A Bayesian Approach for Integrated Raindrop Size Distribution (DSD) Retrieval on an X-Band Dual-Polarization Radar Network

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.

2008 ◽  
Vol 9 (3) ◽  
pp. 589-600 ◽  
Author(s):  
Marios N. Anagnostou ◽  
Emmanouil N. Anagnostou ◽  
Jothiram Vivekanandan ◽  
Fred L. Ogden

Abstract In this study the authors evaluate two algorithms, the so-called beta (β) and constrained methods, proposed for retrieving the governing parameters of the “normalized” gamma drop size distribution (DSD) from dual-polarization radar measurements. The β method treats the drop axis ratio as a variable and computes drop shape and DSD parameters from radar reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase shift (KDP). The constrained method assumes that the axis-ratio relation is fixed and computes DSD parameters from ZH, ZDR, and an empirical relation between the DSD slope and shape parameters. The two techniques are evaluated for polarimetric X-band radar observations by comparing retrieved DSD parameters with disdrometer observations and examining simulated radar parameters for consistency. Error effects on the β method and constrained method retrievals are analyzed. The β approach is found to be sensitive to errors in KDP and to be less consistent with observations. Large retrieved β values are found to be associated with large retrieved DSD shape parameters and small median drop diameters. The constrained method provides reasonable rain DSD retrievals that agree better with disdrometer observations.


2014 ◽  
Vol 53 (6) ◽  
pp. 1618-1635 ◽  
Author(s):  
Elisa Adirosi ◽  
Eugenio Gorgucci ◽  
Luca Baldini ◽  
Ali Tokay

AbstractTo date, one of the most widely used parametric forms for modeling raindrop size distribution (DSD) is the three-parameter gamma. The aim of this paper is to analyze the error of assuming such parametric form to model the natural DSDs. To achieve this goal, a methodology is set up to compare the rain rate obtained from a disdrometer-measured drop size distribution with the rain rate of a gamma drop size distribution that produces the same triplets of dual-polarization radar measurements, namely reflectivity factor, differential reflectivity, and specific differential phase shift. In such a way, any differences between the values of the two rain rates will provide information about how well the gamma distribution fits the measured precipitation. The difference between rain rates is analyzed in terms of normalized standard error and normalized bias using different radar frequencies, drop shape–size relations, and disdrometer integration time. The study is performed using four datasets of DSDs collected by two-dimensional video disdrometers deployed in Huntsville (Alabama) and in three different prelaunch campaigns of the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) ground validation program including the Hydrological Cycle in Mediterranean Experiment (HyMeX) special observation period (SOP) 1 field campaign in Rome. The results show that differences in rain rates of the disdrometer DSD and the gamma DSD determining the same dual-polarization radar measurements exist and exceed those related to the methodology itself and to the disdrometer sampling error, supporting the finding that there is an error associated with the gamma DSD assumption.


2014 ◽  
Vol 31 (2) ◽  
pp. 387-403 ◽  
Author(s):  
Eiichi Yoshikawa ◽  
V. Chandrasekar ◽  
Tomoo Ushio

Abstract A raindrop size distribution (DSD) retrieval method for a dual-polarization radar at attenuating frequency is proposed. The proposed method is developed such that the range profiles of the gamma DSD parameters, an intercept parameter Nw (mm−1 m−3), and a median volume diameter D0 (mm) can be estimated to match the dual-polarization measurements, measured equivalent reflectivity at horizontal polarization ZHm, measured differential reflectivity ZDRm, and measured differential propagation phase ΦDPm, where the forward scattering and backscattering are formulated simultaneously to avoid the two-step process of attenuation correction and DSD retrieval. Additionally, the proposed method does not have the attenuation-correction errors accumulated along range that traditional forward and backward processes have, since the range profiles of the DSD parameters are optimized in a radar beam simultaneously. In the simulation, the proposed algorithm showed fairly good accuracies for retrievals Nw and D0. Errors with the different axis ratio models or calibration biases in ZHm and ZDRm, which contaminate assumptions of the proposed method in real observational data, were also evaluated. Under a Gaussian fluctuation model, the estimation process, known as an iterative maximum-likelihood estimator, derives the best estimation in the statistical fluctuation conditions. This scheme could be extended to duplicative observation such as a radar network environment.


2002 ◽  
Vol 59 (15) ◽  
pp. 2373-2384 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
V. N. Bringi ◽  
Gianfranco Scarchilli

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.


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