Search

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.

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.

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.

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.

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.

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

A multi-radar analysis of the 20 May 2013 Moore, Oklahoma, U.S. supercell is presented using three Weather Surveillance Radars 1988 Doppler (WSR-88Ds) and PX-1000, a rapid-scan, polarimetric, X-band radar, with a focus on the period between 1930 and 2008 UTC, encompassing supercell maturation through rapid tornado intensification. Owing to the 20-s temporal resolution of PX-1000, a detailed radar analysis of the hook echo is performed on (1) the microphysical characteristics through a hydrometeor classification algorithm (HCA)—inter-compared between X- and S-band for performance evaluation—including a hail and debris class and (2) kinematic properties of the low-level mesocyclone (LLM) assessed through ΔVr analyses. Four transient intensifications in ΔVr prior to tornadogenesis are documented and found to be associated with two prevalent internal rear-flank downdraft (RFD) momentum surges, the latter surge coincident with tornadogenesis. The momentum surges are marked by a rapidly advancing reflectivity (ZH) gradient traversing around the LLM, descending reflectivity cores (DRCs), a drop in differential reflectivity (ZDR) due to the advection of smaller drops into the hook echo, a decrease in correlation coefficient (ρhv), and the detection of debris from the HCA. Additionally, volumetric analyses of ZDR and specific differential phase (KDP) signatures show general diffusivity of the ZDR arc even after tornadogenesis in contrast with explosive deepening of the KDP foot downshear of the updraft. Similarly, while the vertical extent of the ZDR and KDP columns decrease leading up to tornadogenesis, the phasing of these signatures are offset after tornadogenesis, with the ZDR column deepening the lagging of KDP.

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.

Based on the preciousness and uniqueness of polarimetric radar observations collected near the landfall of Typhoon Soudelor (2015), this study investigates the sensitivities of very short-range quantitative precipitation forecasts (QPFs) for this typhoon to polarimetric radar data assimilation. A series of experiments assimilating various combinations of radar variables are carried out for the purpose of improving a 6 h deterministic forecast for the most intense period. The results of the control simulation expose three sources of the observation operator errors, including the raindrop shape-size relation, the limitations for ice-phase hydrometeors, and the melting ice model. Nevertheless, polarimetric radar data assimilation with the unadjusted observation operator can still improve the analyses, especially rainwater, and consequent QPFs for this typhoon case. The different impacts of assimilating reflectivity, differential reflectivity, and specific differential phase are only distinguishable at the lower levels of convective precipitation areas where specific differential phase is found most helpful. The positive effect of radar data assimilation on QPFs can last three hours in this study, and further improvement can be expected by optimizing the observation operator in the future

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.

To investigate the impact of rainfall type on rainfall estimation using polarimetric variables, rainfall relations such as those between rain rate (R) and specific differential phase (KDP), between R and KDP/differential reflectivity (ZDR), and between R and reflectivity (Z)/ZDR, were examined with respect to the precipitation type classified using drop size distributions (DSDs) measured by a disdrometer. The classification of rainfall type was assessed using four different methods: temporal rainfall variation, and the relations between intercept parameter (N0) and R, normalized intercept parameter (Nw) and median diameter (D0), and slope parameter (&Lambda, ) and R. The logN0&ndash, R relation discriminated between convective and stratiform rain with less standard deviation than the other methods as shown by the Z&ndash, ZDR scatter with respect to the rainfall types. The transition type from convective to stratiform and vice versa occurred in the stratiform rain region for all methods. To apply the classified rainfall relations to radar rainfall estimation, logNw and D0 were retrieved from polarimetric variables to discriminate the rainfall types in the radar domain. The DSD classification was verified with the vertical profile of reflectivity extracted at two positions corresponding to gage sites. Statistical analysis of four different rainfall events showed that rainfall estimation using the relations with precipitation type were better than those obtained without classification. The R(KDP,ZDR) relation with classification performed best on rainfall estimation for all rainfall events. The greatest improvement in rainfall estimation was obtained from R(Z,ZDR) with classification. We conclude that the classification of rainfall type leads to more accurate rainfall estimation. The different relations R(KDP), R(KDP,ZDR), and R(Z,ZDR) with respect to the rain types using polarimetric radar show improvement compared to estimation without consideration of rainfall type, in Korea.

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.

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.

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.

Analyses of the radar-observed structure and derived rainfall statistics of warm-season convection developing columns of enhanced positive differential reflectivity ZDR over England’s southwest peninsula are presented here. Previous observations of ZDR columns in developing cumulonimbus clouds over England were rare. The observations presented herein suggest otherwise, at least in the southwesterly winds over the peninsula. The results are the most extensive of their kind in the United Kingdom; the data were collected using the National Centre for Atmospheric Science dual-polarization X-band radar (NXPol) during the Convective Precipitation Experiment (COPE). In contrast to recent studies of ZDR columns focused on deep clouds that developed in high-instability environments, the COPE measurements show relatively frequent ZDR columns in shallower clouds, many only 4–5 km deep. The presence of ZDR columns is used to infer that an active warm rain process has contributed to precipitation evolution in convection deep enough for liquid and ice growth to take place. Clouds with ZDR columns were identified objectively in three COPE deployments, with both discrete convection and clouds embedded in larger convective complexes developing columns. Positive ZDR values typically extended to 1–1.25 km above 0°C in the columns, with ZDR ≥ 1 dB sometimes extending nearly 4 km above 0°C. Values above 3 dB typically occurred in the lowest 500 m above 0°C, with coincident airborne measurements confirming the presence of supercooled raindrops. Statistical analyses indicated that the convection that produced ZDR columns was consistently associated with the larger derived rainfall rates when compared with the overall convective population sampled by the NXPol during COPE.

