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

Abstract

As part of the Joint Polarization Experiment (JPOLE), the National Severe Storms Laboratory conducted an operational demonstration of the polarimetric utility of the Norman, Oklahoma (KOUN), Weather Surveillance Radar-1988 Doppler (WSR-88D). The capability of the KOUN radar to estimate rainfall is tested on a large dataset representing different seasons and different types of rain. A dense gauge network—the Agricultural Research Service (ARS) Micronet—is used to validate different polarimetric algorithms for rainfall estimation. One-hour rain totals are estimated from the KOUN radar using conventional and polarimetric algorithms and are compared with hourly accumulations measured by the gauges. Both point and areal rain estimates are examined. A new “synthetic” rainfall algorithm has been developed for rainfall estimation. The use of the synthetic polarimetric algorithm results in significant reduction in the rms errors of hourly rain estimates when compared with the conventional nonpolarimetric relation: 1.7 times for point measurements and 3.7 times for areal rainfall measurements.

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

Abstract

The assimilation of radar data into storm-scale numerical weather prediction models has been shown to be beneficial for successfully modeling convective storms. Because of the difficulty of directly assimilating reflectivity (Z), hydrometeor mixing ratios, and sometimes rainfall rate, are often retrieved from Z observations using retrieval relations, and are assimilated as state variables. The most limiting (although widely employed) cases of these relations are derived, and their assumptions and limitations are discussed.

To investigate the utility of these retrieval relations for liquid water content (LWC) and ice water content (IWC) in rain and hail as well as the potential for improvement using polarimetric variables, two models with spectral bin microphysics coupled with a polarimetric radar operator are used: a one-dimensional melting hail model and the two-dimensional Hebrew University Cloud Model. The relationship between LWC and Z in pure rain varies spatially and temporally, with biases clearly seen using the normalized number concentration. Retrievals using Z perform the poorest while specific attenuation and specific differential phase shift (K DP) perform much better. Within rain–hail mixtures, separate estimation of LWC and IWC is necessary. Prohibitively large errors in the retrieved LWC may result when using Z. The quantity K DP can be used to effectively retrieve the LWC and to isolate the contribution of IWC to Z. It is found that the relationship between Z and IWC is a function of radar wavelength, maximum hail diameter, and principally the height below the melting layer, which must be accounted for in order to achieve accurate retrievals.

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Jeffrey C. Snyder
,
Alexander V. Ryzhkov
,
Matthew R. Kumjian
,
Alexander P. Khain
, and
Joseph Picca

Abstract

Observations and recent high-resolution numerical model simulations indicate that liquid water and partially frozen hydrometeors can be lofted considerably above the environmental 0°C level in the updrafts of convective storms owing to the warm thermal perturbation from latent heating within the updraft and to the noninstantaneous nature of drop freezing. Consequently, upward extensions of positive differential reflectivity (i.e., Z DR ≥ 1 dB)—called Z DR columns—may be a useful proxy for detecting the initiation of new convective storms and examining the evolution of convective storm updrafts. High-resolution numerical simulations with spectral bin microphysics and a polarimetric forward operator reveal a strong spatial association between updrafts and Z DR columns and show the utility of examining the structure and evolution of Z DR columns for assessing updraft evolution. This paper introduces an automated Z DR column algorithm designed to provide additional diagnostic and prognostic information pertinent to convective storm nowcasting. Although suboptimal vertical resolution above the 0°C level and limitations imposed by commonly used scanning strategies in the operational WSR-88D network can complicate Z DR column detection, examples provided herein show that the algorithm can provide operational and research-focused meteorologists with valuable information about the evolution of convective storms.

