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

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.

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

10.5194/amt-2016-14 ◽

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.

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Preliminary evaluation of polarimetric parameters from a new dual-polarization C-band weather radar in an alpine region

Advances in Geosciences ◽

10.5194/adgeo-25-111-2010 ◽

2010 ◽

Vol 25 ◽

pp. 111-117 ◽

Cited By ~ 1

Author(s):

H. Paulitsch ◽

F. Teschl ◽

W. L. Randeu

Keyword(s):

Attenuation Correction ◽

Rain Rate ◽

Weather Radar ◽

Heavy Rain ◽

Rain Gauge ◽

Preliminary Evaluation ◽

Dual Polarization ◽

Horizontal Polarization ◽

Rain Rates ◽

Differential Reflectivity

Abstract. The first operational weather radar with dual polarization capabilities was recently installed in Austria. The use of polarimetric radar variables rises several expectations: an increased accuracy of the rain rate estimation compared to standard Z-R relationships, a reliable use of attenuation correction methods, and finally hydrometeor classification. In this study the polarimetric variables of precipitation events are investigated and the operational quality of the parameters is discussed. For the new weather radar also several polarimetric rain rate estimators, which are based on the horizontal polarization radar reflectivity, ZH, the differential reflectivity, ZDR, and the specific differential propagation phase shift, KDP, have been tested. The rain rate estimators are further combined with an attenuation correction scheme. A comparison between radar and rain gauge indicates that ZDR based rain rate algorithms show an improvement over the traditional Z-R estimate. KDP based estimates do not provide reliable results, mainly due to the fact, that the observed KDP parameters are quite noisy. Furthermore the observed rain rates are moderate, where KDP is less significant than in heavy rain.

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Quantification of Precipitation Using Polarimetric Radar Measurements during Several Typhoon Events in Southern China

Remote Sensing ◽

10.3390/rs12122058 ◽

2020 ◽

Vol 12 (12) ◽

pp. 2058

Author(s):

Qiulei Xia ◽

Wenjuan Zhang ◽

Haonan Chen ◽

Wen-Chau Lee ◽

Lei Han ◽

...

Keyword(s):

Southern China ◽

Rain Gauge ◽

Polarimetric Radar ◽

Dual Polarization ◽

Radar Rainfall ◽

Flood Warning ◽

Microphysical Properties ◽

Raindrop Size Distribution ◽

Precipitation Estimation ◽

Radar Measurements

Accurate quantitative precipitation estimation (QPE) during typhoon events is critical for flood warning and emergency management. Dual-polarization radar has proven to have better performance for QPE, compared to traditional single-polarization radar. However, polarimetric radar applications have not been extensively investigated in China, especially during extreme events such as typhoons, since the operational dual-polarization system upgrade only happened recently. This paper extends a polarimetric radar rainfall system for local applications during typhoons in southern China and conducts comprehensive studies about QPE and precipitation microphysics. Observations from S-band dual-polarization radar in Guangdong Province during three typhoon events in 2017 are examined to demonstrate the enhanced radar rainfall performance. The microphysical properties of hydrometeors during typhoon events are analyzed through raindrop size distribution (DSD) data and polarimetric radar measurements. The stratiform precipitation in typhoons presents lower mean raindrop diameter and lower raindrop concentration than that of the convection precipitation. The rainfall estimates from the adapted radar rainfall algorithm agree well with rainfall measurements from rain gauges. Using the rain gauge data as references, the maximum normalized mean bias ( N M B ) of the adapted radar rainfall algorithm is 20.27%; the normalized standard error ( N S E ) is less than 40%; and the Pearson’s correlation coefficient ( C C ) is higher than 0.92. For the three typhoon events combined, the N S E and N M B are 36.66% and -15.78%, respectively. Compared with several conventional radar rainfall algorithms, the adapted algorithm based on local rainfall microphysics has the best performance in southern China.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-12-00248.1 ◽

2014 ◽

Vol 31 (2) ◽

pp. 387-403 ◽

Cited By ~ 13

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.

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Axis Ratios and Flutter Angles of Cloud Ice Particles: Retrievals from Radar Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-12-00212.1 ◽

2013 ◽

Vol 30 (8) ◽

pp. 1691-1703 ◽

Cited By ~ 18

Author(s):

Valery Melnikov ◽

Jerry M. Straka

Keyword(s):

Standard Deviation ◽

Radar Data ◽

Dual Polarization ◽

Axis Ratio ◽

Retrieval Method ◽

Ice Cloud ◽

Novel Method ◽

The Mean ◽

Cloud Ice ◽

Differential Reflectivity

Abstract A novel method of retrieving the mean axis ratio (width/length) and standard deviation of orientation angles (σθ, which is called herein the intensity of fluttering) of ice cloud particles from polarimetric radar data is described. The method is based on measurements of differential reflectivity ZDR and the copolar correlation coefficient in cloud areas with ZDR > 4 dB. In three analyzed cases, the values of the retrieved axis ratio were in an interval from 0.15 to 0.4 and σθ found in an interval from 2° to 20°. The latter values indicate that the particles experienced light to moderate fluttering. Ambiguities in the retrievals because of uncertainties in the bulk ice density of the particles and possible presence of columnar crystals are considered. The retrieval method is applicable for centimeter-wavelength radars; the analyzed data were collected with the dual-polarization S-band Weather Surveillance Radar-1988 Doppler (WSR-88D).

