ESTIMATION OF RAINDROP SIZE DISTRIBUTION AND PRECIPITATION USING X-BAND MULTI-PARAMETER RADAR INFORMATION

2018 ◽  
Vol 74 (5) ◽  
pp. I_247-I_252
Author(s):  
Yasutaka WAKAZUKI ◽  
Naoki INABA ◽  
Kosei YAMAGUCHI ◽  
Eiichi NAKAKITA
Keyword(s):  
Size Distribution ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size ◽  
Radar Information

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
Keyword(s):  
Size Distribution ◽  
Estimation Accuracy ◽  
Dual Polarization ◽  
Estimation Errors ◽  
Axis Ratio ◽  
Radar Network ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Radar Measurements ◽  
Raindrop Size

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.

scholarly journals Retrieval of the raindrop size distribution from polarimetric radar data using double-moment normalisation

2016 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Climatic Regions ◽  
Retrieval Technique ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Double Moment ◽  
Raindrop Size ◽  
A New Technique

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.

Comparison of Two Raindrop Size Distribution Retrieval Algorithms for X-Band Dual Polarization Observations

2008 ◽  
Vol 9 (3) ◽  
pp. 589-600 ◽  
Author(s):  
Marios N. Anagnostou ◽  
Emmanouil N. Anagnostou ◽  
Jothiram Vivekanandan ◽  
Fred L. Ogden
Keyword(s):  
Size Distribution ◽  
Empirical Relation ◽  
Shape Parameters ◽  
Dual Polarization ◽  
Axis Ratio ◽  
Differential Phase Shift ◽  
Drop Shape ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size

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.

scholarly journals Improving the rainfall rate estimation in the midstream of the Heihe River Basin using raindrop size distribution

2011 ◽  
Vol 15 (3) ◽  
pp. 943-951 ◽  
Author(s):  
G. Zhao ◽  
R. Chu ◽  
T. Zhang ◽  
J. Li ◽  
J. Shen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Tibet Plateau ◽  
Heihe River ◽  
Drop Diameter ◽  
Observation Data ◽  
Polarimetric Radar ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size

Abstract. During the intensive observation period of the Watershed Allied Telemetry Experimental Research (WATER), a total of 1074 raindrop size distribution were measured by the Parsivel disdrometer, the latest state-of-the-art optical laser instrument. Because of the limited observation data in Qinghai-Tibet Plateau, the modelling behaviour was not well done. We used raindrop size distributions to improve the rain rate estimator of meteorological radar in order to obtain many accurate rain rate data in this area. We got the relationship between the terminal velocity of the raindrop and the diameter (mm) of a raindrop: v(D) = 4.67D0.53. Then four types of estimators for X-band polarimetric radar are examined. The simulation results show that the classical estimator R (ZH) is most sensitive to variations in DSD and the estimator R (KDP, ZH, ZDR) is the best estimator for estimating the rain rate. An X-band polarimetric radar (714XDP) is used for verifying these estimators. The lowest sensitivity of the rain rate estimator R (KDP, ZH, ZDR) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 3rd power of the drop diameter. On the other hand, the exponent of the backscatter cross-section, which contributes to ZH, is proportional to the 6th power of the drop diameter. Because the rain rate R is proportional to the 3.57th power of the drop diameter, KDP is less sensitive to DSD variations than ZH.

scholarly journals Perbandingan Karakteristik Distribusi Butiran Hujan yang Berasal dari Awan Laut dan Awan Darat di Kototabang

2016 ◽  
Vol 5 (3) ◽  
pp. 273-282
Author(s):  
Nur Fadillah ◽  
Marzuki Marzuki ◽  
Wendi Harjupa ◽  
Toyoshi Shimomai ◽  
Hiroyuki Hashiguchi
Keyword(s):  
Size Distribution ◽  
Doppler Radar ◽  
Radar Reflectivity ◽  
Two Dimensional ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size ◽  
Coupling Processes

Karakteristik distribusi ukuran butiran hujan atau raindrop size distribution (RDSD) dari hujan yang berasal dari awan laut dan awan darat di Kototabang, Sumatera Barat, telah dibandingkan. Asal hujan diamati menggunakan X-band Doppler radar (XDR) selama proyek Coupling Processes in the Equatorial Atmosphere (CPEA)-I (10 April 2004 - 9 Mei 2004). Data RDSD berasal dari pengamatan two-dimensional video disdrometer (2DVD). RDSD dimodelkan dengan distribusi gamma dan parameternya didapatkan menggunakan metode momen. Dari penelitian ini terlihat bahwa intensitas curah hujan yang tinggi lebih banyak pada hujan dari awan darat dibandingkan dengan yang dari awan laut. Selain itu, butiran hujan yang berukuran besar pada awan darat lebih banyak daripada awan laut. Banyaknya butiran hujan dengan ukuran yang besar ini berdampak kepada nilai radar reflectivity (Z) pada awan darat yang lebih besar dibandingkan dengan awan laut untuk intensitas curah hujan yang sama. Hal ini mengakibatkan persamaan Z-R antara awan darat dan awan laut berbeda dimana nilai koefisien A dari persamaan Z-R untuk awan darat lebih besar daripada awan laut. Dengan demikian, perbedaan karaktersitik RDSD antara awan darat dan laut sebaiknya dipertimbangkan dalam pengembangan radar meteorologi di kawasan tropis. Penggunaan Z-R tunggal (Z = 200R1,6) untuk mengkoversi data radar cuaca di Sumatera terutama Sumatera Barat tidak akan akurat terutama untuk hujan dari awan laut.Kata kunci: distribusi butiran hujan (RDSD), awan darat, awan laut, Kototabang

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