate of CBL depth when compared with depth estimates from upper-air soundings from Norman, Oklahoma (KOUN), during 2014. The 243 Bragg scatter and upper-air sounding CBL depth estimates have a correlation of 0.90 and an RMSE of 254 m. Using Bragg scatter as a proxy for CBL depth was expanded to other seasons and locations—performing well in Wilmington, Ohio; Fairbanks, Alaska; Tucson, Arizona; Minneapolis, Minnesota; Albany, New York; Portland, Oregon; and Tampa, Florida—showing its potential usefulness in monitoring CBL depth throughout the year in a variety of geographic locations and meteorological conditions.

Mechanisms of formation of differential reflectivity columns are investigated in simulations of a midlatitude summertime hailstorm with hailstones up to several centimeters in diameter. Simulations are performed using a new version of the Hebrew University Cloud Model (HUCM) with spectral bin microphysics. A polarimetric radar forward operator is used to calculate radar reflectivity and differential reflectivity ZDR. It is shown that ZDR columns are associated with raindrops and with hail particles growing in a wet growth regime within convective updrafts. The height and volume of ZDR columns increases with an increase in aerosol concentration. Small hail forming under clean conditions grows in updrafts largely in a dry growth regime corresponding to low ZDR. Characteristics of ZDR columns are highly correlated with vertical velocity, hail size, and aerosol concentration.

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.

This study implements a new quasi-vertical profile (QVP) methodology to investigate the microphysical evolution and significance of intriguing winter polarimetric signatures and their statistical correlations. QVPs of transitional stratiform and pure snow precipitation are analyzed using WSR-88D S-band data, alongside their corresponding environmental thermodynamic High-Resolution Rapid Refresh model analyses. QVPs of KDP and ZDR are implemented to demonstrate their value in interpreting elevated ice processes. Several fascinating and repetitive signatures are observed in the QVPs for differential reflectivity ZDR and specific differential phase KDP, in the dendritic growth layer (DGL), and at the tops of clouds. The most striking feature is maximum ZDR (up to 6 dB) in the DGL occurring near the −10-dBZ ZH contour within low KDP and during shallower and warmer cloud tops. Conversely, maximum KDP (up to 0.3° km−1) in the DGL occurs within low ZDR and during taller and colder cloud tops. Essentially, ZDR and KDP in the DGL are anticorrelated and strongly depend on cloud-top temperature. Analyses also show correlations indicating larger ZDR within lower ZH in the DGL and larger KDP within greater ZH in the DGL. The high-ZDR regions are likely dominated by growth of a mixture of highly oblate dendrites and/or hexagonal plates, or prolate needles. Regions of high KDP are expected to be overwhelmed with snow aggregates and crystals with irregular or nearly spherical shapes, seeded at cloud tops. Furthermore, QVP indications of hexagonal plate crystals within the DGL are verified using in situ microphysical measurements, demonstrating the reliability of QVPs in evaluating ice microphysics in upper regions of winter clouds.

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.

Comprehensive analysis of an unusual graupel-shower event recorded by an S-band polarimetric radar and two optical-imaging surface instruments is presented. The primary radar characteristic was negative differential reflectivity Zdr values along a vertical column. During the afternoon hours of 16 February 2015, a sequence of three showers that were composed primarily of small (8–15-mm diameter) graupel affected the ground instrumentation site that was established for the Multi-Angle Snowflake Camera and Radar (MASCRAD) experiment in the high plains of Colorado. While these showers passed the instrumentation site, the CSU–CHILL radar conducted high-time-resolution (~2.5-min cycle time) range–height indicator (RHI) scans from a range of 13 km. The RHI data show that the negative Zdr values extended vertically through much of the reflectivity cores, implying that the reflectivity-weighted mean axis ratios of the graupel particles in this event remained somewhat prolate throughout their lifetime. To be specific, the cores of the convective showers only extended to heights of ~3.5 km AGL and had fractionally negative (from ~−0.3 to −0.7 dB) Zdr levels in those cores. Particle-image data obtained by the MASC system and by a collocated 2D video disdrometer measured the diameters, shapes, and fall speeds of the graupel particles as they reached the surface. The graupel particles were found to be primarily of the lump type with a slightly prolate mean shape (especially for the larger-diameter particles). Microwave backscatter calculations confirm that the graupel-particle shape and orientation characteristics are consistent with the observed slightly, but consistently, negative Zdr values.

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.

