Polarization Radar Measurements Research Articles

Multi-channel and multi-polarization radar measurements around the NEEM site

Abstract. Ice properties inferred from multi-polarization measurements, such as birefringence and crystal orientation fabric (COF), can provide insight into ice strain, viscosity, and ice flow. In 2008, the Center for Remote Sensing of Ice Sheets (CReSIS) used a ground-based VHF (very high frequency) radar to take multi-channel and multi-polarization measurements around the NEEM (North Greenland Eemian Ice Drilling) site. The system operated with 30 MHz bandwidth at a center frequency of 150 MHz. This paper describes the radar system, antenna configurations, data collection, and processing and analysis of this data set. Within the framework derived from uniaxial ice crystal model, we found that ice birefringence dominates the power variation patterns of co-polarization and cross-polarization measurements in the area of 100 km2 around the ice core site. The phase shift between ordinary and extraordinary waves increases nonlinearly with depth. The ice optic axis lies in planes that are close to the vertical plane and perpendicular or parallel to the ice divide depending on depth. The ice optic axis has an average tilt angle of about 11.6° vertically, and its plane may rotate either clockwise or counterclockwise by about 10° across the 100 km2 area, and at a specific location the plane may rotate slightly counterclockwise as depth increases. Comparisons between the radar observations, simulations, and ice core fabric data are in very good agreement. We calculated the effective colatitude at different depths by using azimuth and colatitude measurements of the c axis of ice crystals. We obtained an average effective c axis tilt angle of 9.6° from the vertical axis, very comparable to the average optic axis tilt angle estimated from radar polarization measurements. The comparisons give us confidence in applying this polarimetric radio echo sounding technique to infer profiles of ice fabric in locations where there are no ice core measurements.

Interpretation of observed microwave signatures from ground dual polarization radar and space multi-frequency radiometer for the 2011 Grímsvötn volcanic eruption

Abstract. The important role played by ground-based microwave weather radars for the monitoring of volcanic ash clouds has been recently demonstrated. The potential of microwaves from satellite passive and ground-based active sensors to estimate near-source volcanic ash cloud parameters has been also proposed, though with little investigation of their synergy and the role of the radar polarimetry. The goal of this work is to show the potentiality and drawbacks of the X-band dual polarization (DPX) radar measurements through the data acquired during the latest Grímsvötn volcanic eruptions that took place in May 2011 in Iceland. The analysis is enriched by the comparison between DPX data and the observations from the satellite Special Sensor Microwave Imager/Sounder (SSMIS) and a C-band single polarization (SPC) radar. SPC, DPX, and SSMIS instruments cover a large range of the microwave spectrum, operating respectively at 5.4, 3.2, and 0.16–1.6 cm wavelengths.

Classification of Ground Clutter and Anomalous Propagation Using Dual-Polarization Weather Radar

This paper presents the results of a study designed to classify weather radar clutter echoes obtained from ground-based dual-polarization weather radar systems. The clutter signals are due to ground clutter, sea clutter, and anomalous propagation echoes, which represent sources of error in quantitative radar rainfall estimation. Fuzzy and Bayes classifiers are evaluated as an alternative approach to traditional polarimetric-based methods. Both systems were trained and validated by using C-band dual- polarization radar measurements, and a novel technique is proposed to calculate the texture function to mitigate against the edge effects at the boundaries of precipitation regions. A methodology is presented to extract the membership functions and conditional probability density functions to train the classifiers. The critical success index indicates that the Bayes classifier has, on average, a slightly better performance than the fuzzy classifiers. However, when optimal weighting was applied, the fuzzy classifier gave one of the best performances. The classifiers are sufficiently robust to be used when only single-polarization radar measurements are available.

Improving Parameterization of Rain Microphysics with Disdrometer and Radar Observations

Abstract Disdrometer observations indicate that the raindrop size distribution (DSD) can be represented by a constrained-gamma (CG) distribution model. The model is used to retrieve DSDs from polarization radar measurements of reflectivity and differential reflectivity and to characterize rain microphysics and physical processes such as evaporation, accretion, and precipitation. The CG model parameterization is simplified to a single parameter for application in single-moment numerical models. This simplified parameterization is applied in the Variational Doppler Radar Analysis System (VDRAS) using Kessler-type parameterizations for model initialization and forecasting. Results are compared to those for the Marshall–Palmer (MP) DSD model. It is found that the simplified CG model parameterization better preserves the stratiform rain and produces better forecasts than the MP model parameterization.

