scholarly journals Dual-polarization radar rainfall estimation in Korea according to raindrop shapes using a 2D Video Disdrometer

2016 ◽  
Author(s):  
H.-L. Kim ◽  
M.-K. Suk ◽  
H.-S. Park ◽  
G.-W. Lee ◽  
J.-S. Ko
Keyword(s):  
Korean Peninsula ◽  
Rain Rate ◽  
Dual Polarization ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Axis Ratio ◽  
Stage Of Development ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Differential Reflectivity

Abstract. The shapes of raindrops play an important role in inducing polarimetric rainfall algorithms with differential reflectivity (ZDR) and specific differential phase (KDP). The shapes of raindrops have a direct impact on rainfall estimation. However, the characteristics of raindrop size distribution (DSD) are different depending on precipitation type, storm stage of development, and regional and climatological conditions. Therefore, it is necessary to provide assumptions based on raindrop shapes that reflect the rainfall characteristics of the Korean peninsula. In this study, we presented a method to find optimal polarimetric rainfall algorithms on the Korean peninsula using the 2-Dimensional Video Disdrometer (2DVD) and Bislsan S-Band dual-polarization radar. First, a new axis ratio of raindrop relations was developed for the improvement of rainfall estimation. Second, polarimetric rainfall algorithms were derived using different axis ratio relations, and estimated radar-point one-hour rain rate for the differences in polarimetric rainfall algorithms were compared with the hourly rain rate measured by gauge. In addition, radar rainfall estimation was investigated in relation to calibration bias of reflectivity and differential reflectivity. The derived raindrop axis ratio relation from the 2DVD was more oblate than existing relations in the D < 1.5 mm and D > 5.5 mm range. The R(KDP, ZDR) algorithm based on a new axis ratio relation showed the best result on DSD statistics; however, the R(Zh, ZDR) algorithm showed the best performance for radar rainfall estimation, because the rainfall events used in the analysis were mainly weak precipitation and KDP is noisy at lower rain rates ( ≤ 5 mm hr−1). Thus, the R(KDP, ZDR) algorithm is suitable for heavy rainfall and R(Zh, ZDR) algorithm is suited for light rainfall. The calibration bias of reflectivity (ZH) and differential reflectivity (ZDR) were calculated from the comparison of measured with simulated ZH and ZDR from the 2DVD. The calculated ZH and ZDR bias was used to reduce radar bias, and to produce more accurate rainfall estimation.

scholarly journals Dual-polarization radar rainfall estimation in Korea according to raindrop shapes obtained by using a 2-D video disdrometer

2016 ◽  
Vol 9 (8) ◽  
pp. 3863-3878 ◽  
Author(s):  
Hae-Lim Kim ◽  
Mi-Kyung Suk ◽  
Hye-Sook Park ◽  
Gyu-Won Lee ◽  
Jeong-Seok Ko
Keyword(s):  
Korean Peninsula ◽  
Ground Truth ◽  
Rain Gauge ◽  
Dual Polarization ◽  
Radar Rainfall ◽  
Axis Ratio ◽  
Raindrop Size Distribution ◽  
The Mean ◽  
Rain Rates ◽  
Differential Reflectivity

Abstract. Polarimetric measurements are sensitive to the sizes, concentrations, orientations, and shapes of raindrops. Thus, rainfall rates calculated from polarimetric radar are influenced by the raindrop shapes and canting. The mean raindrop shape can be obtained from long-term raindrop size distribution (DSD) observations, and the shapes of raindrops can play an important role in polarimetric rainfall algorithms based on differential reflectivity (ZDR) and specific differential phase (KDP). However, the mean raindrop shape is associated with the variation of the DSD, which can change depending on precipitation types and climatic regimes. Furthermore, these relationships have not been studied extensively on the Korean Peninsula. In this study, we present a method to find optimal polarimetric rainfall algorithms for the Korean Peninsula by using data provided by both a two-dimensional video disdrometer (2DVD) and the Bislsan S-band dual-polarization radar. First, a new axis-ratio relation was developed to improve radar rainfall estimations. Second, polarimetric rainfall algorithms were derived by using different axis-ratio relations. The rain gauge data were used to represent the ground truth situation, and the estimated radar-point hourly mean rain rates obtained from the different polarimetric rainfall algorithms were compared with the hourly rain rates measured by a rain gauge. The daily calibration biases of horizontal reflectivity (ZH) and differential reflectivity (ZDR) were calculated by comparing ZH and ZDR radar measurements with the same parameters simulated by the 2DVD. Overall, the derived new axis ratio was similar to the existing axis ratio except for both small particles (≤ 2 mm) and large particles (≥ 5.5 mm). The shapes of raindrops obtained by the new axis-ratio relation carried out with the 2DVD were more oblate than the shapes obtained by the existing relations. The combined polarimetric rainfall relations using ZDR and KDP were more efficient than the single-parameter rainfall relation for estimated 2DVD rainfall; however, the R(ZH, ZDR) algorithm showed the best performance for radar rainfall estimations, because the rainfall events used in the analysis consisted mainly of weak precipitation and KDP is relatively noisy at lower rain rates (≤ 10 mm h−1). Some of the polarimetric rainfall algorithms can be further improved by new axis-ratio relations.

