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A novel methodology is introduced for processing and presenting polarimetric data collected by weather surveillance radars. It involves azimuthal averaging of radar reflectivity Z , differential reflectivity Z DR , cross-correlation coefficient ρ hv , and differential phase Φ DP at high antenna elevation, and presenting resulting quasi-vertical profiles (QVPs) in a height-versus-time format. Multiple examples of QVPs retrieved from the data collected by S-, C-, and X-band dual-polarization radars at elevations ranging from 6.4° to 28° illustrate advantages of the QVP technique. The benefits include an ability to examine the temporal evolution of microphysical processes governing precipitation production and to compare polarimetric data obtained from the scanning surveillance weather radars with observations made by vertically looking remote sensors, such as wind profilers, lidars, radiometers, cloud radars, and radars operating on spaceborne and airborne platforms. Continuous monitoring of the melting layer and the layer of dendritic growth with high vertical resolution, and the possible opportunity to discriminate between the processes of snow aggregation and riming, constitute other potential benefits of the suggested methodology.

Conventional radar-based hydrometeor classification algorithms identify the dominant hydrometeor type within a resolved radar volume, while newer techniques estimate the proportions of individual hydrometeor classes (hydrometeor partitioning ratios, HPRs) within a mixture. These newer algorithms (HMCP) are based on dual-polarization measurements from ground-based radars (GR), while to date no comparable algorithms for space-borne radars (SR) with dual-frequency capabilities exist. This study (1) further improves HPR estimates based on GR dual-polarization measurements, (2) exploits the combination of dual-frequency SR and dual-polarization GR to introduce HPRs based on dual-frequency observations only, and (3) evaluates GR- and SR-based HPR retrievals. To achieve these objectives, dual-polarization measurements of NEXRAD's GRs are matched with those of the dual-frequency precipitation radar of the Global Precipitation Measurement Core satellite. All matched volumes are represented by averaged dual-frequency and dual-polarization observations and several hundred GR sub-volumes classified with standard hydrometeor classification. The latter are used to calculate quasi-HPRs (qHPRs). qHPRs and averaged dual-frequency and dual-polarization variables of the training dataset are used to derive covariances and centroids for each hydrometeor class. They serve as the basis for dual-frequency and dual-polarization based HPR retrievals within HMCP and are applied to the test dataset. The ensuing evaluation of HPR retrievals is performed with the qHPRs of the test dataset. HPRs show for most hydrometeor classes high correlations with the qHPRs and confirm the overall good HMCP performance. However, dual-polarization based classification performance is superior to dual-frequency ones. Both underestimate snow, overestimate graupel, and result in low correlations for big drops.

In a two-part paper, radar rain-rate retrievals using specific attenuationAsuggested by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two twin polarimetric X-band weather radars in Germany during the summers of 2011–13 are used to analyze various aspects of rain-rate retrieval, including miscalibration correction, mitigation of ground clutter contamination and partial beam blockage (PBB), sensitivity to precipitation characteristics, and the temperature assumptions of theR(A) technique. In this paper, the relations inherent to theR(A) method are used to estimate radar reflectivityZfromAand compare it to the measuredZin order to estimate PBB and calibration offsets for both radars. The fields ofZestimated fromAfor both radars are consistent, and the differences betweenZ(A) and measuredZare in good agreement with the ones calculated using either consistency relations between reflectivity at horizontal polarizationZ H, differential reflectivityZ DR, and specific differential phaseK DPin rain or a digital elevation model in the presence of PBB. In the analysis, the dependence ofAon temperature appears to have minimal effects on the overall performance of the method. As expected, the difference betweenZ(A) and attenuation-corrected measuredZobservations varies with rain type and exhibits a weak systematic dependency on rainfall intensity; thus, averaging over several rain events is required to obtain reliable estimates of theZbiases caused by radar miscalibration and PBB.

In a series of two papers, rain-rate retrievals based on specific attenuationAat radar X-band wavelength using theR(A) method presented by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two polarimetric X-band weather radars in Germany during the summers of 2011–13 are used to analyze various aspects of the method, like miscalibration correction, ground clutter contamination, partial beam blockage (PBB), sensitivity to precipitation characteristics, and sensitivity to temperature assumptions in the retrievals. In Part I of the series, the relations inherent to theR(A) method were used to calculate radar reflectivityZfrom specific attenuation and it was compared with measured reflectivity to estimate PBB and calibration errors for both radars. In this paper,R(A) rain estimates are compared toR(Z) andR(K DP) retrievals using specific phase shiftK DP. PBB and calibration corrections derived in Part I made theR(Z) rainfall estimates almost perfectly consistent. Accumulated over five summer months, rainfall maps showed strong effects of clutter contamination ifR(K DP) is used and weaker impact onR(A). These effects could be reduced by processing the phase shift measurements with more resilience toward ground clutter contamination and by substituting problematicR(K DP) orR(A) estimates withR(Z). Hourly and daily accumulations from rain estimators are compared with rain gauge measurements; the results show thatR(A) complemented byR(Z) in segments with low total differential phase shift correlates best with gauges and has the lowest bias and RMSE, followed byR(K DP) substituted withR(Z) at rain rates below 8 mm h−1.

