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A. V. Ryzhkov and D. S. Zrnić

Abstract

In this paper, the fields of three radar polarimetric variables-differential reflectivity Z DR, specific differential phase K DP, and correlation coefficient between horizontally (H) and vertically (V) polarized echoes ρhv-along with radar reflectivity Zh, are examined within two Oklahoma mesoscale convective systems (MCSs). The analysis of the whole set of polarimetric variables reveals at least three types of hydrometeor populations in the precipitation within thew MCSs. It seems to be possible to discriminate between pure liquid raindrops, drops with ice cores inside them, and mixed-phase precipitation containing rain and hail using joint analysis of all the polarimetric measurands available. Hail-bearing zones are characterized by significant reduction of Z DR and ρhv, as well as large values of Zh. Specific differential phase K DP is usually high in these zones, and sometimes a pronounced differential phase shift upon scattering is evident.

Experimental data show that the differential phase ΦDP and its derivative K DP are reliable indicators of liquid water in heavy precipitation. A negative bias of Z DR due to differential attenuation in precipitation could be significant in this type of storm. The validity of the correction scheme for Z DR estimates based on the ΦDP evaluation proposed in earlier theoretical papers was examined. It was found that differential attenuation was underestimated at least twofold in the previous theoretical predictions.

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A. V. Ryzhkov and D. S. Zrnić

Abstract

Several polarimetric radar estimators of rain rate R and rainwater content M are examined. The accuracy of the estimators is analyzed using a gamma drop size distribution (DSD) simulation and a radar wavelength of 11 cm. The estimators that use combined measurements of specific differential phase KDP and differential reflectivity ZDR are superior to the estimators of R and M obtained from reflectivity factors Zh and Zv at orthogonal polarizations or KDP only. The standard deviation of the R(KDP, ZDR) estimate is 2–3 times less than for the best of the R(Zh, Zv) estimators. The statistical accuracy of the M(KDP, ZDR) estimator is at least 1.5–2 times better than for the M(Zh, Zv) estimator. Cumulative rainfalls obtained with the estimators are compared with accumulations recorded with 42 rain gauges in the Little Washita River basin. Biases, errors, and reasons for the superior performance of the R(KDP, ZDR) estimator are explained in terms of the microphysical processes in the squall line that contributed to the rainfall.

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A. V. Ryzhkov and D. S. Zrnic

Abstract

Polarimetric signatures of snow precipitation for six Oklahoma snowstorms are examined. The available data consist of specific differential phase K DP, differential reflectivity Z DR, cross-correlation coefficient ρ hv, and radar reflectivity factor Z. These data were obtained with the 10-cm-wavelength Cimarron polarimetric weather radar. The data suggest that in pure snow the average values of K DP and Z DR do not follow a systematic trend with change of the radar reflectivity factor if Z < 35 dBZ; this is not the case in rain. Precipitation is qualified as snow if the average Z DR is less than 0.2 dB for Z < 35 dBZ. The presence of a bright band with a pronounced ρ hv minimum and Z DR maximum is a good discernible feature for discriminating between snow and rain. Thus, a localized deep minimum of the cross-correlation coefficient delineates the transition region between snow and rain in the horizontal direction if sufficiently large snowflakes are generated in the transition area. Otherwise, a sharp change of Z DR can be used to localize the position of the snow–rain line.

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A. V. Ryzhkov, V. B. Zhuravlyov, and N. A. Rybakova

Abstract

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.

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A. V. Ryzhkov, D. S. Zrnic, and B. A. Gordon

Abstract

Two variants of a polarimetric method to determine ice water content are presented. One uses specific differential phase and differential reflectivity and the other uses specific differential phase; both quantities are for a 10-cm wavelength. Theoretical considerations indicate that these polarimetric methods are suited for pristine ice crystals. Ice water content of lightly to moderately aggregated crystals might also be estimated. Verification of the proposed method is made using in situ data collected by the T-28 instrumented aircraft. Comparison with two estimators that use the reflectivity factor suggests that the polarimetric methods are better and can quantify correctly ice water content in the range above 0.1 g m−3.

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E. Ilotoviz, A. Khain, Alexander V. Ryzhkov, and Jeffrey C. Snyder

Abstract

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 Z DR. It is shown that Z DR columns are associated with raindrops and with hail particles growing in a wet growth regime within convective updrafts. The height and volume of Z DR 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 Z DR. Characteristics of Z DR columns are highly correlated with vertical velocity, hail size, and aerosol concentration.