Detection of snow and ice crystals using polarization radar measurements: comparison between ground-based in situ and S-Pol observations

Polarimetric radars have the potential of identifying ‘bulk’ hydrometeor types within the radar volume by, for example, combining various polarimetric observables. Semiempirical, rule-based hydrometeor identification algorithms have been developed for the linear polarimetric S-Pol radar of the National Center of Atmospheric Research (NCAR). S-Pol was deployed during the field phase of the Mesoscale Alpine Programme (MAP) in Northern Italy for 10 weeks during the fall of 1999. It was a key instrument for one specific objective of MAP, namely, the orographically induced heavy precipitation events at the southern slopes of the Alps. During MAP, two hydrometeor type identification algorithms were implemented for real-time display. While the algorithm developed at the University of Washington (UW) uses fixed boundaries in polarimetric space, the algorithm developed at NCAR uses a fuzzy logic approach. The performance of the algorithms was tested using ground-based in situ observations from a mountain station located 65 km from the radar. This observation included the use of Formvar replicas that preserve solid precipitation particles on a microscope slide, and optical spectrometer providing information on size spectra. In situ data of two case studies from MAP provided detailed information on snow and ice crystals and were therefore suitable for a comparison to radar-based hydrometeor type detection. Because of spatial and temporal differences in the observation, the comparison is discussed qualitatively. The algorithms are considered successful when a good qualitative correlation could be found between the evolution of the hydrometeor types observed by in situ measurements, and the evolution observed remotely. Results based on the NCAR algorithm consistently performed better than the UW algorithm in both cases.

Using cloud radar polarization measurements to evaluate stratus cloud and insect echoes

Suspended insects and other nonhydrometeor particulates are commonly detected in and near the planetary boundary layer by high‐sensitivity millimeter‐wave cloud radars. Radar reflectivity patterns of these targets are difficult to discern from those of stratus clouds, and therefore these particles represent undesirable contaminants for automated cloud‐detection algorithms. Radar polarization measurements, however, offer a means of distinguishing between cloud droplets and these contaminants, based on the shape information contained in depolarization ratio observations. A procedure is presented which allows dual‐polarization cloud radar data and simultaneous lidar and laser ceilometer data to determine the presence of cloud droplets alone, insects alone, and mixtures of the two at the Atmospheric Radiation Measurement program's Cloud and Radiation Test bed sites. Theory is also developed for estimating the contribution of cloud droplets to the observed reflectivity of an insect plus droplet mixture using dual‐polarization cloud radar data. Preliminary data indicate that the method provides more accurate estimates if the radar transmits circular rather than linear polarization because the effects of target orientation are minimized.

An automatic identification of clutter and anomalous propagation in polarization-diversity weather radar data using neural networks

Radar polarization measurements have mostly been used to improve rainfall estimation and hydrometeor characterization. The authors extend the use of such measurements to the problem of ground clutter recognition, including the case when this problem is associated with anomalous propagation of the electromagnetic wave. They present a methodology used for recognizing both clutter and meteorological targets. The methodology is based on the knowledge of the scattering properties of the targets, as provided by the polarization measurements and the use of the neural network approach that performs the classification. The results show that if circular polarization is used, the circular depolarization ratio and the degree of polarization are good discriminators of clutter and nonclutter. They have used data from the Alberta polarization diversity radar to build an automatic decision process using a feedforward neural network. After they trained the neural network, they tested the classifier for two common clutter situations: when there is an electromagnetic wave anomalous propagation and when targets from rain are mixed with the clutter close to the radar.

