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Alexander V. Ryzhkov
,
Terry J. Schuur
,
Donald W. Burgess
, and
Dusan S. Zrnic

Abstract

Polarimetric radars are shown to be capable of tornado detection through the recognition of tornadic debris signatures that are characterized by the anomalously low cross-correlation coefficient ρ hv and differential reflectivity Z DR. This capability is demonstrated for three significant tornadic storms that struck the Oklahoma City, Oklahoma, metropolitan area. The first tornadic debris signature, based on the measurements with the National Severe Storms Laboratory’s Cimarron polarimetric radar, was reported for a storm on 3 May 1999. Similar signatures were identified for two significant tornadic events during the Joint Polarization Experiment (JPOLE) in May 2003. The data from these storms were collected with a polarimetric prototype of the Next-Generation Weather Radar (NEXRAD). In addition to a small-scale debris signature, larger-scale polarimetric signatures that might be relevant to tornadogenesis were persistently observed in tornadic supercells. The latter signatures are likely associated with lofted light debris (leaves, grass, dust, etc.) in the inflow region and intense size sorting of hydrometeors in the presence of strong wind shear and circulation.

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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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Jacob T. Carlin
,
Jidong Gao
,
Jeffrey C. Snyder
, and
Alexander V. Ryzhkov

Abstract

Achieving accurate storm-scale analyses and reducing the spinup time of modeled convection is a primary motivation for the assimilation of radar reflectivity data. One common technique of reflectivity data assimilation is using a cloud analysis, which inserts temperature and moisture increments and hydrometeors deduced from radar reflectivity via empirical relations to induce and sustain updraft circulations. Polarimetric radar data have the ability to provide enhanced insight into the microphysical and dynamic structure of convection. Thus far, however, relatively little has been done to leverage these data for numerical weather prediction. In this study, the Advanced Regional Prediction System’s cloud analysis is modified from its original reflectivity-based formulation to provide moisture and latent heat adjustments based on the detection of differential reflectivity columns, which can serve as proxies for updrafts in deep moist convection and, subsequently, areas of saturation and latent heat release. Cycled model runs using both the original cloud analysis and above modifications are performed for two high-impact weather cases: the 19 May 2013 central Oklahoma tornadic supercells and the 25 May 2016 north-central Kansas tornadic supercell. The analyses and forecasts of convection qualitatively and quantitatively improve in both cases, including more coherent analyzed updrafts, more realistic forecast reflectivity structures, a better correspondence between forecast updraft helicity tracks and radar-derived rotation tracks, and improved frequency biases and equitable threat scores for reflectivity. Based on these encouraging results, further exploration of the assimilation of dual-polarization radar data into storm-scale models is warranted.

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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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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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David J. Bodine
,
Matthew R. Kumjian
,
Robert D. Palmer
,
Pamela L. Heinselman
, and
Alexander V. Ryzhkov

Abstract

This study investigates the use of tornadic debris signature (TDS) parameters to estimate tornado damage severity using Norman, Oklahoma (KOUN), polarimetric radar data (polarimetric version of the Weather Surveillance Radar-1988 Doppler radar). Several TDS parameters are examined, including parameters based on the 10th or 90th percentiles of polarimetric variables (lowest tilt TDS parameters) and TDS parameters based on the TDS volumetric coverage (spatial TDS parameters). Two highly detailed National Weather Service (NWS) damage surveys are compared to TDS parameters. The TDS parameters tend to be correlated with the enhanced Fujita scale (EF) rating. The 90th percentile reflectivity, TDS height, and TDS volume increase during tornado intensification and decrease during tornado dissipation. For 14 tornado cases, the maximum or minimum TDS parameter values are compared to the tornado’s EF rating. For tornadoes with a higher EF rating, higher maximum values of the 90th percentile Z HH, TDS height, and volume, as well as lower minimum values of 10th percentile ρ HV and Z DR, are observed. Maxima in spatial TDS parameters are observed after periods of severe, widespread tornado damage for violent tornadoes. This paper discusses how forecasters could use TDS parameters to obtain near-real-time information about tornado damage severity and spatial extent.