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Edward A. Brandes, Alexander V. Ryzhkov, and Dus̆an S. Zrnić

Abstract

Specific differential propagation phase (K DP) is examined for estimating convective rainfall in Colorado and Kansas. Estimates are made at S band with K DP alone and in combination with radar reflectivity (Z H). Results are compared to gauge observations by computing bias factors, defined as the sum of gauge-measured rainfalls divided by the sum of radar estimates at gauges reporting rainfall, and the correlation coefficient between the gauge and radar-estimated amounts. Rainfall accumulations computed from positive-only values of K DP (provided Z H ≥ 25 dBZ) yield bias factors that vary from 0.76 to 2.42 for 3 storms in Colorado and from 0.78 to 1.46 for 10 storms in Kansas. Correlation coefficients between gauge-observed and radar-estimated rainfalls are 0.76 to 0.95. When negative K DP’s are included as negative rainfall rates, bias factors range from 0.81 to 3.00 in Colorado and from 0.84 to 2.31 in Kansas. In most storms, the correlation between gauge and radar rainfalls decreases slightly.

In an experiment with the K DP/Z H combination, rainfall rates are computed from K DP when K DP is ≥0.4° km−1 and from Z H for K DP < 0.4° km−1 and Z H ≥ 25 dBZ. Neglect of the negative K DP’s and substitution of the always positive Z H rainfall rates result in a tendency to overestimate rainfall. Bias factors are 0.63–1.46 for Colorado storms and 0.68–0.97 for Kansas storms, and correlation coefficients between gauge and radar amounts are 0.80–0.95. In yet another test with the K DP/Z H pair, rainfall estimates are computed from K DP when Z H ≥ 40 dBZ and from Z H when 25 ⩽ Z H < 40 dBZ. For this experiment, bias factors range from 0.90 to 1.91 in Colorado and from 0.88 to 1.46 in Kansas. Correlation coefficients are 0.80–0.96.

Since bias factors and correlation coefficients between estimated rainfalls and gauge observations for K DP are similar to those for radar reflectivity, there was no obvious benefit with K DP rainfalls for a well-calibrated radar. Large underestimates with K DP in two storms were attributed to rainfalls dominated by small drops. In one storm, the problem was aggravated by widespread negative K DP’s thought related to vertical gradients of precipitation. An advantage of K DP-derived rainfall estimates confirmed here is an insensitivity to anomalous propagation.

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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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R. J. Doviak, V. Bringi, A. Ryzhkov, A. Zahrai, and D. Zrnić

Abstract

This paper reports on the steps taken by the National Severe Storms Laboratory (NSSL) to 1) develop open system hardware to facilitate upgrades to the WSR-88D (NEXRAD) radar and 2) improve identification of the type of precipitation and its quantitative measure. An engineering evaluation is made to determine if the WSR-88D antenna assembly with minimum modification could be used in a polarimetric mode. The polarimetric characteristics and radiation patterns of a research WSR-88D are briefly discussed. Considerations for the choice of polarimetric basis and design options are described. A polarimetric scheme employing simultaneous transmission of horizontally (H) and vertically (V) polarized waves is suggested for the WSR-88D, which eliminates an expensive, high-power switch. A theoretical evaluation is performed to determine the effects that feed alignment, drop canting, and backscatter depolarization have on the measurements of polarimetric parameters made with simultaneous transmission and reception of H and V signals. Experiments with the Colorado State University–Universities of Chicago and Illinois radar are performed to compare polarimetric variables obtained with alternate and simultaneous transmissions of H, V waves. Both simultaneous reception in two receivers and alternate reception in one receiver have been used.

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Hyang Suk Park, A. V. Ryzhkov, D. S. Zrnić, and Kyung-Eak Kim

Abstract

This paper contains a description of the most recent version of the hydrometeor classification algorithm for polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). This version contains several modifications and refinements of the previous echo classification algorithm based on the principles of fuzzy logic. These modifications include the estimation of confidence factors that characterize the possible impacts of all error sources on radar measurements, the assignment of the matrix of weights that characterizes the classification power of each variable with respect to every class of radar echo, and the implementation of a class designation system based on the distance from the radar and the parameters of the melting layer that are determined as functions of azimuth with polarimetric radar measurements. These additions provide considerable flexibility and improve the discrimination between liquid and frozen hydrometeors. The new classification scheme utilizes all available polarimetric variables and discerns 10 different classes of radar echoes. Furthermore, a methodology for the new fuzzy logic classification scheme is discussed and the results are illustrated using polarimetric radar data collected with the Norman, Oklahoma (KOUN), WSR-88D prototype radar during a mesoscale convective system event on 13 May 2005.

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