scholarly journals Statistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimation

2019 ◽  
Vol 23 (10) ◽  
pp. 4153-4170 ◽  
Author(s):  
Yu Ma ◽  
Guangheng Ni ◽  
Chandrasekar V. Chandra ◽  
Fuqiang Tian ◽  
Haonan Chen
Keyword(s):  
Size Distribution ◽  
Urban Area ◽  
Rain Rate ◽  
Statistical Characteristics ◽  
Spatial And Temporal Variability ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Convective Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Abstract. Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation, especially in complex terrain or urban environments which are known for complicated rainfall mechanism and high spatial and temporal variability. In this study, the DSD characteristics of rainy seasons in the Beijing urban area are extensively investigated using 5-year DSD observations from a Parsivel2 disdrometer located at Tsinghua University. The results show that the DSD samples with rain rate < 1 mm h−1 account for more than half of total observations. The mean values of the normalized intercept parameter (log 10Nw) and the mass-weighted mean diameter (Dm) of convective rain are higher than that of stratiform rain, and there is a clear boundary between the two types of rain in terms of the scattergram of log 10Nw versus Dm. The convective rain in Beijing is neither continental nor maritime, owing to the particular location and local topography. As the rainfall intensity increases, the DSD spectra become higher and wider, but they still have peaks around diameter D∼0.5 mm. The midsize drops contribute most towards accumulated rainwater. The Dm and log 10Nw values exhibit a diurnal cycle and an annual cycle. In addition, at the stage characterized by an abrupt rise of urban heat island (UHI) intensity as well as the stage of strong UHI intensity during the day, DSD shows higher Dm values and lower log 10Nw values. The localized radar reflectivity (Z) and rain rate (R) relations (Z=aRb) show substantial differences compared to the commonly used NEXRAD relationships, and the polarimetric radar algorithms R(Kdp), R(Kdp, ZDR), and R(ZH, ZDR) show greater potential for rainfall estimation.

scholarly journals Statistical characteristics of raindrop size distribution during rainy seasons in Beijing urban area and implications for radar rainfall estimation

2019 ◽  
Author(s):  
Yu Ma ◽  
Guangheng Ni ◽  
V. Chandrasekar ◽  
Fuqiang Tian ◽  
Haonan Chen
Keyword(s):  
Size Distribution ◽  
Urban Area ◽  
Rain Rate ◽  
Statistical Characteristics ◽  
Spatial And Temporal Variability ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Convective Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Abstract. Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation, especially in complex terrain or urban environment which is known for its complicated rainfall mechanism and high spatial and temporal variability. In this study, the DSD characteristics of rainy seasons in Beijing urban area are extensively investigated using 5-year DSD observations from a Parsivel2 disdrometer located at Tsinghua University. The results show that the DSD samples with rain rate < 1 mm h−1 account for more than half of total observations. The mean values of log10 Nw and Dm of convective rain are higher than that of stratiform rain, and there is a clear boundary between the two types of rain in terms of the scattergram of log10Nw versus Dm. The convective rain in Beijing is neither continental nor maritime owing to the particular location and local topography. As the rainfall intensity increases, the DSD spectra become higher and wider, but they still have peaks around diameter D ~ 0.5 mm. The midsize drops contribute most towards accumulated rainwater. The Dm and log10Nw values show a diurnal cycle and an annual cycle. In addition, DSD shows higher Dm values and lower log10Nw values during the periods of strong urban heat island (UHI) effect and UHI up stage of a day, and the same in July and August. The localized radar reflectivity (Z) and rain rate (R) relations (Z = aRb) show substantial differences compared to the commonly used NEXRAD relationships. And the polarimetric radar algorithms R(Kdp), R(Kdp, ZDR), and R(ZH, ZDR) show greater potential for rainfall estimation.

scholarly journals Raindrop Size Distribution (DSD) Retrieval for X-Band Dual-Polarization Radar

2014 ◽  
Vol 31 (2) ◽  
pp. 387-403 ◽  
Author(s):  
Eiichi Yoshikawa ◽  
V. Chandrasekar ◽  
Tomoo Ushio
Keyword(s):  
Size Distribution ◽  
Attenuation Correction ◽  
Statistical Fluctuation ◽  
Dual Polarization ◽  
Horizontal Polarization ◽  
Axis Ratio ◽  
Raindrop Size Distribution ◽  
Median Volume ◽  
Raindrop Size ◽  
Differential Reflectivity

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.

