scholarly journals Polarimetric X-band weather radar measurements in the tropics: radome and rain attenuation correction

2012 ◽  
Vol 5 (9) ◽  
pp. 2183-2199 ◽  
Author(s):  
M. Schneebeli ◽  
J. Sakuragi ◽  
T. Biscaro ◽  
C. F. Angelis ◽  
I. Carvalho da Costa ◽  
...  

Abstract. A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with three additional laser disdrometers. The disdrometers are capable of measuring the raindrop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This set-up allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. For the campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps was analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured at a distance of 20 km from the radar. Radome attenuation reached values up to 14 dB which was found to be consistent with an empirical radome attenuation vs. rain intensity relation that was previously developed for the same radar type. In contrast to previous work, our results suggest that radome attenuation should be estimated individually for every view direction of the radar in order to obtain homogenous reflectivity fields.

2012 ◽  
Vol 5 (1) ◽  
pp. 1717-1761
Author(s):  
M. Schneebeli ◽  
J. Sakuragi ◽  
T. Biscaro ◽  
C. F. Angelis ◽  
I. Carvalho da Costa ◽  
...  

Abstract. A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with additional sensors like a Ka-band vertically pointing frequency modulated continuous wave (FMCW) radar and three laser disdrometers. The disdrometers as well as the FMCW radar are capable of measuring the rain drop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This set-up allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. In the first campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps is being analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured in a distance of 20 km to the radar.


2008 ◽  
Vol 25 (5) ◽  
pp. 729-741 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Luca Baldini

Abstract The recent advances in attenuation correction methodology are based on the use of a constraint represented by the total amount of the attenuation encountered along the path shared over each range bin in the path. This technique is improved by using the inner self-consistency of radar measurements. The full self-consistency methodology provides an optimization procedure for obtaining the best estimate of specific and cumulative attenuation and specific and cumulative differential attenuation. The main goal of the study is to examine drop size distribution (DSD) retrieval from X-band radar measurements after attenuation correction. A new technique for estimating the slope of a linear axis ratio model from polarimetric radar measurements at attenuated frequencies is envisioned. A new set of improved algorithms immune to variability in the raindrop shape–size relation are presented for the estimation of the governing parameters characterizing a gamma raindrop size distribution. Simulations based on the use of profiles of gamma drop size distribution parameters obtained from S-band observations are used for quantitative analysis. Radar data collected by the NOAA/Earth System Research Laboratory (ESRL) X-band polarimetric radar are used to provide examples of the DSD parameter retrievals using attenuation-corrected radar measurements. Retrievals agree fairly well with disdrometer data. The radar data are also used to observe the prevailing shape of raindrops directly from the radar measurements. A significant result is that oblateness of drops is bounded between the two shape models of Pruppacher and Beard, and Beard and Chuang, the former representing the upper boundary and the latter the lower boundary.


2006 ◽  
Vol 23 (7) ◽  
pp. 952-963 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
Robert Cifelli ◽  
Patrick C. Kennedy ◽  
Steven W. Nesbitt ◽  
Steven A. Rutledge ◽  
...  

Abstract A comparative study of the use of X- and S-band polarimetric radars for rainfall parameter retrievals is presented. The main advantage of X-band polarimetric measurements is the availability of reliable specific differential phase shift estimates, KDP, for lighter rainfalls when phase measurements at the S band are too noisy to produce usable KDP. Theoretical modeling with experimental raindrop size distributions indicates that due to some non-Rayleigh resonant effects, KDP values at a 3.2-cm wavelength (X band) are on average a factor of 3.7 greater than at 11 cm (S band), which is a somewhat larger difference than simple frequency scaling predicts. The non-Rayleigh effects also cause X-band horizontal polarization reflectivity, Zeh, and differential reflectivity, ZDR, to be larger than those at the S band. The differences between X- and S-band reflectivities can exceed measurement uncertainties for Zeh starting approximately at Zeh > 40 dBZ, and for ZDR when the mass-weighted drop diameter, Dm, exceeds about 2 mm. Simultaneous X- and S-band radar measurements of rainfall showed that consistent KDP estimates exceeding about 0.1° km−1 began to be possible at reflectivities greater than ∼26–30 dBZ while at the S band such estimates can generally be made if Zeh > ∼35–39 dBZ. Experimental radar data taken in light-to-moderate stratiform rainfalls with rain rates R in an interval from 2.5 to 15 mm h−1 showed availability of the KDP-based estimates of R for most of the data points at the X band while at the S band such estimates were available only for R greater than about 8–10 mm h−1. After correcting X-band differential reflectivity measurements for differential attenuation, ZDR measurements at both radar frequency bands were in good agreement with each other for Dm < 2 mm, which approximately corresponds to ZDR ≈ 1.6 dB. The ZDR-based retrievals of characteristic raindrop sizes also agreed well with in situ disdrometer measurements.


2013 ◽  
Vol 52 (1) ◽  
pp. 169-185 ◽  
Author(s):  
Qing Cao ◽  
Guifu Zhang ◽  
Ming Xue

AbstractThis study presents a two-dimensional variational approach to retrieving raindrop size distributions (DSDs) from polarimetric radar data in the presence of attenuation. A two-parameter DSD model, the constrained-gamma model, is used to represent rain DSDs. Three polarimetric radar measurements—reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP—are optimally used to correct for the attenuation and retrieve DSDs by taking into account measurement error effects. Retrieval results with simulated data demonstrate that the proposed algorithm performs well. Applications to real data collected by the X-band Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radars and the C-band University of Oklahoma–Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) also demonstrate the efficacy of this approach.


