Abstract

The impact of beam broadening on the quality of radar polarimetric data in the presence of nonuniform beam filling (NBF) is examined both theoretically and experimentally. Cross-beam gradients of radar reflectivity Z, differential reflectivity Z _DR, and differential phase Φ_DP within the radar resolution volume may produce significant biases of Z _DR, Φ_DP, and the cross-correlation coefficient ρ _hv. These biases increase with range as a result of progressive broadening of the radar beam. They are also larger at shorter radar wavelengths and wider antenna beams.

Simple analytical formulas are suggested for estimating the NBF-induced biases from the measured vertical and horizontal gradients of Z, Z _DR, and Φ_DP. Analysis of polarimetric data collected by the KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) demonstrates that frequently observed perturbations of the radial Φ_DP profiles and radially oriented “valleys” of ρ _hv depression can be qualitatively and quantitatively explained using the suggested NBF model.

Abstract

A simple model of the radar scattering by atmospheric particles is used to interpret all elements of the covariance scattering matrix. The components of the covariance scattering matrix and corresponding polarimetric variables are expressed via a limited number of integral parameters that characterize distributions of sizes, shapes, and orientations of meteorological scatterers.

The co–cross-polar correlation coefficients ρ _xh and ρ _xυ measured in the horizontal–vertical linear polarization basis are the major focus of this study. It is shown that the magnitudes of both coefficients are almost entirely determined by orientation of particles and do not depend on particle sizes and shapes. The phases of these coefficients can be used to detect the presence of melting hail or wet snow in the radar resolution volume.

A model of the mean canting angle of raindrops varying along a propagation path is developed to examine effects of propagation on the depolarization variables such as ρ _xh , ρ _xυ , and linear depolarization ratio. Analysis shows that depolarization variables are very sensitive to the mean canting angle averaged over a long propagation path.

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.

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.

Abstract

Soon, the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) network will be upgraded to allow dual-polarization capabilities. Therefore, it is imperative to understand and identify microphysical processes using the polarimetric variables. Though melting and size sorting of hydrometeors have been investigated, there has been relatively little focus devoted to the impacts of evaporation on the polarimetric characteristics of rainfall. In this study, a simple explicit bin microphysics one-dimensional rainshaft model is constructed to quantify the impacts of evaporation (neglecting the collisional processes) on vertical profiles of polarimetric radar variables in rain. The results of this model are applicable for light to moderate rain (<10 mm h⁻¹). The modeling results indicate that the amount of evaporation that occurs in the subcloud layer is strongly dependent on the initial shape of the drop size distribution aloft, which can be assessed with polarimetric measurements. Understanding how radar-estimated rainfall rates may change in height due to evaporation is important for quantitative precipitation estimates, especially in regions far from the radar or in regions of complex terrain where low levels may not be adequately sampled. In addition to quantifying the effects of evaporation, a simple method of estimating the amount of evaporation that occurs in a given environment based on polarimetric radar measurements of the reflectivity factor Z_H and differential reflectivity Z _DR aloft is offered. Such a technique may be useful to operational meteorologists and hydrologists in estimating the amount of precipitation reaching the surface, especially in regions of poor low-level radar coverage such as mountainous regions or locations at large distances from the radar.

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 Φ_DP 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 Φ_DP signatures strongly depend on the orientation of crystals and a system differential phase on transmission.

Abstract

Differential sedimentation of precipitation occurs because heavier hydrometeors fall faster than lighter ones. Updrafts and vertical wind shear can maintain this otherwise transient size sorting, resulting in prolonged regions of ongoing particle sorting in storms. This study quantifies the impact of size sorting on the S-band polarimetric radar variables (radar reflectivity factor at horizontal polarization Z_H , differential reflectivity Z _DR, specific differential phase K _DP, and the copolar cross-correlation coefficient ρ _hv). These variables are calculated from output of two idealized bin models: a one-dimensional model of pure raindrop fallout and a two-dimensional rain shaft encountering vertical wind shear. Additionally, errors in the radar variables as simulated by single-, double-, and triple-moment bulk microphysics parameterizations are quantified for the same size sorting scenarios.