The coupling between the metal–insulator transition (MIT) and the structural phase transition (SPT) in VO2 has been at the center of discussion for several decades, while the underlying mechanisms of electron–lattice or electron–electron interactions remain an open question. Until recently, the equilibrium state VO2 is believed to be a non-standard Mott–Hubbard system, i.e., both of the two interactions cooperatively work on MIT, indicating the association between MIT and SPT. However, due to the pronounced contribution of strain in strongly correlated systems, it is desirable to explore the correspondence in an interface-engineered VO2. Herein, we investigate the carrier dynamics in the VO2 films with anomalous MIT on the basis of time-resolved transient differential reflectivity measurements. Unexpectedly, MIT is decoupled from SPT, in sharp contrast with the case of strain-free VO2 films: MIT is triggered by bandgap recombination below 75 °C during heating, while intense SPT-induced signal appears separately between 70 °C and 100 °C. The decoupling between MIT and SPT provides insights into the interfacial interactions in VO2 thin films.

This study analyzes radar observations of evaporation in rain and investigates its impact on surface rainfall and atmospheric cooling rates. A 1D model is used to examine the impact of raindrop evaporation on the evolution of the initial raindrop size distribution (DSD), the resulting reflectivity (Z), and differential reflectivity (ZDR) and surface rain rates. Raindrop evaporation leads to a decrease of Z and an increase of ZDR toward the surface because of the depletion of small raindrops that evaporate first and thus enhance the mean raindrop size. The latter effect, however, can be reduced because of the increasing temperature toward the surface and may even lead to a decrease of ZDR toward the surface. Two events with significant rain evaporation, observed simultaneously by a polarimetric X-band radar and a K-band Micro Rain Radar (MRR), offer quite detailed insight into the evaporation process. During the first event, which exhibits an initial ZDR > 1.5 dB in the upper rain column, raindrops undergo relatively weak evaporation as deduced from the decrease of the small raindrop fraction observed by the MRR. The second event is characterized by a lower initial ZDR < 0.5 dB with all raindrops evaporating before reaching the ground. A retrieval scheme for estimating the evaporation-related cooling rate and surface precipitation from polarimetric radar observations below the bright band is derived based on MRR observations. The algorithm is then used to simulate polarimetric X-band radar observations, which might mitigate uncertainties in the surface rainfall retrievals due to evaporation at far distances from the radars and in the case of beam blocking.

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%.

Drop size distributions observed by four Particle Size Velocity (PARSIVEL) disdrometers during the 2013 Great Colorado Flood are used to diagnose rain characteristics during intensive rainfall episodes. The analysis focuses on 30 h of intense rainfall in the vicinity of Boulder, Colorado, from 2200 UTC 11 September to 0400 UTC 13 September 2013. Rainfall rates R, median volume diameters D0, reflectivity Z, drop size distributions (DSDs), and gamma DSD parameters were derived and compared between the foothills and adjacent plains locations. Rainfall throughout the entire event was characterized by a large number of small- to medium-sized raindrops (diameters smaller than 1.5 mm) resulting in small values of Z (

Observations and recent high-resolution numerical model simulations indicate that liquid water and partially frozen hydrometeors can be lofted considerably above the environmental 0°C level in the updrafts of convective storms owing to the warm thermal perturbation from latent heating within the updraft and to the noninstantaneous nature of drop freezing. Consequently, upward extensions of positive differential reflectivity (i.e., ZDR ≥ 1 dB)—called ZDR columns—may be a useful proxy for detecting the initiation of new convective storms and examining the evolution of convective storm updrafts. High-resolution numerical simulations with spectral bin microphysics and a polarimetric forward operator reveal a strong spatial association between updrafts and ZDR columns and show the utility of examining the structure and evolution of ZDR columns for assessing updraft evolution. This paper introduces an automated ZDR column algorithm designed to provide additional diagnostic and prognostic information pertinent to convective storm nowcasting. Although suboptimal vertical resolution above the 0°C level and limitations imposed by commonly used scanning strategies in the operational WSR-88D network can complicate ZDR column detection, examples provided herein show that the algorithm can provide operational and research-focused meteorologists with valuable information about the evolution of convective storms.

Dual-polarization radar variables, such as differential reflectivity $(\mathrm{Z}_{\mathrm{dr}})$ , are simulated from observed microphysical property of snowflakes. The increases of particle mass and aspect ratio are found to have opposite effects on $\mathrm{Z}_{\mathrm{dr}}$ , This contradictory effect is different in various riming condition. The results of simulation were adopted to interpret radar observations, which are found to agree with the current hypothesis of riming process.

