Search Results

You are looking at 11 - 20 of 62 items for

  • Author or Editor: Alexander V. Ryzhkov x
  • Refine by Access: All Content x
Clear All Modify Search
Scott E. Giangrande
and
Alexander V. Ryzhkov

Abstract

In the presence of partial beam blockage (PBB), weather radar measurements can experience significant bias that directly compromises the accuracy of the hydrologic applications. Techniques for the calibration of the radar reflectivity factor Z and differential reflectivity Z DR, measured with dual-polarization weather radars in the presence of partial beam obstruction, are examined in this paper.

The proposed Z DR calibration technique utilizes radar measurements of Z DR in light rain and dry aggregated snow at unblocked and blocked elevations. This calibration technique was tested for the National Severe Storms Laboratory’s (NSSL’s) Cimarron radar that suffers from PBB, and a polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) that does not experience PBB. Results indicate that the Z DR bias that is associated with PBB can be calibrated with an accuracy of 0.2–0.3 dB, provided that the dataset is sufficiently large.

Calibration of Z in the presence of PBB is based on the idea of self-consistency among Z, Z DR, and the specific differential phase K DP in rain. The self-consistency calibration of Z from the Cimarron radar is performed following an area–time integral method. Integration is partitioned into small azimuthal sectors to assess the azimuthal modulation of the Z bias. The suggested technique is validated by direct comparisons of reflectivity factors that are measured by the Cimarron radar and the unobstructed operational WSR-88D radar. It is shown that the azimuthal modulation of Z that is caused by PBB is well captured, and the accuracy of the Z calibration is within 2–3 dB.

Full access
Alexander V. Ryzhkov
and
Dusan S. Zrnić

Abstract

Simultaneous transmission and reception of horizontally and vertically polarized waves is a preferable choice technique for dual-polarization weather radar. One of the consequences of such a choice is possible cross-coupling between orthogonally polarized waves. Cross-coupling depends on depolarizing properties of propagation media, and it is usually negligible in rain because the net mean canting angle of raindrops is close to zero.

Snow crystals at the tops of thunderstorm clouds are often canted in the presence of strong electric fields and produce noticeable cross-coupling between radar signals at horizontal and vertical polarizations if both signals are transmitted and received simultaneously. As a result, peculiar-looking radial signatures of differential reflectivity Z DR and differential phase ΦDP are commonly observed in the crystal regions of thunderstorms.

The paper presents examples of strong depolarization in oriented crystals from the data collected by the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) and a theoretical model that explains the results of measurements. It is shown that the sign and magnitude of the Z DR and ΦDP signatures strongly depend on the orientation of crystals and a system differential phase on transmission.

Full access
Dusan S. Zrnic
and
Alexander V. Ryzhkov

This paper is an overview of weather radar polarimetry emphasizing surveillance applications. The following potential benefits to operations are identified: improvement of quantitative precipitation measurements, discrimination of hail from rain with possible determination of sizes, identification of precipitation in winter storms, identification of electrically active storms, and distinction of biological scatterers (birds vs insects). Success in rainfall measurements is attributed to unique properties of differential phase. Referrals to fields of various polarimetric variables illustrate the signatures associated with different phenomena. It is argued that classifying hydrometeors is a necessary step prior to proper quantification of the water substance. The promise of polarimetry to accomplish classification is illustrated with an application to a hailstorm.

Full access
Edwin L. Dunnavan
and
Alexander V. Ryzhkov

Abstract

This study derives simple analytical expressions for the theoretical height profiles of particle number concentrations (Nt ) and mean volume diameters (Dm ) during the steady-state balance of vapor growth and collision–coalescence with sedimentation. These equations are general for both rain and snow gamma size distributions with size-dependent power-law functions that dictate particle fall speeds and masses. For collision–coalescence only, Nt (Dm ) decreases (increases) as an exponential function of the radar reflectivity difference between two height layers. For vapor deposition only, Dm increases as a generalized power law of this reflectivity difference. Simultaneous vapor deposition and collision–coalescence under steady-state conditions with conservation of number, mass, and reflectivity fluxes lead to a coupled set of first-order, nonlinear ordinary differential equations for Nt and Dm . The solutions to these coupled equations are generalized power-law functions of height z for Dm (z) and Nt (z) whereby each variable is related to one another with an exponent that is independent of collision–coalescence efficiency. Compared to observed profiles derived from descending in situ aircraft Lagrangian spiral profiles from the CRYSTAL-FACE field campaign, these analytical solutions can on average capture the height profiles of Nt and Dm within 8% and 4% of observations, respectively. Steady-state model projections of radar retrievals aloft are shown to produce the correct rapid enhancement of surface snowfall compared to the lowest-available radar retrievals from 500 m MSL. Future studies can utilize these equations alongside radar measurements to estimate Nt and Dm below radar tilt elevations and to estimate uncertain microphysical parameters such as collision–coalescence efficiencies.