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Alexander V. Ryzhkov
,
Matthew R. Kumjian
,
Scott M. Ganson
, and
Alexander P. Khain

Abstract

Spectral (bin) microphysics models are used to simulate polarimetric radar variables in melting hail. Most computations are performed in a framework of a steady-state, one-dimensional column model. Vertical profiles of radar reflectivity factor Z, differential reflectivity Z DR, specific differential phase K DP, specific attenuation A h , and specific differential attenuation A DP are modeled at S, C, and X bands for a variety of size distributions of ice particles aloft. The impact of temperature lapse rate, humidity, vertical air velocities, and ice particle density on the vertical profiles of the radar variables is also investigated. Polarimetric radar signatures of melting hail depend on the degree of melting or the height of the radar resolution volume with respect to the freezing level, which determines the relative fractions of partially and completely melted hail (i.e., rain). Simulated vertical profiles of radar variables are very sensitive to radar wavelength and the slope of the size distribution of hail aloft, which is correlated well with maximal hail size. Analysis of relative contributions of different parts of the hail/rain size spectrum to the radar variables allows explanations of a number of experimentally observed features such as large differences in Z of hail at the three radar wavelengths, unusually high values of Z DR at C band, and relative insensitivity of the measurements at C and X bands to the presence of large hail exceeding 2.5 cm in diameter. Modeling results are consistent with S- and C-band polarimetric radar observations and are utilized in Part II for devising practical algorithms for hail detection and determination of hail size as well as attenuation correction and rainfall estimation in the presence of hail.

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

Abstract

A midlatitude hail storm was simulated using a new version of the spectral bin microphysics Hebrew University Cloud Model (HUCM) with a detailed description of time-dependent melting and freezing. In addition to size distributions of drops, plate-, columnar-, and branch-type ice crystals, snow, graupel, and hail, new distributions for freezing drops as well as for liquid water mass within precipitating ice particles were implemented to describe time-dependent freezing and wet growth of hail, graupel, and freezing drops.

Simulations carried out using different aerosol loadings show that an increase in aerosol loading leads to a decrease in the total mass of hail but also to a substantial increase in the maximum size of hailstones. Cumulative rain strongly increases with an increase in aerosol concentration from 100 to about 1000 cm−3. At higher cloud condensation nuclei (CCN) concentrations, the sensitivity of hailstones’ size and surface precipitation to aerosols decreases. The physical mechanism of these effects was analyzed. It was shown that the change in aerosol concentration leads to a change in the major mechanisms of hail formation and growth. The main effect of the increase in the aerosol concentration is the increase in the supercooled cloud water content. Accordingly, at high aerosol concentration, the hail grows largely by accretion of cloud droplets in the course of recycling in the cloud updraft zone. The main mechanism of hail formation in the case of low aerosol concentration is freezing of raindrops.

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Matthew R. Kumjian
,
Alexander V. Ryzhkov
,
Valery M. Melnikov
, and
Terry J. Schuur

Abstract

In recent years, there has been widespread interest in collecting and analyzing rapid updates of radar data in severe convective storms. To this end, conventional single-polarization rapid-scan radars and phased array radar systems have been employed in numerous studies. However, rapid updates of dual-polarization radar data in storms are not widely available. For this study, a rapid scanning strategy is developed for the polarimetric prototype research Weather Surveillance Radar-1988 Doppler (WSR-88D) radar in Norman, Oklahoma (KOUN), which emulates the future capabilities of a polarimetric multifunction phased array radar (MPAR). With this strategy, data are collected over an 80° sector with 0.5° azimuthal spacing and 250-m radial resolution (“super resolution”), with 12 elevation angles. Thus, full volume scans over a limited area are collected every 71–73 s.

The scanning strategy was employed on a cyclic nontornadic supercell storm in western Oklahoma on 1 June 2008. The evolution of the polarimetric signatures in the supercell is analyzed. The repetitive pattern of evolution of these polarimetric features is found to be directly tied to the cyclic occlusion process of the low-level mesocyclone. The cycle for each of the polarimetric signatures is presented and described in detail, complete with a microphysical interpretation. In doing so, for the first time the bulk microphysical properties of the storm on small time scales (inferred from polarimetric data) are analyzed. The documented evolution of the polarimetric signatures could be used operationally to aid in the detection and determination of various stages of the low-level mesocyclone occlusion.

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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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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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