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Erica M. Griffin
,
Terry J. Schuur
,
Alexander V. Ryzhkov
,
Heather D. Reeves
, and
Joseph C. Picca

Abstract

On 8–9 February 2013, the northeastern United States experienced a historic winter weather event ranking among the top five worst blizzards in the region. Heavy snowfall and blizzard conditions occurred from northern New Jersey, inland to New York, and northward through Maine. Storm-total snow accumulations of 30–61 cm were common, with maximum accumulations up to 102 cm and snowfall rates exceeding 15 cm h−1. Dual-polarization radar measurements collected for this winter event provide valuable insights into storm microphysical processes. In this study, polarimetric data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) in Upton, New York (KOKX), are investigated alongside thermodynamic analyses from the 13-km Rapid Refresh model and surface precipitation type observations from both Meteorological Phenomena Identification Near the Ground (mPING) and the National Weather Service (NWS) Forecast Office in Upton, New York, for interpretation of polarimetric signatures. The storm exhibited unique polarimetric signatures, some of which have never before been documented for a winter system. Reflectivity values were unusually large, reaching magnitudes >50 dBZ in shallow regions of heavy wet snow near the surface. The 0°C transition line was exceptionally distinct in the polarimetric imagery, providing detail that was often unmatched by the numerical model output. Other features include differential attenuation of magnitudes typical of melting hail, depolarization streaks that provide evidence of electrification, nonuniform beamfilling, a “snow flare” signature, and localized downward excursions of the melting-layer bright band collocated with observed transitions in surface precipitation types. In agreement with previous studies, widespread elevated depositional growth layers, located at temperatures near the model-predicted −15°C isotherm, appear to be correlated with increased snowfall and large reflectivity factors Z H near the surface.

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Terry J. Schuur
,
Hyang-Suk Park
,
Alexander V. Ryzhkov
, and
Heather D. Reeves

Abstract

A new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help to diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events for which past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation-type categories when the observations are found to be inconsistent with the background classification. Using data from the polarimetric KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman, Oklahoma, the algorithm is tested on a transitional winter-storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006. Examples are presented in which the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.

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Matthew R. Kumjian
,
Alexander V. Ryzhkov
,
Heather D. Reeves
, and
Terry J. Schuur

Abstract

Polarimetric radar measurements in winter storms that produce ice pellets have revealed a unique signature that is indicative of ongoing hydrometeor refreezing. This refreezing signature is observed within the low-level subfreezing air as an enhancement of differential reflectivity Z DR and specific differential phase K DP and a decrease of radar reflectivity factor at horizontal polarization ZH and copolar correlation coefficient ρ hv. It is distinct from the overlying melting-layer “brightband” signature and suggests that unique microphysical processes are occurring within the layer of hydrometeor refreezing. The signature is analyzed for four ice-pellet cases in central Oklahoma as observed by two polarimetric radars. A statistical analysis is performed on the characteristics of the refreezing signature for a case of particularly long duration. Several hypotheses are presented to explain the appearance of the signature, along with a summary of the pros and cons for each. It is suggested that preferential freezing of small drops and local ice generation are plausible mechanisms for the appearance of the Z DR and K DP enhancements. Polarimetric measurements and scattering calculations are used to retrieve microphysical information to explore the validity of the hypotheses. The persistence and repetitiveness of the signature suggest its potential use in operational settings to diagnose the transition between freezing rain and ice pellets.

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Alexander V. Ryzhkov
,
Matthew R. Kumjian
,
Scott M. Ganson
, and
Pengfei Zhang