Drop-size distributions of raindrops by polarization radar and simultaneous measurements with disdrometer, windprofiler and PMS probes

Drop-size distributions of raindrops by polarization radar and simultaneous measurements with disdrometer, windprofiler and PMS probes

Drop‐size distributions of raindrops by polarization radar and simultaneous measurements with disdrometer, windprofiler and PMS probes

AbstractMultiparameter polarimetric weather radars offer the possibility of estimating raindrop size distribution directly. the retrieved parameters of exponential drop‐size distributions are compared with discrete drop‐size spectra obtained from a vertical‐pointing radar (windprofiler type), airborne particle measuring systems (PMS) probes and a disdrometer. the windprofiler and PMS probes allow simultaneous measurements at almost the same location. This unique data set shows that radar‐estimated drop‐size distributions can be retrieved with the same quality as distributions from other standard instruments. Results obtained with a C‐band radar during the CLEOPATRA (Cloud Experiment Oberpfaffenhofen and Transports) campaign in southern Germany are confirmed by measurements with an S‐band radar in southern England. the quality of the estimated rain rate is high, but differences in quantity can be caused not only by differences in the instrumental set‐up but also by deviation from an exponential shape of the drop‐size distribution.

Error structure of radar rainfall measurement at C‐band frequencies with dual polarization algorithm for attenuation correction

A simple procedure is developed to estimate specific attenuation and differential attenuation at C‐band frequencies from the dual polarization radar measurements, reflectivity at horizontal polarization (ZH), and differential reflectivity (ZDR). An algorithm is presented to correct C‐band reflectivity and differential reflectivity measurements for absolute attenuation and differential attenuation, respectively. The effect of the attenuation correction procedure on the error structure of rainfall estimation is studied by utilizing data collected by the dual polarized C‐band radar, POLAR 55C, as well as a network of rain gages over the Arno River basin near Florence, Italy. Radar rainfall estimates are compared over two small basins, one close to the radar, at a distance of 35 km, and the other farther from the radar, at a distance of 65 km, where the effect of attenuation is likely to be more significant. On the basis of a comparative study of radar and rain gage measurements over the two basins it is shown that the attenuation correction improves the radar rainfall estimates based on Z‐R algorithms for both basins. The correction procedure improves the radar rainfall estimates based on dual polarization algorithm for the farther basin; however, the attenuation correction does not improve the radar rainfall estimates based on dual polarization algorithm for the closer basin (when the differential attenuation is not significant).

Estimation of Ice Hydrometeor Types and Shapes from Radar Polarization Measurements

Abstract An approach to distinguish between various types of ice hydrometeors and to estimate their shapes using radar polarization measurements is discussed. It is shown that elevation angle dependencies of radar depolarization ratios can be used to distinguish between planar crystals, columnar crystals, and aggregates in reasonably homogeneous stratiform clouds. Absolute values of these ratios depend on the reflectivity-weighted mean particle aspect ratio in the polarization plane. Circular depolarization ratios depend on this ratio, and linear depolarization ratios depend on this ratio and particle orientation in the polarization plane. The use of nearly circular elliptical polarization provides a means of measuring depolarization for low reflectivity scatterers when the circular polarization fails due to low signal level in one of the receiving channels. Modeling of radar backscattering was applied to the elliptical depolarization ratios as measured by the Ka-band radar developed at the NOAA Environme...

A Study of Embryo Production and Hail Growth Using Dual-Doppler and Multiparameter Radars

The origin and importance to embryo and hail production of a region of drops advected above the freezing level in the updraft of a severe Colorado hailstorm is examined using radar polarization measurements in conjunction with dual-Doppler and trajectory analysis. These drops, which give a distinct radar signature termed the “differential reflectivity column,” originate from 1) melted hydrometeors that fall from the back-sheared anvil, through the embryo curtain, and are recirculated into the storm updraft, and 2) in situ drop growth within the updraft. Some of the drops refreeze and likely produce frozen-drop hailstone embryos. Numerous hailstone trajectories are found to cross either through, or over, the drop column where the hailstones undergo a significant growth phase. Two separate hailstone fallout regions are identified. Some hailstones in the northern fallout region show anticyclonic trajectories and in situ updraft and column growth. Others grow while crossing the top of the vault. Hailstones in the southern region exhibit growth while passing cyclonically through the column or over the vault. A new method to determine hydrometeor fall speeds from radar polarization measurements for use with dual-Doppler analysis is introduced.