Backscatter differential phaseδwithin the melting layer has been identified as a reliably measurable but still underutilized polarimetric variable. Polarimetric radar observations at X band in Germany and S band in the United States are presented that show maximal observedδof 8.5° at X band but up to 70° at S band. Dual-frequency observations at X and C band in Germany and dual-frequency observations at C and S band in the United States are compared to explore the regional frequency dependencies of theδsignature. Theoretical simulations based on usual assumptions about the microphysical composition of the melting layer cannot reproduce the observed large values ofδat the lower-frequency bands and also underestimate the enhancements in differential reflectivityZ DRand reductions in the cross-correlation coefficientρhv . Simulations using a two-layer T-matrix code and a simple model for the representation of accretion can, however, explain the pronouncedδsignatures at S and C bands in conjunction with smallδat X band. The authors conclude that theδsignature bears information about microphysical accretion and aggregation processes in the melting layer and the degree of riming of the snowflakes aloft.

Recent advances demonstrate the benefits of radar-derived specific attenuation at horizontal polarization (A H) for quantitative precipitation estimation (QPE) at S and X band. To date the methodology has, however, not been adapted for the widespread European C-band radars such as those installed in the network of the German Meteorological Service (DWD, Deutscher Wetterdienst). Simulations based on a large dataset of drop size distributions (DSDs) measured over Germany are performed to investigate the DSD dependencies of the attenuation parameter αH for the A H estimates. The normalized raindrop concentration (Nw) and the change of differential reflectivity (Z DR) with reflectivity at horizontal polarization (Z H) are used to categorize radar observations into regimes for which scan-wise optimized αH values are derived. For heavier continental rain with Z H > 40 dBZ, the A H-based rainfall retrieval R(A H) is combined with a rainfall estimator using a substitute of specific differential phase ( K DP * ) . We also assess the performance of retrievals based on specific attenuation at vertical polarization (A V). Finally, the regime-adapted hybrid QPE algorithms are applied to four convective cases and one stratiform case from 2017 to 2019, and compared to DWD’s operational Radar-Online-Aneichung (RADOLAN) RW rainfall product, which is based on Z h only but adjusted to rain gauge measurements. For the convective cases, our hybrid retrievals outperform the traditional R(Z h) and pure R(A H/V) retrievals with fixed αH/V values when evaluated with gauge measurements and outperform RW when evaluated by disdrometer measurements. Potential improvements using ray-wise αH/V and segment-wise applications of the ZPHI method along the radials are discussed.

Sensitivity experiments with a numerical weather prediction (NWP) model and polarimetric radar forward operator (FO) are conducted for a long-duration stratiform event over northwestern Germany to evaluate uncertainties in the partitioning of the ice water content and assumptions of hydrometeor scattering properties in the NWP model and FO, respectively. Polarimetric observations from X-band radar and retrievals of hydrometeor classifications are used for comparison with the multiple experiments in radar and model space. Modifying the critical diameter of particles for ice-to-snow conversion by aggregation (Dice) and the threshold temperature responsible for graupel production by riming (Tgr), was found to improve the synthetic polarimetric moments and simulated hydrometeor population, while keeping the difference in surface precipitation statistically insignificant at model resolvable grid scales. However, the model still exhibited a low bias (lower magnitude than observation) in simulated polarimetric moments at lower levels above the melting layer (-3 to -13 ∘C) where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models to draw valid conclusions.

Polarimetric weather radars offer a wealth of new information compared to conventional technology, not only to enhance quantitative precipitation estimation, warnings, and short-term forecasts, but also to improve our understanding of precipitation generating processes and their representation in numerical weather prediction models. To support such research opportunities, this paper describes an open-access dataset between 2014–2019 collected by the polarimetric Doppler X-band weather radar in Bonn (BoXPol), western Germany. To complement this dataset, the technical radar characteristics, scanning strategy and the best-practice for radar data processing are detailed. In addition, an investigation of radar calibration is presented. Reflectivity measurements from the Dual-frequency Precipitation Radar operating on the core satellite of the Global Precipitation Mission are compared to those of BoXPol to provide absolute calibration offsets with the dataset. The Relative Calibration Adjustment technique is applied to identify stable calibration periods. The absolute calibration of differential reflectivity is determined using the vertical scan and provided with the BoxPol dataset. Measurement(s) Radar backscattering of precipitation Technology Type(s) Polarimetric Doppler X-band weather radar

On the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phaseδhas been explored;δhas been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phaseK DP, especially at shorter radar wavelengths. Moreover,δbears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimatingδin rain and in the melting layer are suggested. The method for estimatingδin rain is based on a modified version of the “ZPHI” algorithm and provides reasonably robust estimates ofδandK DPin pure rain except in regions where the total measured differential phase ΦDPbehaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimatingδin the melting layer results in reliable estimates ofδin stratiform precipitation and requires azimuthal averaging of radial profiles of ΦDPat high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence betweenδand differential reflectivityZ DR. Becauseδis immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation betweenZ DRandδis of interest for quantitative precipitation estimation:δandZ DRare differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude ofδcan be utilized as an important calibration parameter for improving microphysical models of the melting layer.

This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km  ×  5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.