Size sorting produces regions of sparsely concentrated large drops with a lack of smaller drops, causing Z _DR enhancements as large as 1 dB in areas of decreased Z_H , often along a Z_H gradient. Such areas of enhanced Z _DR are offset from those of high Z_H and K _DP. Illustrative examples of polarimetric radar observations in a variety of precipitation regimes demonstrate the widespread occurrence of size sorting and are consistent with the bin model simulations. Single-moment schemes are incapable of size sorting, leading to large underestimations in Z _DR (>2 dB) compared to the bin model solution. Double-moment schemes with a fixed spectral shape parameter produce excessive size sorting by incorrectly increasing the number of large raindrops, overestimating Z _DR by 2–3 dB. Three-moment schemes with variable shape parameters better capture the narrowing drop size distribution resulting from size sorting but can underestimate Z _DR and overestimate K _DP by as much as 20%. Implications for polarimetric radar data assimilation into storm-scale numerical weather prediction models are discussed.

Abstract

The dual-polarization radar variables are especially sensitive to the microphysical processes of melting and size sorting of precipitation particles. In deep convective storms, polarimetric measurements of such processes can provide information about the airflow in and around the storm that may be used to elucidate storm behavior and evolution. Size sorting mechanisms include differential sedimentation, vertical transport, strong rotation, and wind shear. In particular, winds that veer with increasing height typical of supercell environments cause size sorting that is manifested as an enhancement of differential reflectivity (Z _DR) along the right or inflow edge of the forward-flank downdraft precipitation echo, which has been called the Z _DR arc signature. In some cases, this shear profile can be augmented by the storm inflow. It is argued that the magnitude of this enhancement is related to the low-level storm-relative environmental helicity (SRH) in the storm inflow.

To test this hypothesis, a simple numerical model is constructed that calculates trajectories for raindrops based on their individual sizes, which allows size sorting to occur. The modeling results indicate a strong positive correlation between the maximum Z _DR in the arc signature and the low-level SRH, regardless of the initial drop size distribution aloft. Additional observational evidence in support of the conceptual model is presented. Potential changes in the Z _DR arc signature as the supercell evolves and the low-level mesocyclone occludes are described.

Abstract

Although radial velocity data from Doppler radars can partially resolve some tornadoes, particularly large tornadoes near the radar, most tornadoes are not explicitly resolved by radar owing to inadequate spatiotemporal resolution. In addition, it can be difficult to determine which mesocyclones typically observed on radar are associated with tornadoes. Since debris lofted by tornadoes has scattering characteristics that are distinct from those of hydrometeors, the additional information provided by polarimetric weather radars can aid in identifying debris from tornadoes; the polarimetric tornadic debris signature (TDS) provides what is nearly “ground truth” that a tornado is ongoing (or has recently occurred). This paper outlines a modification to the hydrometeor classification algorithm used with the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) network in the United States to include a TDS category. Examples of automated TDS classification are provided for several recent cases that were observed in the United States.

Abstract

Diabatic cooling from hydrometeor phase changes in the stratiform melting layer is of great interest to both operational forecasters and modelers for its societal and dynamical consequences. Attempts to estimate the melting-layer cooling rate typically rely on either the budgeting of hydrometeor content estimated from reflectivity Z or model-generated lookup tables scaled by the magnitude of Z in the bright band. Recent advances have been made in developing methods to observe the unique polarimetric characteristics of melting snow and the additional microphysical information they may contain. However, to date no work has looked at the thermodynamic information available from the polarimetric radar brightband signature. In this study, a one-dimensional spectral bin model of melting snow and a coupled polarimetric operator are used to study the relation between the polarimetric radar bright band and the melting-layer cooling rate. Simulations using a fixed particle size distribution (PSD) and variable environmental conditions show that the height and thickness of the bright band and the maximum brightband Z and specific differential phase shift $K_{\text{DP}}$ are all sensitive to the ambient environment, while the differential reflectivity $Z_{\text{DR}}$ is relatively insensitive. Additional simulations of 2700 PSDs based on in situ observations above the melting layer indicate that the maximum Z, $\mathrm{\Delta }Z$ , and $Z_{\text{DR}}$ within the melting layer are poorly correlated with the maximum cooling rate while $K_{\text{DP}}$ is strongly correlated. Finally, model simulations suggest that, in addition to riming, concurrent changes in aggregation and precipitation intensity and the associated cooling may plausibly cause observed sagging brightband signatures.