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  • Author or Editor: Alexander V. Ryzhkov x
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Silke Trömel
,
Alexander V. Ryzhkov
,
Malte Diederich
,
Kai Mühlbauer
,
Stefan Kneifel
,
Jeffrey Snyder
, and
Clemens Simmer

Abstract

Multisensor observations of anvil mammatus are analyzed in order to gain a more detailed understanding of their spatiotemporal structure and microphysical characterization. Remarkable polarimetric radar signatures are detected for the Pentecost 2014 supercell in Northrhine Westfalia, Germany, and severe storms in Oklahoma along their mammatus-bearing anvil bases. Radar reflectivity at horizontal polarization Z H and cross-correlation coefficient ρ HV decrease downward toward the bottom of the anvil while differential reflectivity Z DR rapidly increases, consistent with the signature of crystal depositional growth. The differential reflectivity Z DR within mammatus exceeds 2 dB in the Pentecost storm and in several Oklahoma severe convective storms examined for this paper. Observations from a zenith-pointing Ka-band cloud radar and a Doppler wind lidar during the Pentecost storm indicate the presence of a supercooled liquid layer of at least 200–300-m depth near the anvil base at temperatures between −15° and −30°C. These liquid drops, which are presumably generated in localized areas of vertical velocities of up to 1.5 m s−1, coexist with ice particles identified by cloud radar. The authors hypothesize that pristine crystals grow rapidly within these layers of supercooled water, and that oriented planar ice crystals falling from the liquid layers lead to high Z DR at precipitation radar frequencies. A mammatus detection strategy using precipitation radar observations is presented, based on a methodology so far mainly used for the detection of updrafts in convective storms. Owing to the presence of a supercooled liquid layer detected above the mammatus lobes, the new detection strategy might also be relevant for aviation safety.

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Yadong Wang
,
Pengfei Zhang
,
Alexander V. Ryzhkov
,
Jian Zhang
, and
Pao-Liang Chang

Abstract

To improve the accuracy of quantitative precipitation estimation (QPE) in complex terrain, a new rainfall rate estimation algorithm has been developed and applied on two C-band dual-polarization radars in Taiwan. In this algorithm, the specific attenuation A is utilized in the rainfall rate R estimation, and the parameters used in the R(A) method were estimated using the local drop size distribution (DSD) and drop shape relation (DSR) observations. In areas of complex terrain where the lowest antenna tilt is completely blocked, observations from higher tilts are used in radar QPE. Correction of the vertical profile of rain rate estimated by the R(A) algorithm (VPRA) is applied to account for the vertical variability of rain. It has been found that the VPRA correction improved the accuracy of estimated rainfall in severely blocked areas. The R(A)–VPRA scheme was tested for different precipitation cases including typhoon, stratiform, and convective rain. Compared to existing rainfall estimation algorithms such as rainfall–reflectivity (RZ) and rainfall–specific differential phase (RK DP), the new method is able to provide accurate and robust rainfall estimates when the radar reflectivity is miscalibrated or significantly biased by attenuation or when the lower tilt of the radar beam is significantly blocked.

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R. Jeffrey Trapp
,
David M. Schultz
,
Alexander V. Ryzhkov
, and
Ronald L. Holle

Abstract

A significant winter precipitation event occurred on 8–9 March 1994 in Oklahoma. Snow accumulations greater than 30 cm (12 in.) were measured within a narrow corridor in northern Oklahoma. On the synoptic scale and mesoscale, a correspondence between large snow accumulations and 600-hPa frontogenesis was revealed; the precipitation was formed above the cold frontal surface, owing to midtropospheric ascent associated with the cross-frontal circulation in a region of elevated conditional instability. The location of such a narrow corridor of large accumulations was not, however, disclosed by any patterns in the radar reflectivity data. Indeed, during this event, an elongated maximum of snow accumulation was not associated with a persistent “band” of enhanced reflectivity and vice versa.

Dual-polarization and dual-Doppler radar data allowed for a novel analysis of winter precipitation processes and structures, within the context of the larger-scale diagnosis. It was possible to identify, in order of distance southward toward the surface cold front: (i) an elevated convective element, which was classified as an elevated thunderstorm and may have functioned as an ice crystal “generator” cell, embedded within a broad region of generally stratiform precipitation; (ii) a reflectivity band and associated rain–snow transition zone, the evolution and structure of which apparently were coupled to the effects of melting precipitation and strong vertical wind shear; and (iii) a mixed-phase precipitation-generating, prolific lightning-producing, nonelevated thunderstorm cell that was sustained in the postfrontal air in part by virtue of its rotational dynamics.

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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.

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