A Regression-Free Rainfall Estimation Algorithm for Dual-Polarization Radars

2018 ◽  
Vol 35 (8) ◽  
pp. 1701-1721 ◽  
Author(s):  
Bin Pei ◽  
Firat Y. Testik
Keyword(s):  
Cost Function ◽  
Rain Rate ◽  
Estimation Algorithm ◽  
Cost Functions ◽  
Size Distributions ◽  
Dual Polarization ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Raindrop Size ◽  
Rain Rates

AbstractIn this study a new radar rainfall estimation algorithm—rainfall estimation using simulated raindrop size distributions (RESID)—was developed. This algorithm development was based upon the recent finding that measured and simulated raindrop size distributions (DSDs) with matching triplets of dual-polarization radar observables (i.e., horizontal reflectivity, differential reflectivity, and specific differential phase) produce similar rain rates. The RESID algorithm utilizes a large database of simulated gamma DSDs, theoretical rain rates calculated from the simulated DSDs, the corresponding dual-polarization radar observables, and a set of cost functions. The cost functions were developed using both the measured and simulated dual-polarization radar observables. For a given triplet of measured radar observables, RESID chooses a suitable cost function from the set and then identifies nine of the simulated DSDs from the database that minimize the value of the chosen cost function. The rain rate associated with the given radar observable triplet is estimated by averaging the calculated theoretical rain rates for the identified simulated DSDs. This algorithm is designed to reduce the effects of radar measurement noise on rain-rate retrievals and is not subject to the regression uncertainty introduced in the conventional development of the rain-rate estimators. The rainfall estimation capability of our new algorithm was demonstrated by comparing its performance with two benchmark algorithms through the use of rain gauge measurements from the Midlatitude Continental Convective Clouds Experiment (MC3E) and the Olympic Mountains Experiment (OLYMPEx). This comparison showed favorable performance of the new algorithm for the rainfall events observed during the field campaigns.

scholarly journals Evaluation of Gamma Raindrop Size Distribution Assumption through Comparison of Rain Rates of Measured and Radar-Equivalent Gamma DSD

2014 ◽  
Vol 53 (6) ◽  
pp. 1618-1635 ◽  
Author(s):  
Elisa Adirosi ◽  
Eugenio Gorgucci ◽  
Luca Baldini ◽  
Ali Tokay
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Hydrological Cycle ◽  
Drop Size Distribution ◽  
Dual Polarization ◽  
Raindrop Size Distribution ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Rain Rates

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.

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.

A New Dual-Polarization Radar Rainfall Algorithm: Application in Colorado Precipitation Events

2011 ◽  
Vol 28 (3) ◽  
pp. 352-364 ◽  
Author(s):  
R. Cifelli ◽  
V. Chandrasekar ◽  
S. Lim ◽  
P. C. Kennedy ◽  
Y. Wang ◽  
...  
Keyword(s):  
Estimation Algorithm ◽  
State University ◽  
Dual Polarization ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Colorado State University ◽  
Differential Phase ◽  
Precipitation Estimation ◽  
The One ◽  
Differential Reflectivity

Abstract The efficacy of dual-polarization radar for quantitative precipitation estimation (QPE) has been demonstrated in a number of previous studies. Specifically, rainfall retrievals using combinations of reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) have advantages over traditional Z–R methods because more information about the drop size distribution (DSD) and hydrometeor type are available. In addition, dual-polarization-based rain-rate estimators can better account for the presence of ice in the sampling volume. An important issue in dual-polarization rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), an optimization algorithm has been developed and used for a number of years to estimate rainfall based on thresholds of Zh, Zdr, and Kdp. Although the algorithm has demonstrated robust performance in both tropical and midlatitude environments, results have shown that the retrieval is sensitive to the selection of the fixed thresholds. In this study, a new rainfall algorithm is developed using hydrometeor identification (HID) to guide the choice of the particular rainfall estimation algorithm. A separate HID algorithm has been developed primarily to guide the rainfall application with the hydrometeor classes, namely, all rain, mixed precipitation, and all ice. Both the data collected from the S-band Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar and a network of rain gauges are used to evaluate the performance of the new algorithm in mixed rain and hail in Colorado. The evaluation is also performed using an algorithm similar to the one developed for the Joint Polarization Experiment (JPOLE). Results show that the new CSU HID-based algorithm provides good performance for the Colorado case studies presented here.

scholarly journals Influence of the Subgrid Variability of the Raindrop Size Distribution on Radar Rainfall Estimators

2012 ◽  
Vol 51 (4) ◽  
pp. 780-785 ◽  
Author(s):  
Joël Jaffrain ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Power Laws ◽  
Radar Data ◽  
Sampling Uncertainty ◽  
Radar Rainfall ◽  
Differential Phase Shift ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Pixel Scale

AbstractThis work aims at quantifying the variability of the parameters of the power laws used for rain-rate estimation from radar data, on the basis of raindrop size distribution measurements over a typical weather radar pixel. Power laws between the rain rate and the reflectivity or the specific differential phase shift are fitted to the measured values, and the variability of the parameters is analyzed. At the point scale, the variability within this radar pixel cannot be solely explained by the sampling uncertainty associated with disdrometer measurements. When parameters derived from point measurements are applied at the radar pixel scale, the resulting error in the rain amount varies between −2% and +15%.

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