Showing papers by "Guifu Zhang published in 2015"
TL;DR: Results obtained from simulation show that the planar polarimetric phased array radar has unacceptable polarIMetric parameter biases that require beam to beam correction, whereas biases obtained with the cylindrical polarimetry phased array Radar are much lower and comparable to that obtained using the parabolic reflector antenna.
Abstract: Planar or cylindrical phased arrays are two candidate antennas for future polarimetric weather radar. These two candidate antennas have distinctly different attributes when used to make quantitative measurements of the polarimetric properties of precipitation. Of critical concern is meeting the required polarimetric performance for all directions of the electronically steered beam. The copolar and cross-polar radiation patterns and polarimetric parameter estimation performances of these two phased array antennas are studied and compared with that obtained using a dual-polarized parabolic reflector antenna. Results obtained from simulation show that the planar polarimetric phased array radar has unacceptable polarimetric parameter biases that require beam to beam correction, whereas biases obtained with the cylindrical polarimetric phased array radar are much lower and comparable to that obtained using the parabolic reflector antenna.
32 citations
TL;DR: In this article, a multi-variable Bayesian classification algorithm was applied to 2Dimensional video disdrometer (2DVD) data, collected in central Oklahoma, to the problem of convective-stratiform rain separation.
12 citations
TL;DR: To achieve low sidelobes and matched beams, pattern synthesis using an optimization method is presented and results reported herein support the idea that CPPARs can be designed and implemented for accurate weather measurements.
Abstract: Accurate radar remote sensing requires a radar system with high cross-polarization isolation, highly matched dual-polarization patterns, and low sidelobes. A cylindrical polarimetric phased-array radar (CPPAR), which has polarization purity and scan-invariant beam properties, has recently been introduced to the weather and air surveillance communities. To achieve low sidelobes and matched beams, pattern synthesis using an optimization method is presented. Results reported herein support the idea that CPPARs can be designed and implemented for accurate weather measurements. Furthermore, some uncertainty analysis is performed to show the effects of the amplitude and phase errors on the radiation patterns of the PAR.
12 citations
TL;DR: In this paper, Zhang et al. pointed out that the gamma DSD model with a sm-Dm relation is essentially equivalent to the C-G model with m-L relation that has already been introduced.
Abstract: In the radar remote sensing of precipitation, a twoparameter raindrop size distribution (DSD) model is needed to facilitate an observation-based retrieval because both the network of dual-polarization Weather Surveillance Radar-1988 Doppler (WSR-88D) instruments and the Global Precipitation Measurement dual-frequency radar each provide two independent measurements. A two-parameter DSD model is also needed for two-moment microphysics parameterizations in numerical weather prediction (Zhang et al. 2006). Since the m–L relation was introduced to reduce the three parameters of the gamma distribution model to the two parameters of the constrained-gamma (C-G) model for rainDSDs (Zhang et al. 2001, 2003), there have been many papers, including this one (Williams et al. 2014), publishing new constraints and debating the validity of the C-Gmodel in remote sensing applications. It is great to see these papers because they further our understanding of the C-G DSD model, but there is some confusion regarding how the C-G models are similar/ different and how to accurately derive and use a valid constraint. The confusion needs to be clarified, which is the motivation for this comment. My first point is that the gamma DSD model with a sm–Dm relation (Williams et al. 2014) is essentially equivalent to the C-G model with a m–L relation that has already been introduced (Zhang et al. 2001), which can be shown in both the equations and the plots of the parameters (m–L vs sm–Dm). People should think of the gammaDSDmodel constrained by either am–L relation or a sm–Dm relation as just another two-parameterDSD model, like the exponential distribution model, the gamma distribution model with a fixed m, or the gamma distribution model with a m–Dm relation. The C-G model is equivalent to the normalized DSD model with two parameters (Testud et al. 2001), as shown in Figs. 9 and 10 of Cao and Zhang (2009). It is also similar to the gamma DSD model that is represented by three uncorrelated/independent parameters through parameter transformation in which the three DSD parameters are transformed into a set of three new parameters but one of new parameters is fixed/predetermined (Haddad et al. 1996, 1997, 2006). For a better understating of themodel similarity, let us first provide some fundamentals about the gamma DSD model. For a gamma DSD ofN(D)5N0D m exp(2LD), the nth moment of the DSD (ignoring truncation effects for simplicity) is
6 citations
TL;DR: A weighted average of autocorrelations of radar signals from three consecutive radials is proposed to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times.
Abstract: When spectral moments in the azimuth are spaced by less than a beamwidth, it is called oversampling. Superresolution is a type of oversampling that refers to sampling at half a beamwidth on the national network of Doppler weather radars [Weather Surveillance Radar-1988 Doppler (WSR-88D)]. Such close spacing is desirable because it extends the range at which small severe weather features, such as tornadoes or microbursts, can be resolved. This study examines oversampling for phased array radars. The goal of the study is to preserve the same effective beamwidth as on the WSR-88D while obtaining smaller spectral moment estimate errors at the same or faster volume update times. To that effect, a weighted average of autocorrelations of radar signals from three consecutive radials is proposed. Errors in three spectral moments obtained from these autocorrelations are evaluated theoretically. Methodologies on how to choose weights that preserve the desirable effective beamwidth are presented. The results ...
4 citations