Rainfall and Clutter Discrimination by Means of Dual-linear Polarization Radar Measurements

The presence of undetected mixed-phase precipitation or superimposed intense clutter can cause serious errors in the estimation of rainfall rate and other parameters of precipitation occurring in the radar scattering volume. To reduce or avoid these errors it is necessary to distinguish between the rain echo, and that due to other types of precipitation, and between precipitation radar echoes and ground clutter. Multiparameter radar measurements may be exploited for this discrimination. In particular, it is demonstrated that dual-linear polarization measurements may play a major role in this process. Sample radar data are employed to illustrate several different tests to classify radar data: the results refer to comparisons of dual-polarized echoes due to precipitation (rain or mixed-phase event) and land with echoes from land alone. This is illustrated by example through the application of a series of tests on a clutter-contaminated dual-polarized dataset obtained during the May Polarization Experiments (MAYPOLE) 1984 field program in Colorado.

Polarization Radar Measurements in Rain at 5 and 9 GHz

Potential techniques for measuring rainfall rate R and rainwater content W at 9 and 5 GHz are explored. An investigation is made of a previous technique to use the polarization propagation differential phase shift with increasing distance from the radar Phi(H-V) to estimate and remove the effects of specific and polarization differential attenuation from Z(H) and Z(DR), respectively. It is shown that in rain this technique is sensitive to variations in the drop-size distribution. It is confirmed that Phi(H-V) can be used to extend the distance over which useful measurements of Z(H) and Z(DR) can be obtained. While residual errors introduced by attenuation and the 'noise' from the correction scheme itself eclipse the potential of many possible techniques for quantitative rainfall measurements at these frequencies, the attenuation recovery scheme is argued to be adequate for obtaining useful polarization microphysical measurements, particularly above the melting level, even after encounters with rain.

Deducing the Microphysical Character of Precipitation from Multiple-Parameter Radar Polarization Measurements

Abstract Radar polarization measurements are influenced by the distribution of shapes (weighted by the index of refraction) and the fall behaviors of the hydrometeors. In so far as precipitation-sized hydrometeors are symmetric oblates in the Rayleigh-Gans scattering regime, the effects of canting and shapes can, in principle, be separated using the co- and cross-polarized backscattered signals at both horizontal and vertical polarizations. These measurements yield estimates of the variance of a two-parameter distribution of canting angles as well as the refractive index weighted estimates of the mean and variance of the shape (axis ratio) distribution. To the extent that hydrometeor asymmetries can be neglected, these quantities provide a possible framework for precipitation identification from radar polarization measurements at long wavelengths.

Estimation of Propagation-Differential Phase Shift from Sequential Orthogonal Linear Polarization Radar Measurements

Abstract As radar waves at different polarizations propagate through a medium of nonspherical, oriented scatterers a phase difference between the waves appears. A method is proposed for estimating this propagation-differential phase shift using sequential measurements at alternating horizontal and vertical polarizations. As a consequence, several new potentially useful parameters can be extracted from alternating horizontal and vertical co-polarization measurements.

Microphysical Interpretation of Multi-Parameter Radar Measurements in Rain. Part II: Estimation of Raindrop Distribution Parameters by Combined Dual-Wavelength and Polarization Measurements

The radar reflectivity weighted mean axis ratio R¯ and the variance of the axis ratio distribution σR2 of an ensemble of raindrops can be estimated from polarization radar measurements. If the shape function relating axis ratio to drop size is known or measured, then these quantities may be transformed into the radar reflectivity weighted mean diameter D and, in the case of quiescent drops, into the variance of the raindrop size distribution σD2. Although these parameters are of intrinsic meteorological interest, estimates of the rainfall rate in still air R0 and of liquid water content W can also be constructed. In principle, estimates using both D¯ and σD2 appear, potentially, to be more accurate than estimates based only on D¯. Realization of this potential improvement probably depends on the development of techniques to extract that component of σD2 arising solely from the raindrop size distribution.