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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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.

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

A calibration procedure of differential reflectivity on the Weather Surveillance Radar-1988 Doppler (WSR-88D) is described. It has been tested on NOAA's modified WSR-88D research and development polarimetric radar and is directly applicable to radars that simultaneously transmit and receive waves having horizontal and vertical polarization.

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

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

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

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

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

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

The intrastorm variability of raindrop size distributions as a source of uncertainty in single-parameter and dual-parameter radar rainfall estimates is studied using time series analyses of disdrometer observations. Two rain-rate (R) estimators are considered: the traditional single-parameter estimator using only the radar reflectivity factor (Z) and a dual-polarization estimator using a combination of radar reflectivity at horizontal polarization (Z(H)) and differential reflectivity (Z(DR)). A case study for a squall-line system passing over the Goodwin Creek experimental watershed in northern Mississippi is presented. Microphysically, the leading convective line is characterized by large raindrop concentrations (>500 drops per cubic meter), large mean raindrop sizes (>1 mm), and wide raindrop size distributions (standard deviations >0.5 mm), as compared to the transition region and the trailing stratiform rain. The transition and stratiform phases have similar raindrop concentrations and mean raindrop sizes. Their main difference is that the distributions are wider in the latter. A scaling-law analysis reveals that the shapes of the scaled spectra are bent downward for small raindrop sizes in the leading convective line, slightly bent upward in the transition zone, and strongly bent upward in the trailing stratiform rain. The exponents of the resulting Z-R relationships are roughly the same for the leading convective line and the trailing stratiform rain (approximate to1.4) and slightly larger for the transition region (approximate to1.5), with prefactors increasing in this order: transition (approximate to200), convective (approximate to300), stratiform (approximate to450). In terms of rainfall estimation bias, the best-fit mean R(Z(H), Z(DR)) relationship outperforms the best-fit mean R( Z) relationship, both for each storm phase separately and for the event as a whole.

The early histories of radar echo and polarization differential reflectivity (ZDR) from growing cumulus clouds observed in Florida with a 10-cm-wavelength radar are reported in detail. Raindrops 1 to several millimeters in diameter are present at about cloud-base level in most cases as soon as any identifiable precipitation echo is seen within cloud (distinct from Bragg scattering and echo from cloud droplets). This is in most cases by the time of the first 10-dBZ radar echo aloft. The very early occurrence of large drops is consistent with origination directly from coalescence on ultragiant aerosol. However, they appear to exist so early and so low in the clouds as to be unexpected if the cumulus were single, vigorous thermals. The explanation may lie in the presence of a more gradual, very early cloud stage that is generally not observed in any detail. Simultaneous Ze and ZDR measurements in the early stages of developing, warm cumulus will provide a powerful test of understanding the onset of ...

On June 5, 2013, Lubbock Texas is hit by a haboob at 10:30 pm. The storm is categorized as a wind event by television media and the dust component goes unreported. This event is used as a case study to evaluate the usefulness of the polarimetric variables differential reflectivity (ZDR) and correlation coefficient (CC) in identifying the storm as a haboob. Photographic evidence of the haboob is collected and correlated to NEXRAD signatures of base reflectivity and velocity from the Lubbock TX NEXRAD station (KLBB). NEXRAD level III products ZDR and CC are also obtained. The storm presents with gust front features to the north and east of the station. Low values returned from CC indicate nonmeteorological content. ZDR representations weakly indicate the presence of gust fronts to the east, with a stronger signal to the north. As no visual evidence of the northern gust front is available, the ZDR data are inconclusive. The correlation of low CC values to the visual representation of the haboob is an indicator that CC in combination with the NEXRAD base reflectivity and velocity products may be used to test wind events for the presence of sand, dust, and dirt and therefore exhibit predictive qualities.

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

While radars measure several quantities closely coupled to the rainfall rate, for frequencies less than 15 GHz, estimates of the rainwater content W are traditionally computed from the radar reflectivity factor Z or the rate of attenuation A--quantities only weakly related to W. Consequently, instantaneous point estimates of W using Z and A are often erroneous. A more natural, alternative parameter for estimating W at these frequencies is the specific polarization propagation differential phase shift phi(sub DP), which is a measure of the change in the difference between phases of vertically (V) and horizontally (H) polarized waves with increasing distance from a radar. It is now well known that W is nearly linearly related to phi(sub DP) divided by (1 - reversed R), where reversed R is the mass-weighted mean axis ratio of the raindrops. Unfortunately, such relations are not widely used in part because measurements of phi(sub DP) are scarce but also because one must determine reversed R. In this work it is shown that this parameter can be estimated using the differential reflectivity (Z(sub H)/Z(sub V) at 3 GHz. An alternative technique is suggested for higher frequencies when the differential reflectivity becomes degraded by attenuation. While theory indicates that it should be possible using phi(sub DP) to estimate W quite accurately, measurement errors increase the uncertainty to +/- 18%-35% depending on reversed R. While far from ideal, it appears that these estimates are likely to be considerably more accurate than those deduced using currently available methods.

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

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

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