A method for estimating rain rate and drop size distribution from polarimetric radar measurements

2001 ◽  
Vol 39 (4) ◽  
pp. 830-841 ◽  
Author(s):  
G. Zhang ◽  
J. Vivekanandan ◽  
E. Brandes
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Drop Size Distribution ◽  
Polarimetric Radar ◽  
Radar Measurements

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.

scholarly journals Microphysical Retrievals from Dual-Polarization Radar Measurements at X Band

2008 ◽  
Vol 25 (5) ◽  
pp. 729-741 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Luca Baldini
Keyword(s):  
Size Distribution ◽  
Attenuation Correction ◽  
Drop Size ◽  
Radar Data ◽  
Drop Size Distribution ◽  
Polarimetric Radar ◽  
Axis Ratio ◽  
X Band ◽  
Radar Measurements ◽  
Self Consistency

Abstract The recent advances in attenuation correction methodology are based on the use of a constraint represented by the total amount of the attenuation encountered along the path shared over each range bin in the path. This technique is improved by using the inner self-consistency of radar measurements. The full self-consistency methodology provides an optimization procedure for obtaining the best estimate of specific and cumulative attenuation and specific and cumulative differential attenuation. The main goal of the study is to examine drop size distribution (DSD) retrieval from X-band radar measurements after attenuation correction. A new technique for estimating the slope of a linear axis ratio model from polarimetric radar measurements at attenuated frequencies is envisioned. A new set of improved algorithms immune to variability in the raindrop shape–size relation are presented for the estimation of the governing parameters characterizing a gamma raindrop size distribution. Simulations based on the use of profiles of gamma drop size distribution parameters obtained from S-band observations are used for quantitative analysis. Radar data collected by the NOAA/Earth System Research Laboratory (ESRL) X-band polarimetric radar are used to provide examples of the DSD parameter retrievals using attenuation-corrected radar measurements. Retrievals agree fairly well with disdrometer data. The radar data are also used to observe the prevailing shape of raindrops directly from the radar measurements. A significant result is that oblateness of drops is bounded between the two shape models of Pruppacher and Beard, and Beard and Chuang, the former representing the upper boundary and the latter the lower boundary.

Estimation of Spatial Correlation of Drop Size Distribution Parameters and Rain Rate Using NASA’s S-Band Polarimetric Radar and 2D Video Disdrometer Network: Two Case Studies from MC3E

2015 ◽  
Vol 16 (3) ◽  
pp. 1207-1221 ◽  
Author(s):  
V. N. Bringi ◽  
L. Tolstoy ◽  
M. Thurai ◽  
W. A. Petersen
Keyword(s):  
Size Distribution ◽  
Spatial Correlation ◽  
Drop Size ◽  
Rain Rate ◽  
Pearson Correlation ◽  
Drop Size Distribution ◽  
Distinct Advantage ◽  
Rain Event ◽  
Polarimetric Radar ◽  
Spatial Correlation Function

Abstract Polarimetric radar data obtained at high spatial and temporal resolutions offer a distinct advantage in estimating the spatial correlation function of drop size distribution (DSD) parameters and rain rate compared with a fixed gauge–disdrometer network. On two days during the 2011 Midlatitude Continental Convective Clouds Experiment (MC3E) campaign in Oklahoma, NASA’s S-band polarimetric radar (NPOL) performed repeated PPI scans every 40 s over six 2D video disdrometer (2DVD) sites, located 20–30 km from the radar. The two cases were 1) a rapidly evolving multicell rain event (with large drops) and 2) a long-duration stratiform rain event. From the time series at each polar pixel, the Pearson correlation coefficient is computed as a function of distance along each radial in the PPI scan. Azimuthal dependence is found, especially for the highly convective event. A pseudo-1D spatial correlation is computed that is fitted to a modified-exponential function with two parameters (decorrelation distance R0 and shape F). The first event showed significantly higher spatial variability in rain rate (shorter decorrelation distance R0 = 3.4 km) compared with the second event with R0 = 10.2 km. Further, for the second event, the spatial correlation of the DSD parameters and rain rate from radar showed good agreement with 2DVD-based spatial correlations over distances ranging from 1.5 to 7 km. The NPOL also performed repeated RHI scans every 40 s along one azimuth centered over the 2DVD network. Vertical correlations of the DSD parameters as well as the rainwater content were determined below the melting level, with the first event showing more variability compared with the second event.