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Matthew R. Kumjian
,
Alexander P. Khain
,
Nir Benmoshe
,
Eyal Ilotoviz
,
Alexander V. Ryzhkov
, and
Vaughan T. J. Phillips

Abstract

Polarimetric radar observations of deep convective storms frequently reveal columnar enhancements of differential reflectivity Z DR. Such “Z DR 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 Z DR 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 Z DR columns in a deep convective continental storm. In doing so, the mechanisms by which Z DR 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 Z DR columns is quantified, revealing the transition from supercooled liquid drops to freezing drops to hail with height in the Z DR column. The life cycle of Z DR 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 Z H , causing the death of the Z DR column and leaving behind its “ghost” of supercooled drops. In addition, the practical applications of Z DR columns and their evolution are explored. The height of the Z DR column is correlated with updraft strength, and the evolution of Z DR column height is correlated with increases in Z H and hail mass content at the ground after a lag of 10–15 min.

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Alexander V. Ryzhkov
,
Dusan S. Zrnic
,
John C. Hubbert
,
V. N. Bringi
,
J. Vivekanandan
, and
Edward A. Brandes

Abstract

Preliminary analysis of all components of the polarimetric radar covariance matrix for precipitation measured with the NCAR S-band dual-polarization Doppler radar (S-Pol) and the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radars is presented. Radar reflectivity at horizontal polarization Z h, differential reflectivity Z DR, linear depolarization ratio LDR, specific differential phase K DP, cross-correlation coefficient |ρ hv|, and two co-cross-polar correlation coefficients, ρ xh and ρ xv, have been measured and examined for two rain events: the 14 August 1998 case in Florida and the 8 August 1998 case in Colorado.

Examination of the coefficients ρ xh and ρ xv is the major focus of the study. It is shown that hydrometeors with different types of orientation can be better delineated if the coefficients ρ xh and ρ xv are used. Rough estimates of the raindrop mean canting angles and the rms width of the canting angle distribution are obtained from the co-cross-polar correlation coefficients in combination with other polarimetric variables.

Analysis of the two cases indicates that the raindrop net canting angles averaged over the propagation paths near the ground in typical convective cells do not exceed 2.5°. Nonetheless, the mean canting angles in individual radar resolution volumes in rain can be noticeably higher. Although the net canting angle for individual convective cells can deviate by a few degrees from zero, the average over a long propagation path along several cells is close to zero, likely because canting angles in different cells vary in sign.

The rms width of the canting angle distribution in rain is estimated to vary mainly between 5° and 15° with the median value slightly below 10°.

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Alexander V. Ryzhkov
,
Terry J. Schuur
,
Donald W. Burgess
,
Pamela L. Heinselman
,
Scott E. Giangrande
, and
Dusan S. Zrnic

As part of the evolution and future enhancement of the Next Generation Weather Radars (NEXRAD), the National Severe Storms Laboratory recently upgraded the KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) to include a polarimetric capability. The proof of concept was tested in central Oklahoma during a 1-yr demonstration project referred to as the Joint Polarization Experiment (JPOLE). This paper presents an overview of polarimetric algorithms for rainfall estimation and hydrometeor classification and their performance during JPOLE. The quality of rainfall measurements is validated on a large dataset from the Oklahoma Mesonet and Agricultural Research Service Micronet rain gauge networks. The comparison demonstrates that polarimetric rainfall estimates are often dramatically superior to those provided by conventional rainfall algorithms. Using a synthetic R(Z, K DP, Z DR) polarimetric rainfall relation, rms errors are reduced by a factor of 1.7 for point measurements and 3.7 for areal estimates [when compared to results from a conventional R(Z) relation]. Radar data quality improvement, hail identification, rain/snow discrimination, and polarimetric tornado detection are also illustrated for selected events.

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