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 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 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 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 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 Decadal Variation in Raindrop Size Distributions in Busan, Korea

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Cheol-Hwan You ◽  
Dong-In Lee
Keyword(s):  
Drop Size ◽  
Annual Rainfall ◽  
Size Distributions ◽  
Decadal Variation ◽  
Gamma Model ◽  
Radar Rainfall ◽  
Precipitation Occurrence ◽  
Raindrop Size ◽  
Using Data ◽  
Rain Rates

This paper investigated the variability of raindrop size distributions (DSDs) in Busan, Korea, using data from two different disdrometers: a precipitation occurrence sensor system (POSS) and a particle size velocity (Parsivel) optical disdrometer. DSDs were simulated using a gamma model to assess the intercomparability of these two techniques. Annual rainfall amount was higher in 2012 than in 2002, as were the annually averagedDm(which was 0.1 mm greater in 2012) and the frequency of convective rain. Severe rainfall (greater than 20 mm h−1) occurred more frequently and with a largerDmin 2012. The values ofDmfrom July, August, and December, 2012, were much greater than from other months when compared with 2002. Larger raindrops contributed to the higher rain rates that were observed in the morning during 2012, whereas relatively smaller raindrops dominated in the afternoon. These results suggest that the increase in raindrop size that has been observed in Busan may continue in the future; however, more research will be required if we are to fully understand this phenomenon. Rainfall variables are highly dependent on drop size and so should be recalculated using the newest DSDs to allow more accurate polarimetric radar rainfall estimation.

scholarly journals An empirical method to improve rainfall estimation of dual polarization radar using ground measurements

2016 ◽  
Author(s):  
Jungsoo Yoon ◽  
Mi-Kyung Suk ◽  
Kyung-Yeub Nam ◽  
Jeong-Seok Ko ◽  
Hae-Lim Kim ◽  
...  
Keyword(s):  
Empirical Method ◽  
Dual Polarization ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Rainfall Events ◽  
High Rainfall ◽  
Estimation Algorithms ◽  
Hourly Rainfall ◽  
Constant Altitude ◽  
Position Indicator

Abstract. This study presents an easy and convenient empirical method to optimize polarimetric variables and produce more accurate dual polarization radar rainfall estimation. Weather Radar Center (WRC) in Korea Meteorological Administration (KMA) suggested relations between polarimetric variables (Z–ZDR and Z–KDP) based on a 2-D Video Distrometer (2DVD) measurements in 2014. Observed polarimetric variables from CAPPI (Constant Altitude Plan Position Indicator) images composed at 1 km of height were adjusted using the WRC's relations. Then dual polarization radar rainfalls were estimated by six different radar rainfall estimation algorithms, which are using either Z, Z and ZDR, or Z, ZDR and KDP. Accuracy of radar rainfall estimations derived by the six algorithms using the adjusted variables was assessed through comparison with raingauge observations. As a result, the accuracy of the radar rainfall estimation using adjusted polarimetric variables has improved from 50 % to 70 % approximately. Three high rainfall events with more than 40 mm of maximum hourly rainfall were shown the best accuracy on the rainfall estimation derived by using Z, ZDR and KDP. Meanwhile stratiform event was gained better radar rainfalls estimated by algorithms using Z and ZDR.

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