Several recent studies have implicated vertical wind shear in producing steady-state size sorting of a distribution of hydrometeors falling at their terminal velocity, which varies as a function of hydrometeor diameter. In particular, this mechanism has been invoked to explain both the strength and storm-relative orientation of the commonly observed differential reflectivity (ZDR) arc in supercell thunderstorms. However, the actual role of the shear has not been fully clarified. In this study, a simple analytical model is used to show that the fundamental source of size sorting is the storm-relative wind field itself and, in particular, its mean taken over the depth of the sorting layer. Wind shear is only strictly required for producing sustained size sorting in the special but common case of a precipitation source having a motion that lies on the hodograph (such as with the environmental winds at the source level). In supercells, the precipitation source (the rotating updraft) does not necessarily move with the winds at any level. It is shown that this off-hodograph propagation and the associated storm-relative mean wind is responsible for the positive correlation of size-sorting observables (such as ZDR) and storm-relative helicity that has been noted in previous work.

Since the advent of dual-polarized technology, many studies have been conducted to determine the extent to which the differential reflectivity (ZDR) and specific differential phase shift (KDP) add benefits to estimating rain rates (R) to reflectivity (Z). It has been previously noted that this new technology provides significant improvement to rain rate estimation, but only for ranges within 125 km from the radar. Beyond this range, it is nebulous as to whether the National Weather Service conventional R(Z)-Convective algorithm is superior, as little research has investigated radar precipitation estimate performance at large ranges. The current study investigates the performance of three radars, St. Louis (KLSX), Kansas City (KEAX), and Springfield (KSGF), MO, with respect to range, with 15 terrestrial based tipping buckets served as ground-truth to the radars. Over 1100 hours of precipitation data was analyzed for the current study. It was found that, in general, performance degraded with range beyond, approximately, 150 km from the radar. Probability of detection in addition to bias values decreased, while the false alarm ratios increased as range increased. Bright-band contamination was observed to play a potential role as large increases in the absolute bias and overall error values near 120 km for the cool season, and 150 km in the warm season. The analyses found furthers our understanding in the strengths and limitations of the Next Generation Radar system overall, and from a seasonal perspective.

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.

Polarimetric radar observations of deep convective storms frequently reveal columnar enhancements of differential reflectivity ZDR. Such “ZDR columns” can extend upward more than 3 km above the environmental 0°C level, indicative of supercooled liquid drops being lofted by the updraft. Previous observational and modeling studies of ZDR columns are reviewed. To address remaining questions, the Hebrew University Cloud Model, an advanced spectral bin microphysical model, is coupled with a polarimetric radar operator to simulate the formation and life cycle of ZDR columns in a deep convective continental storm. In doing so, the mechanisms by which ZDR columns are produced are clarified, including the formation of large raindrops in the updraft by recirculation of smaller raindrops formed aloft back into the updraft at low levels. The internal hydrometeor structure of ZDR columns is quantified, revealing the transition from supercooled liquid drops to freezing drops to hail with height in the ZDR column. The life cycle of ZDR columns from early formation, through growth to maturity, to demise is described, showing how hail falling out through the weakening or ascending updraft bubble dominates the reflectivity factor ZH, causing the death of the ZDR column and leaving behind its “ghost” of supercooled drops. In addition, the practical applications of ZDR columns and their evolution are explored. The height of the ZDR column is correlated with updraft strength, and the evolution of ZDR column height is correlated with increases in ZH and hail mass content at the ground after a lag of 10–15 min.

The low levels of supercell forward flanks commonly exhibit distinct differential reflectivity (ZDR) signatures, including the low-ZDR hail signature and the high-ZDR “arc.” The ZDR arc has been previously associated with size sorting of raindrops in the presence of vertical wind shear; here this model is extended to include size sorting of hail. Idealized simulations of a supercell storm observed by the Norman, Oklahoma (KOUN), polarimetric radar on 1 June 2008 are performed using a multimoment bulk microphysics scheme, in which size sorting is allowed or disallowed for hydrometeor species. Several velocity–diameter relationships for the hail fall speed are considered, as well as fixed or variable bulk densities that span the graupel-to-hail spectrum. A T-matrix-based emulator is used to derive polarimetric fields from the hydrometeor state variables. Size sorting of hail is found to have a dominant impact on ZDR and can result in a ZDR arc from melting hail even when size sorting is disallowed in the rain field. The low-ZDR hail core only appears when size sorting is allowed for hail. The mean storm-relative wind in a deep layer is found to align closely with the gradient in mean mass diameter of both rain and hail, with a slight shift toward the storm-relative mean wind below the melting level in the case of rain. The best comparison with the observed 1 June 2008 supercell is obtained when both rain and hail are allowed to sort, and the bulk density and associated fall-speed curve for hail are predicted by the model microphysics.