Significance Statement

While complex numerical models are often used to describe weather phenomenon, sometimes simple equations can instead provide equally good or comparable results. Thus, these simple equations can be used in place of more complicated models in certain situations and this replacement can allow for computationally efficient and elegant solutions. This study derives such simple equations in terms of exponential and power-law mathematical functions that describe how the average size and total number of snow or rain particles change at different atmospheric height levels due to growth from the vapor phase and aggregation (the sticking together) of these particles balanced with their fallout from clouds. We catalog these mathematical equations for different assumptions of particle characteristics and we then test these equations using spirally descending aircraft observations and ground-based measurements. Overall, we show that these mathematical equations, despite their simplicity, are capable of accurately describing the magnitude and shape of observed height and time series profiles of particle sizes and numbers. These equations can be used by researchers and forecasters along with radar measurements to improve the understanding of precipitation and the estimation of its properties.

Restricted access
Matthew R. Kumjian
and
Alexander V. Ryzhkov

Abstract

Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetric signatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero Z DR and high Z HH. In addition, a shallow region of very high Z DR is found consistently on the southern edge of the FFD, called the Z DR “arc.” The Z DR and K DP columns and midlevel “rings” of enhanced Z DR and depressed ρ HV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested.

Full access
Scott E. Giangrande
and
Alexander V. Ryzhkov

Abstract

The quality of polarimetric radar rainfall estimation is investigated for a broad range of distances from the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D). The results of polarimetric echo classification have been integrated into the study to investigate the performance of radar rainfall estimation contingent on hydrometeor type. A new method for rainfall estimation that capitalizes on the results of polarimetric echo classification (EC method) is suggested. According to the EC method, polarimetric rainfall relations are utilized if the radar resolution volume is filled with rain (or rain and hail), and multiple R(Z) relations are used for different types of frozen hydrometeors. The intercept parameters in the R(Z) relations for each class are determined empirically from comparisons with gauges. It is shown that the EC method exhibits better performance than the conventional WSR-88D algorithm with a reduction by a factor of 1.5–2 in the rms error of 1-h rainfall estimates up to distances of 150 km from the radar.

Full access
Pamela L. Heinselman
and
Alexander V. Ryzhkov

Abstract

This study describes, illustrates, and validates hail detection by a simplified version of the National Severe Storms Laboratory’s fuzzy logic polarimetric hydrometeor classification algorithm (HCA). The HCA uses four radar variables: reflectivity, differential reflectivity, cross-correlation coefficient, and “reflectivity texture” to classify echoes as rain mixed with hail, ground clutter–anomalous propagation, biological scatterers (insects, birds, and bats), big drops, light rain, moderate rain, and heavy rain. Diagnostic capabilities of HCA, such as detection of hail, are illustrated for a variety of storm environments using polarimetric radar data collected mostly during the Joint Polarimetric Experiment (JPOLE; 28 April–13 June 2003). Hail classification with the HCA is validated using 47 rain and hail reports collected by storm-intercept teams during JPOLE. For comparison purposes, probability of hail output from the Next-Generation Weather Radar Hail Detection Algorithm (HDA) is validated using the same ground truth. The anticipated polarimetric upgrade of the Weather Surveillance Radar-1988 Doppler network drives this direct comparison of performance. For the four examined cases, contingency table statistics show that the HCA outperforms the HDA. The superior performance of the HCA results primary from the algorithm’s lack of false alarms compared to the HDA. Statistical significance testing via bootstrapping indicates that differences in the probability of detection and critical success index between the algorithms are statistically significant at the 95% confidence level, whereas differences in the false alarm rate and Heidke skill score are statistically significant at the 90% confidence level.