Abstract

The results of theoretical modeling in Part I are utilized to develop practical recommendations for developing the algorithms for hail detection and determination of its size as well as attenuation correction and rainfall estimation in the presence of hail. A new algorithm for discrimination between small hail (with maximal size of less than 2.5 cm), large hail (with diameters between 2.5 and 5.0 cm), and giant hail with size exceeding 5.0 cm is proposed and implemented for applications with the S-band dual-polarization Weather Surveillance Radar-1988 Doppler (WSR-88D) systems. The fuzzy-logic algorithm is based on the combined use of radar reflectivity Z, differential reflectivity Z DR, and cross-correlation coefficient ρ hv. The parameters of the membership functions depend on the height of the radar resolution volume with respect to the freezing level, exploiting the size-dependent melting characteristics of hailstones. The attenuation effects in melting hail are quantified in this study, and a novel technique for polarimetric attenuation correction in the presence of hail is suggested. The use of a rainfall estimator that is based on specific differential phase K DP is justified on the basis of the results of theoretical simulations and comparison of actual radar retrievals at S band with gauge measurements for storms containing large hail with diameters exceeding 2.5 cm.

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Silke Trömel
,
Matthew R. Kumjian
,
Alexander V. Ryzhkov
,
Clemens Simmer
, and
Malte Diederich

Abstract

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

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Terry J. Schuur
,
Alexander V. Ryzhkov
,
Dusan S. Zrnić
, and
Michael Schönhuber

Abstract

An analysis of drop size distributions (DSDs) measured in four very different precipitation regimes is presented and is compared with polarimetric radar measurements. The DSDs are measured by a 2D video disdrometer, which is designed to measure drop size, shape, and fall speed with unprecedented accuracy. The observations indicate that significant DSD variability exists not only from one event to the next, but also within each system. Also, despite having vastly different storm structures and maximum rain rates, large raindrops with diameters greater than 5 mm occurred with each system. By comparing the occurrence of large drops with rainfall intensity, the authors find that the largest median diameters are not always associated with the heaviest rainfall, but are sometimes located either in advance of convective cores or, occasionally, in stratiform regions where rainfall rates are relatively low. Disdrometer and polarimetric radar measurements of radar reflectivity Z, differential reflectivity Z DR, specific differential phase K DP, and R(Z) and R(K DP) rain-rate estimators are compared in detail. Overall agreement is good, but it is found that both R(Z) and R(K DP) underestimate rain rate when the DSD is dominated by small drops and overestimate rain rate when the DSD is dominated by large drops. The results indicate that a classification of different rain types (associated with different DSDs) should be an essential part of polarimetric rainfall estimation. Furthermore, observations suggest that Z DR is a key parameter for making such a distinction. Last, the authors compute and compare maximum and average of gamma shape, slope, and intercept parameters for all four precipitation events. Potential measurement errors with the 2D video disdrometer are also discussed.

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Jacob T. Carlin
,
Edwin L. Dunnavan
,
Alexander V. Ryzhkov
, and
Mariko Oue

Abstract

Quasi-vertical profiles (QVPs) of polarimetric radar data have emerged as a powerful tool for studying precipitation microphysics. Various studies have found enhancements in specific differential phase K dp in regions of suspected secondary ice production (SIP) due to rime splintering. Similar K dp enhancements have also been found in regions of sublimating snow, another proposed SIP process. This work explores these K dp signatures for two cases of sublimating snow using nearly collocated S- and Ka-band radars. The presence of the signature was inconsistent between the radars, prompting exploration of alternative causes. Idealized simulations are performed using a radar beam-broadening model to explore the impact of nonuniform beam filling (NBF) on the observed reflectivity Z and K dp within the sublimation layer. Rather than an intrinsic increase in ice concentration, the observed K dp enhancements can instead be explained by NBF in the presence of sharp vertical gradients of Z and K dp within the sublimation zone, which results in a K dp bias dipole. The severity of the bias is sensitive to the Z gradient and radar beamwidth and elevation angle, which explains its appearance at only one radar. In addition, differences in scanning strategies and range thresholds during QVP processing can constructively enhance these positive K dp biases by excluding the negative portion of the dipole. These results highlight the need to consider NBF effects in regions not traditionally considered (e.g., in pure snow) due to the increased K dp fidelity afforded by QVPs and the subsequent ramifications this has on the observability of sublimational SIP.

