Improving Parameterization of Rain Microphysics with Disdrometer and Radar Observations

2006 ◽  
Vol 63 (4) ◽  
pp. 1273-1290 ◽  
Author(s):  
Guifu Zhang ◽  
Juanzhen Sun ◽  
Edward A. Brandes
Keyword(s):  
Doppler Radar ◽  
Numerical Models ◽  
Distribution Model ◽  
Model Parameterization ◽  
Raindrop Size Distribution ◽  
Single Moment ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Analysis System ◽  
Differential Reflectivity

Abstract Disdrometer observations indicate that the raindrop size distribution (DSD) can be represented by a constrained-gamma (CG) distribution model. The model is used to retrieve DSDs from polarization radar measurements of reflectivity and differential reflectivity and to characterize rain microphysics and physical processes such as evaporation, accretion, and precipitation. The CG model parameterization is simplified to a single parameter for application in single-moment numerical models. This simplified parameterization is applied in the Variational Doppler Radar Analysis System (VDRAS) using Kessler-type parameterizations for model initialization and forecasting. Results are compared to those for the Marshall–Palmer (MP) DSD model. It is found that the simplified CG model parameterization better preserves the stratiform rain and produces better forecasts than the MP model parameterization.

scholarly journals A Variational Approach for Retrieving Raindrop Size Distribution from Polarimetric Radar Measurements in the Presence of Attenuation

2013 ◽  
Vol 52 (1) ◽  
pp. 169-185 ◽  
Author(s):  
Qing Cao ◽  
Guifu Zhang ◽  
Ming Xue
Keyword(s):  
Variational Approach ◽  
Simulated Data ◽  
Real Data ◽  
Radar Data ◽  
Polarimetric Radar ◽  
University Of Oklahoma ◽  
Raindrop Size Distribution ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Differential Reflectivity

AbstractThis study presents a two-dimensional variational approach to retrieving raindrop size distributions (DSDs) from polarimetric radar data in the presence of attenuation. A two-parameter DSD model, the constrained-gamma model, is used to represent rain DSDs. Three polarimetric radar measurements—reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP—are optimally used to correct for the attenuation and retrieve DSDs by taking into account measurement error effects. Retrieval results with simulated data demonstrate that the proposed algorithm performs well. Applications to real data collected by the X-band Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radars and the C-band University of Oklahoma–Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) also demonstrate the efficacy of this approach.

scholarly journals Uncertainty in Retrieving Raindrop Size Distribution from Polarimetric Radar Measurements

2019 ◽  
Vol 36 (4) ◽  
pp. 585-605 ◽  
Author(s):  
Hao Huang ◽  
Guifu Zhang ◽  
Kun Zhao ◽  
Su Liu ◽  
Long Wen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Measurement Errors ◽  
Distribution Model ◽  
Fundamental Parameter ◽  
Polarimetric Radar ◽  
Quantitative Precipitation Estimation ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Radar Measurements ◽  
Raindrop Size

AbstractDrop size distribution (DSD) is a fundamental parameter in rain microphysics. Retrieving DSDs from polarimetric radar measurements extends the capabilities of rain microphysics research and quantitative precipitation estimation. In this study, issues in rain DSD retrieval were studied with simulated and measured data. It was found that a three-parameter gamma distribution model was not suitable for directly retrieving DSD from polarimetric radar measurements. A statistical constraint, such as the shape–slope relation used in the constrained-gamma (C-G) distribution model, helped to reduce the uncertainties and errors in the retrieval. The inclusion of specific differential phase (KDP) measurements resulted in more accurate DSD retrieval and rain physical parameter estimation if the measurement errors were properly characterized in the error minimization analysis (EMA), which was verified using two real precipitation events. The study demonstrated the potential of using full polarimetric radar measurements to improve rain DSD retrieval.

scholarly journals Raindrop Size Distribution and Rain Characteristics during the 2013 Great Colorado Flood

2015 ◽  
Vol 17 (1) ◽  
pp. 53-72 ◽  
Author(s):  
Katja Friedrich ◽  
Evan A. Kalina ◽  
Joshua Aikins ◽  
Matthias Steiner ◽  
David Gochis ◽  
...  
Keyword(s):  
Drop Size ◽  
Doppler Radar ◽  
Liquid Water Content ◽  
Size Distributions ◽  
Intense Rainfall ◽  
Wind Fields ◽  
Raindrop Size Distribution ◽  
Median Volume ◽  
Drop Size Distributions ◽  
Analysis System

Abstract Drop size distributions observed by four Particle Size Velocity (PARSIVEL) disdrometers during the 2013 Great Colorado Flood are used to diagnose rain characteristics during intensive rainfall episodes. The analysis focuses on 30 h of intense rainfall in the vicinity of Boulder, Colorado, from 2200 UTC 11 September to 0400 UTC 13 September 2013. Rainfall rates R, median volume diameters D0, reflectivity Z, drop size distributions (DSDs), and gamma DSD parameters were derived and compared between the foothills and adjacent plains locations. Rainfall throughout the entire event was characterized by a large number of small- to medium-sized raindrops (diameters smaller than 1.5 mm) resulting in small values of Z (<40 dBZ), differential reflectivity Zdr (<1.3 dB), specific differential phase Kdp (<1° km−1), and D0 (<1 mm). In addition, high liquid water content was present throughout the entire event. Raindrops observed in the plains were generally larger than those in the foothills. DSDs observed in the foothills were characterized by a large concentration of small-sized drops (d < 1 mm). Heavy rainfall rates with slightly larger drops were observed during the first intense rainfall episode (0000–0800 UTC 12 September) and were associated with areas of enhanced low-level convergence and vertical velocity according to the wind fields derived from the Variational Doppler Radar Analysis System. The disdrometer-derived Z–R relationships reflect how unusual the DSDs were during the 2013 Great Colorado Flood. As a result, Z–R relations commonly used by the operational NEXRAD strongly underestimated rainfall rates by up to 43%.

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.

Comment on raindrop size distribution model

1994 ◽  
Vol 42 (9) ◽  
pp. 1360 ◽  
Author(s):  
L.W. Li ◽  
T.S. Yeo ◽  
P.S. Kooi ◽  
M.S. Leong
Keyword(s):  
Size Distribution ◽  
Distribution Model ◽  
Raindrop Size Distribution ◽  
Raindrop Size

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 Radar and Surface Measurement of Rainfall during CaPE: 26 July 1991 Case Study

1995 ◽  
Vol 34 (7) ◽  
pp. 1570-1577 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Gianfranco Scarchilli
Keyword(s):  
Rain Gauge ◽  
Distribution Functions ◽  
Surface Measurement ◽  
Rainfall Estimation ◽  
Statistical Framework ◽  
Raindrop Size Distribution ◽  
Surface Measurements ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Multiparameter Radar

Abstract Conventional usage of multiparameter radar measurements for rainfall estimation has been associated with tracking the variability of the raindrop size distribution. The use of multiparameter radar measurements in a statistical framework to estimate rainfall is presented in this paper. The techniques developed in this paper are applied to the radar and rain gauge measurement of rainfall observed on 26 July 1991, during the Convection and Precipitation Electrification program. Conventional pointwise estimates of rainfall are also compared. The probability matching procedure, when applied to the radar and surface measurements shows that multiparameter radar algorithms can match the probability distribution functions better than the reflectivity based algorithms, thereby indicating the potential of multiparameter radar measurements for statistical approach to rainfall estimation.

Sign in / Sign up

Export Citation Format

Share Document