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 accuracy of polarimetric rainfall relations for heavy rainfall, an extreme rainfall case was analysed and some methods were examined. The observed differential reflectivity (ZDR) quality check was theoretically investigated using the relation between the standard deviation of differential reflectivity and cross correlation, and the light rain method for ZDR bias was also applied to the rainfall estimation. The best performance for this heavy rainfall case was obtained when the moving average of ZDR over a window size of 9 gates was applied to the rainfall estimation using horizontal reflectivity (ZH) and ZDR and to the calculation of ZH bias. The differential reflectivity calculated by disdrometer data may be an alternative to the vertical pointing scan for calculating ZDR bias. The accuracy of the combined rainfall relation, R(Z,ZDR,KDP,AH) was relatively insensitive to ZDR and ZH biases in both observations and simulations.

It is shown that the scattering resonance effects in echoes from migrating birds are so strong that a 10% frequency deviation within S-band can result in more than 10-dB changes in reflectivity values. Differential reflectivity values from adjacent polarimetric WSR-88D weather radars operating at offset frequencies can differ by several decibels in “clear air” echoes.

We consider weather radar measurements at simultaneous transmission and simultaneous reception of horizontal and vertical polarizations and show that the degree of polarization at simultaneous transmit (ps) is related to differential reflectivity and copolar correlation coefficient at simultaneous transmit (namely, ZDRs and ρhys). We evaluate the potential of degree of polarization at simultaneous transmit for weather radar applications. Ultimately, we explore the consequences of adjusting the transmit polarization state of dual-polarization weather radars to circular polarization.

A method is described for adjusting the far-field polarization of an electronically steered phased-array antenna. In this method, the polarization of a small subset of array elements is switched in order to reduce far-field cross-polarization of the overall array. The technique is intended for antennas used in polarimetric radars that measure quantities such as differential reflectivity (Zdr) and specific differential phase (KDP). In particular, it is appropriate for lower cost arrays where only one transmit or receive polarization is active at a time. In such arrays, it will reduce the number of measurements needed by one-third. Analysis of the tradeoffs in the technique is presented as well as examples in hypothetical large arrays. Measured results are presented for a small 4×4 array.

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.

This study is based on analyses of dual-polarization radar observations made by the 11-cm-wavelength Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) system during four significant winter storms in northeastern Colorado. It was found that values of specific differential phase KDP often reached local maxima of ∼0.15°–0.4° km−1 in an elevated layer near the −15°C environmental temperature isotherm. The passage of these elevated positive KDP areas is shown to be linked to increased surface precipitation rates. Calculations using a microwave scattering model indicate that populations of highly oblate ice particles with moderate bulk densities and diameters in the ∼0.8–1.2-mm range can generate KDP (and differential reflectivity ZDR) values that are consistent with the radar observations. The persistent correlation between the enhanced KDP level and the −15°C temperature regime suggests that rapidly growing dendrites likely played a significant role in the production of the observed KDP patterns. The detection of organized regions of S-band KDP values greater than ∼0.1°–0.2° km−1 in winter storms may therefore be useful in identifying regions of active dendritic particle growth, as a precursor to aggregate snowfall.

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.

Early radar echo development in trade wind cumulus clouds is studied using the equivalent reflectivity factor Ze combined with the differential reflectivity Zdr. The clouds studied are among the largest of trade wind cumulus, developing significantly positive values of Zdr and attaining at least about a 30-dBZ equivalent reflectivity factor. The measures used for analysis are values calculated for entire constant–elevation angle sweeps through the clouds and entire volume scans—not maximum single-pulse-volume values. The radar echo evolution follows fairly closely the Marshall–Palmer distribution with scatter toward higher values of Zdr especially in the earliest stages of echo intensification, where some of the scatter in the whole-sweep values is caused by size sorting. The data provide no evidence for an important role of ultragiant aerosols (UGA) in initiating coalescence. They are in strong contrast with similar data from a cloud over northern Alabama that do suggest a major role for UGA in producing several-mm-diameter raindrops that dominate its weak, early radar echo.

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.

Non-conventional GaAs/GaAlAs structures, with an AlAs monolayer inserted at different positions in wells, have been investigated to observe the behaviour of excitons in quantum wells. The energy and the oscillator strength for different transitions are calculated as a function of the probe position. The differential reflectivity of the spectrum for some samples is measured in order to test our theoretical simulations. We confirmed the observation of certain parity-forbidden transitions only in the most asymmetric samples.