Significance Statement

Many different processes can cause snowflakes to break apart into numerous tiny pieces, including when they evaporate into dry air. Purported evidence of this phenomenon has been seen in data from some weather radars, but we noticed it was not seen in data from others. In this work we use case studies and models to show that this signature may actually be an artifact from the radar beam becoming too big and there being too much variability of the precipitation within it. While this breakup process may actually be occurring in reality, these results suggest we may have trouble observing it with typical weather radars.

Free access
Silke Trömel
,
Alexander V. Ryzhkov
,
Brandon Hickman
,
Kai Mühlbauer
, and
Clemens Simmer

Abstract

Time series of quasi–vertical profiles (QVPs) from 52 stratiform precipitation events observed with the polarimetric X-band radar in Bonn, Germany (BoXPol), between 2013 and 2016 have been statistically analyzed to infer microphysical processes shaping the dendritic-growth-layer (DGL) and melting-layer (ML) signatures including surface rainfall. Specific differential phase K DP in the ML shows an average correlation of 0.65 with surface rainfall for these cases. Radar reflectivity decreases below the ML by about 2 dB on average while differential reflectivity Z DR is hardly affected, which suggests rain evaporation as the dominating effect. Estimated ice water content or snow water equivalent precipitation rate S in the DGL is correlated with surface rain rates with lead times of 30 min and longer, which opens a pathway for radar-based nowcasting of stratiform precipitation tendencies. Trajectories of snow generated aloft down to the surface are constructed from wind profiles derived both from the nearest radiosounding and radar-based velocity azimuth displays (VAD) to narrow down the location at which the DGL-generated snow reaches the surface as rain. The lagged correlation analysis between K DP in the DGL and reflectivity Z H at that location demonstrates the superiority of the VAD information. Correlation coefficients up to 0.80 with lead times up to 120 min provide a proof of concept for future nowcasting applications that are based on DGL monitoring. Statistical relations found in our QVP dataset provide a database for estimating intrinsic polarimetric variables from the usual azimuth and elevation scans within and in the vicinity of the ML.

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Alexander V. Ryzhkov
,
Scott E. Giangrande
,
Valery M. Melnikov
, and
Terry J. Schuur

Abstract

Techniques for the absolute calibration of radar reflectivity Z and differential reflectivity Z DR measured with dual-polarization weather radars are examined herein.

Calibration of Z is based on the idea of self-consistency among Z, Z DR, and the specific differential phase K DP in rain. Extensive spatial and temporal averaging is used to derive the average values of Z DR and K DP for each 1 dB step in Z. Such averaging substantially reduces the standard error of the K DP 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 Z DR 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 Z DR calibration is modified for nonzenith elevation angles. It is shown that the required 0.1–0.2-dB accuracy of the Z DR calibration is potentially achievable.

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Yadong Wang
,
Tian-You Yu
,
Alexander V. Ryzhkov
, and
Matthew R. Kumjian

Abstract

Spectral polarimetry has the potential to be used to study microphysical properties in relation to the dynamics within a radar resolution volume by combining Doppler and polarimetric measurements. The past studies of spectral polarimetry have focused on using radar measurements from higher elevation angles, where both the size sorting from the hydrometeors’ terminal velocities and polarimetric characteristics are maintained. In this work, spectral polarimetry is applied to data from the 0° elevation angle, where polarimetric properties are maximized. Radar data collected by the C-band University of Oklahoma Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) during a hailstorm event on 24 April 2011 are used in the analysis. The slope of the spectral differential reflectivity exhibits interesting variations across the hail core, which suggests the presence of size sorting of hydrometeors caused by vertical shear in a turbulent environment. A nearby S-band polarimetric Weather Surveillance Radar-1988 Doppler (KOUN) is also used to provide insights into this hailstorm. Moreover, a flexible numerical simulation is developed for this study, in which different types of hydrometeors such as rain and melting hail can be considered individually or as a combination under different sheared and turbulent conditions. The impacts of particle size distribution, shear, turbulence, attenuation, and mixture of rain and melting hail on polarimetric spectral signatures are investigated with the simulated Doppler spectra and spectral differential reflectivity.

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