2016 ◽  
Vol 33 (2) ◽  
pp. 377-389 ◽  
Author(s):  
Eiichi Yoshikawa ◽  
V. Chandrasekar ◽  
Tomoo Ushio ◽  
Takahiro Matsuda

AbstractA raindrop size distribution (DSD) retrieval method for a weather radar network consisting of several X-band dual-polarization radars is proposed. An iterative maximum likelihood (ML) estimator for DSD retrieval in a single radar was developed in the authors’ previous work, and the proposed algorithm in this paper extends the single-radar retrieval to radar-networked retrieval, where ML solutions in each single-radar node are integrated based on a Bayesian scheme in order to reduce estimation errors and to enhance accuracy. Statistical evaluations of the proposed algorithm were carried out using numerical simulations. The results with eight radar nodes showed that the bias and standard errors are −0.05 and 0.09 in log(Nw); and Nw (mm−1 m−3) and 0.04 and 0.09 in D0 (mm) in an environment with fluctuations in dual-polarization radar measurements (normal distributions with standard deviations of 0.8 dBZ, 0.2 dB, and 1.5° in ZHm, ZDRm, and ΦDPm, respectively). Further error analyses indicated that the estimation accuracy depended on the number of radar nodes, the ranges of varying μ, the raindrop axis ratio model, and the system bias errors in dual-polarization radar measurements.


2016 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne

Abstract. A new technique for estimating the raindrop size distribution (DSD) from polarimetric radar data is proposed. Two statistical moments of the DSD are estimated from polarimetric variables, and the DSD is reconstructed. The technique takes advantage of the relative invariance of the double-moment normalised DSD. The method was tested using X-band radar data and networks of disdrometers in three different climatic regions. Radar-derived estimates of the DSD compare reasonably well to observations. In the three tested domains, the proposed method performs similarly to and often better than a state-of-the-art DSD-retrieval technique. The approach is flexible because no specific double-normalised DSD model is prescribed. In addition, a method is proposed to treat noisy radar data to improve DSD-retrieval performance with radar measurements.


2001 ◽  
Vol 5 (4) ◽  
pp. 615-628 ◽  
Author(s):  
R. Uijlenhoet

Abstract. The conversion of the radar reflectivity factor Z(mm6m-3) to rain rate R(mm h-1 ) is a crucial step in the hydrological application of weather radar measurements. It has been common practice for over 50 years now to take for this conversion a simple power law relationship between Z and R. It is the purpose of this paper to explain that the fundamental reason for the existence of such power law relationships is the fact that Z and R are related to each other via the raindrop size distribution. To this end, the concept of the raindrop size distribution is first explained. Then, it is demonstrated that there exist two fundamentally different forms of the raindrop size distribution, one corresponding to raindrops present in a volume of air and another corresponding to those arriving at a surface. It is explained how Z and R are defined in terms of both these forms. Using the classical exponential raindrop size distribution as an example, it is demonstrated (1) that the definitions of Z and R naturally lead to power law Z–R relationships, and (2) how the coefficients of such relationships are related to the parameters of the raindrop size distribution. Numerous empirical Z–R relationships are analysed to demonstrate that there exist systematic differences in the coefficients of these relationships and the corresponding parameters of the (exponential) raindrop size distribution between different types of rainfall. Finally, six consistent Z–R relationships are derived, based upon different assumptions regarding the rain rate dependence of the parameters of the (exponential) raindrop size distribution. An appendix shows that these relationships are in fact special cases of a general Z–R relationship that follows from a recently proposed scaling framework for describing raindrop size distributions and their properties. Keywords: radar hydrology, raindrop size distribution, radar reflectivity–rain rate relationship


2006 ◽  
Vol 23 (12) ◽  
pp. 1668-1681 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Luca Baldini

Abstract New algorithms for rain attenuation correction of reflectivity factor and differential reflectivity are presented. Following the methodology suggested for the first time by Gorgucci et al., the new algorithms are developed based on the self-consistency principle, describing the interrelation between polarimetric measurements along the rain medium. There is an increasing interest in X-band radar systems, owing to the early success of the attenuation-correction procedures as well as the initiative of the Center for Collaborative Adaptive Sensing of the Atmosphere to deploy X-band radars in a networked fashion. In this paper, self-consistent algorithms for correcting attenuation and differential attenuation are developed. The performance of the algorithms for application to X-band dual-polarization radars is evaluated extensively. The evaluation is conducted based on X-band dual-polarization observations generated from S-band radar measurements. Evaluation of the new self-consistency algorithms shows significant improvement in performance compared to the current class of algorithms. In the case that reflectivity and differential reflectivity are calibrated between ±1 and ±0.2 dB, respectively, the new algorithms can estimate both attenuation and differential attenuation with less than 10% bias and 15% random error. In addition, the attenuation-corrected reflectivity and differential reflectivity are within 1–0.2 dB 96% and 99% of the time, respectively, demonstrating the good performance.


2005 ◽  
Vol 2 ◽  
pp. 51-57 ◽  
Author(s):  
G. Vulpiani ◽  
F. S. Marzano ◽  
V. Chandrasekar ◽  
R. Uijlenhoet

Abstract. A new model-based iterative technique to correct for attenuation and differential attenuation and retrieve rain rate, based on a neural-network scheme and a differential phase constraint, is presented. Numerical simulations are used to investigate the efficiency and accuracy of this approach named NIPPER. The simulator is based on a T-matrix solution technique, while precipitation is characterized with respect to shape, raindrop size distribution and orientation. A sensitivity analysis is performed in order to evaluate the expected errors of this method. The performance of the proposed methodology on radar measurements is evaluated by using one-dimensional Gaussian shaped rain cell models and synthetic radar data derived from disdrometer measurements. Numerical results are discussed in order to evaluate the robustness of the proposed technique.


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