As a manifestation of low-altitude wind shear, a downburst is a localized, strong downdraft that can lead to disastrous wind on the ground surface. For effective pre-warning and forecasting of downbursts, it is particularly critical to understand relevant weather features that occur before and during a downburst process. It is important to identify the macroscopic features associated with the downburst weather process before considering fine-scale observations because this would greatly increase the accuracy and timeliness of forecasts. Therefore, we applied the wind-vector potential-temperature energy analysis (WPEA) method and CSU-CHILL X-band dual-polarization radar to explore the features of the downburst process. Here it was found that prior to the occurrence of the downburst of interest, the specific areas that should be monitored in future events could be determined by studying the atmospherically unstable areas using the WPEA method. Combining the WPEA method with dual-polarization radar observations, we can better distinguish the phase distribution of the hydrometeor in the process and greatly enhance the judgment of the possibility of the downburst. From exploration of the microphysical features of the downburst, we further found that &lsquo, Zdr (differential reflectivity) column&rsquo, can be regarded as an important early warning indicator of the location of the downburst. Finally, a schematic of the formation process of the downburst according to the analyses was produced.

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.

Clouds consist of water particles (hydrometeors) in different aggregate states. Above the melting layer these hydrometeors are formed mainly as ice crystals and other completely or partly frozen particles. With measurements from the C-band dual polarimetric radar POLDIRAD (Oberpfaffenhofen, Germany) the backscattered signals of the ice particles in the horizontal/vertical polarisation base were analysed. The focus is lying on the co-polar reflectivities and therefore the differential reflectivity. In the next step a simulation of the backscattered signals deliver the physical ansatz for the creation of an ice crystal class. Finally the comparison of this class with a raindrop classification is shown.

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.

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.

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.

TFG MOBILITY Weather forecast estimation has been a matter of analysis for many years. The arrival of dual polarization radars meant an improvement due to the incorporation of new variables. This project illustrates how to obtain the standard and new meteorological variables (Reflectivity, Doppler Velocity, Spectrum Width, Differential Reflectivity, Co-Polar Correlation Coefficient and Differential Propagation Phase). Reflectivity and Doppler velocity appear to be more advantageous because they are more consistent since the Spectrum Width is easily corrupted. Variables retrieved from the dual polarization radars happen to be even more reliable than the standard ones because most of them are independent from miscalibrations and attenuations. It also analyzes two different noise identification methods in order to estimate the noise floor. One of them based on the Co-Polar Correlation Coefficient characteristics that, for most of the cases, show a better performance than the other method based on three different features that threshold the noise. El estudio de eventos meteorológicos es un campo de interés des de hace años. La llegada de radares de doble polarización ha causado una mejora importante en la estimación del tiempo gracias a la incorporación de las nuevas variables meteorológicas. Este proyecto ilustra la forma de obtener las variables estándar y las de doble polarización para el análisis del tiempo. La reflectividad y la velocidad doppler tienen unos resultados más consistentes que el ancho de espectro, ya que son más difíciles de corromper. Las variables calculadas a partir de la doble polarización son incluso más fiables ya que la mayoría de ellas no dependen de errores de calibración ni atenuaciones. En el proyecto, también se estudian dos métodos diferentes de identificación de ruido. Uno de los métodos está basado en las características propias del coeficiente de correlación co-polar que, en la mayoría de casos, resulta tener mejores resultado que el otro método, basado en el cálculo de tres variables que analizan el ruido. L'estudi d'esdeveniments meteorològics és un camp d'interès des de fa anys. L'arribada de radars de doble polarització ha causat una millora significativa en l'estimació del temps gràcies a la incorporació de les noves variables meteorològiques. Aquest projecte il·lustra com obtenir les variables estàndards i de doble polarització de l'anàlisi meteorològic. La reflectivitat i la velocitat doppler tenen uns resultats més consistents que l'ample d'espectre, ja que és més difícil corrompre-les. Les variables calculades a partir de la doble polarització són molt més fiables ja que la majoria d'elles, són independents dels errors de calibrat i d'atenuacions. En el projecte, també s'estudien dos mètodes d'identificació del soroll per a poder fer l'estimació d'aquest. Un dels mètodes està basat en les característiques pròpies del coeficient de correlació co-polar que, per la majoria de situacions, té un comportament millor que l'altre mètode, basat en el càlcul de tres variables que analitzen el soroll.

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.