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

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-13-0150.1 ◽

2014 ◽

Vol 53 (6) ◽

pp. 1618-1635 ◽

Cited By ~ 24

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.

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Comparison of Single- and Dual-Polarization–Based Rainfall Estimates Using NEXRAD Data for the NASA Iowa Flood Studies Project

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0169.1 ◽

2015 ◽

Vol 16 (4) ◽

pp. 1658-1675 ◽

Cited By ~ 22

Author(s):

Bong-Chul Seo ◽

Brenda Dolan ◽

Witold F. Krajewski ◽

Steven A. Rutledge ◽

Walter Petersen

Keyword(s):

Rain Rate ◽

Heavy Rain ◽

Rain Gauge ◽

Superior Performance ◽

Dual Polarization ◽

Radar Rainfall ◽

Colorado State University ◽

Precipitation Estimation ◽

Improved Performance ◽

Rainfall Estimates

Abstract This study compares and evaluates single-polarization (SP)- and dual-polarization (DP)-based radar-rainfall (RR) estimates using NEXRAD data acquired during Iowa Flood Studies (IFloodS), a NASA GPM ground validation field campaign carried out in May–June 2013. The objective of this study is to understand the potential benefit of the DP quantitative precipitation estimation, which selects different rain-rate estimators according to radar-identified precipitation types, and to evaluate RR estimates generated by the recent research SP and DP algorithms. The Iowa Flood Center SP (IFC-SP) and Colorado State University DP (CSU-DP) products are analyzed and assessed using two high-density, high-quality rain gauge networks as ground reference. The CSU-DP algorithm shows superior performance to the IFC-SP algorithm, especially for heavy convective rains. We verify that dynamic changes in the proportion of heavy rain during the convective period are associated with the improved performance of CSU-DP rainfall estimates. For a lighter rain case, the IFC-SP and CSU-DP products are not significantly different in statistical metrics and visual agreement with the rain gauge data. This is because both algorithms use the identical NEXRAD reflectivity–rain rate (Z–R) relation that might lead to substantial underestimation for the presented case.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-15-0060.1 ◽

2016 ◽

Vol 33 (2) ◽

pp. 377-389 ◽

Cited By ~ 5

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.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2010jtecha1488.1 ◽

2011 ◽

Vol 28 (3) ◽

pp. 352-364 ◽

Cited By ~ 110

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.

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An Early Performance Evaluation of the NEXRAD Dual-Polarization Radar Rainfall Estimates for Urban Flood Applications

Weather and Forecasting ◽

10.1175/waf-d-13-00046.1 ◽

2013 ◽

Vol 28 (6) ◽

pp. 1478-1497 ◽

Cited By ~ 20

Author(s):

Luciana K. Cunha ◽

James A. Smith ◽

Mary Lynn Baeck ◽

Witold F. Krajewski

Keyword(s):

Kansas City ◽

Spatial Scales ◽

Rain Gauge ◽

Dual Polarization ◽

Radar Rainfall ◽

Urban Flood ◽

Temporal And Spatial ◽

Single Polarization ◽

Early Performance ◽

Rainfall Estimates

Abstract Dual-polarization radars are expected to provide better rainfall estimates than single-polarization radars because of their ability to characterize hydrometeor type. The goal of this study is to evaluate single- and dual-polarization radar rainfall fields based on two overlapping radars (Kansas City, Missouri, and Topeka, Kansas) and a dense rain gauge network in Kansas City. The study area is located at different distances from the two radars (23–72 km for Kansas City and 104–157 km for Topeka), allowing for the investigation of radar range effects. The temporal and spatial scales of radar rainfall uncertainty based on three significant rainfall events are also examined. It is concluded that the improvements in rainfall estimation achieved by polarimetric radars are not consistent for all events or radars. The nature of the improvement depends fundamentally on range-dependent sampling of the vertical structure of the storms and hydrometeor types. While polarimetric algorithms reduce range effects, they are not able to completely resolve issues associated with range-dependent sampling. Radar rainfall error is demonstrated to decrease as temporal and spatial scales increase. However, errors in the estimation of total storm accumulations based on polarimetric radars remain significant (up to 25%) for scales of approximately 650 km2.

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