scholarly journals Estimating the Accuracy of Polarimetric Radar–Based Retrievals of Drop-Size Distribution Parameters and Rain Rate: An Application of Error Variance Separation Using Radar-Derived Spatial Correlations

2012 ◽  
Vol 13 (3) ◽  
pp. 1066-1079 ◽  
Author(s):  
M. Thurai ◽  
V. N. Bringi ◽  
L. D. Carey ◽  
P. Gatlin ◽  
E. Schultz ◽  
...  
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Sampling Error ◽  
Error Variance ◽  
Radar Data ◽  
Drop Size Distribution ◽  
Precipitation Event ◽  
Retrieval Algorithm ◽  
Polarimetric Radar

Abstract The accuracy of retrieving the two drop size distribution (DSD) parameters, median volume diameter (D0), and normalized intercept parameter (NW), as well as rain rate (R), from polarimetric C-band radar data obtained during a cool-season, long-duration precipitation event in Huntsville, Alabama, is examined. The radar was operated in a special “near-dwelling” mode over two video disdrometers (2DVD) located 15 km away. The polarimetric radar–based retrieval algorithms for the DSD parameters and rain rate were obtained from simulations using the 2DVD measurements of the DSD. A unique feature of this paper is the radar-based estimation of the spatial correlation functions of the two DSD parameters and rain rate that are used to estimate the “point-to-area” variance. A detailed error variance separation is performed, including the aforementioned point-to-area variance, along with variance components due to the retrieval algorithm error, radar measurement error, and disdrometer sampling error. The spatial decorrelation distance was found to be smallest for the R (4.5 km) and largest for D0 (8.24 km). For log10(NW), it was 7.22 km. The proportion of the variance of the difference between radar-based estimates and 2DVD measurements that could be explained by the aforementioned errors was 100%, 57%, and 73% for D0, log10(NW), and R, respectively. The overall accuracy of the radar-based retrievals for the particular precipitation event quantified in terms of the fractional standard deviation were estimated to be 6.8%, 6%, and 21% for D0, log10(NW), and R, respectively. The normalized bias was <1%. These correspond to time resolution of ~3 min and spatial resolution of ~1.5 km.

scholarly journals One, No One, and One Hundred Thousand: The Paradigm of the Z–R Relationship

2020 ◽  
Vol 21 (6) ◽  
pp. 1161-1169
Author(s):  
Massimiliano Ignaccolo ◽  
Carlo De Michele
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Scaling Law ◽  
Drop Size Distribution ◽  
Physical Relationship ◽  
Simple Realization ◽  
Linear Fit ◽  
State Of Affairs

AbstractThe Z–R relationship is a scaling-law formulation, Z = ARb, connecting the radar reflectivity Z to the rain rate R. However, more than 100 Z–R relationships, with different values of the parameters, have been reported in literature. This abundance of relationships is in itself a strong indication that no one “physical” relationship exists, a state of affairs that we find similar to that of the protagonist of Luigi Pirandello’s novel One, No One and One Hundred Thousand. Nevertheless the “elevation” of a simple linear fit in the (logR, logZ) space to the role of “scaling law” is such a widespread tenet in literature that it eclipses the simple realization that the abundance of different intercepts and slopes reflects the inhomogeneous nature of rain, and, in ultimate analysis, the statistical variability existing between the number of drops and drop size distribution. Here, we “eliminate” the contribution of the number of drops by rescaling both reflectivity and rainfall rate to per unit drop variables, (Z, R) → (z, r), so that the remaining variability is due only to the variability of the drop size distribution. We use a worldwide database of disdrometer data to show that for the rescaled variables (z, r) only “one,” albeit approximate, scaling law exists.

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