Full access
Petar Bukovčić
,
Alexander V. Ryzhkov
, and
Jacob T. Carlin

Abstract

The intrinsic uncertainty of radar-based retrievals in snow originates from a large diversity of snow growth habits, densities, and particle size distributions, all of which can make interpreting radar measurements of snow very challenging. The application of polarimetric radar for snow measurements can mitigate some of these issues. In this study, a novel polarimetric method for quantification of the extinction coefficient and visibility in snow, based on the joint use of radar reflectivity at horizontal polarization Z and specific differential phase K DP, is introduced. A large 2D-video-disdrometer snow dataset from central Oklahoma is used to derive a polarimetric bivariate power-law relation for the extinction coefficient, σ e ( K DP , Z ) = γ K DP α Z β . The relation is derived for particle aspect ratios ranging from 0.5 to 0.8 and the width of the canting angle distribution ranging from 0° to 40°, values typical of aggregated snow, and validated via theoretical and analytical derivations/simulations. The multiplier of the relation is sensitive to variations in particles’ densities, the width of the canting angle distribution, and particles’ aspect ratios, whereas the relation’s exponents are practically invariant to changes in the latter two parameters. This novel approach is applied to polarimetric S-band WSR-88D data and verified against previous studies and in situ measurements of the extinction coefficient for four snow events in the eastern United States. The polarimetric radar estimates of the extinction coefficient exhibit smaller biases in comparison to previous studies concerning the ground measurements. The results indicate that there is good potential for reliable radar estimates of visibility from polarimetric weather radars, a parameter inversely proportional to the extinction coefficient.

Full access
Silke Trömel
,
Michael Ziegert
,
Alexander V. Ryzhkov
,
Christian Chwala
, and
Clemens Simmer

Abstract

The variability in raindrop size distributions and attenuation effects are the two major sources of uncertainty in radar-based quantitative precipitation estimation (QPE) even when dual-polarization radars are used. New methods are introduced to exploit the measurements by commercial microwave radio links to reduce the uncertainties in both attenuation correction and rainfall estimation. The ratio α of specific attenuation A and specific differential phase K DP is the key parameter used in attenuation correction schemes and the recently introduced R(A) algorithm. It is demonstrated that the factor α can be optimized using microwave links at Ku band oriented along radar radials with an accuracy of about 20%–30%. The microwave links with arbitrary orientation can be utilized to optimize the intercepts in the R(K DP) and R(A) relations with an accuracy of about 25%. The performance of the suggested methods is tested using the polarimetric C-band radar operated by the German Weather Service on Mount Hohenpeissenberg in southern Germany and two radially oriented Ku-band microwave links from Ericsson GmbH.

Full access
Matthew R. Kumjian
,
Scott M. Ganson
, and
Alexander V. Ryzhkov

Abstract

Polarimetric radar observations of convective storms routinely reveal positive differential reflectivity Z DR extending above the 0°C level, indicative of the presence of supercooled liquid particles lofted by the storm’s updraft. The summit of such “Z DR columns” is marked by a zone of enhanced linear depolarization ratio L DR or decreased copolar cross-correlation coefficient ρ hv and a sharp decrease in Z DR that together mark a particle freezing zone. To better understand the relation between changes in the storm updraft and the observed polarimetric variables, it is necessary to first understand the physics governing this freezing process and the impact of freezing on the polarimetric variables.

A simplified, one-dimensional explicit bin microphysics model of stochastic drop nucleation by an immersed foreign particle and subsequent deterministic freezing is developed and coupled with an electromagnetic scattering model to explore the impact of the freezing process on the polarimetric radar variables. As expected, the height of the Z DR column is closely related to the updraft strength and initial drop size distribution. Additionally, the treatment of the stochastic nucleation process can also affect the depth of the freezing zone, underscoring the need to accurately depict this process in parameterizations. Representation of stochastic nucleation and deterministic freezing for each drop size bin yields better agreement between observations and the modeled vertical profiles of the surface reflectivity factor ZH and Z DR than bulk microphysics schemes. Further improvements in the representation of the L DR cap, the observed ZDR gradient in the freezing zone, and the magnitude of the ρ hv minimum may require inclusion of accretion, which was not included in this model.

Full access