scholarly journals Errors in Estimating Raindrop Size Distribution Parameters Employing Disdrometer and Simulated Raindrop Spectra

2009 ◽  
Vol 48 (2) ◽  
pp. 406-425 ◽  
Author(s):  
Qing Cao ◽  
Guifu Zhang
Keyword(s):  
Size Distribution ◽  
Measurement Errors ◽  
Model Errors ◽  
Moment Estimators ◽  
Raindrop Size Distribution ◽  
Distribution Parameters ◽  
Raindrop Size ◽  
Mean Function ◽  
Differential Reflectivity ◽  
Multiparameter Radar

Abstract There have been debates and differences of opinion over the validity of using drop size distribution (DSD) models to characterize precipitation microphysics and to retrieve DSD parameters from multiparameter radar measurements. In this paper, simulated and observed rain DSDs are used to evaluate moment estimators. Seven estimators for gamma DSD parameters are evaluated in terms of the biases and fractional errors of five integral parameters: radar reflectivity (ZH), differential reflectivity (ZDR), rainfall rate (R), mean volume diameter (Dm), and total number concentration (NT). It is shown that middle-moment estimators such as M234 (using the second-third-fourth moments) produce smaller errors than lower- and higher-moment estimators if the DSD follows the gamma distribution. However, if there are model errors, the performance of M234 degrades. Even though the DSD parameters can be biased in moment estimators, integral parameters are usually not. Maximum likelihood (ML) and L-moment (LM) estimators perform similarly to low-moment estimators such as M012. They are sensitive to both model error and the measurement errors of the low ends of DSDs. The overall differences among M234, M246, and M346 are not substantial for the five evaluated parameters. This study also shows that the discrepancy between the radar and disdrometer observations cannot be reduced by using these estimators. In addition, the previously found constrained-gamma model is shown not to be exclusively determined by error effects. Rather, it is equivalent to the mean function of normalized DSDs derived through Testud’s approach, and linked to precipitation microphysics.

Dual-Polarization Radar Retrievals of Coastal Pacific Northwest Raindrop Size Distribution Parameters Using Random Forest Regression

2020 ◽  
Vol 37 (2) ◽  
pp. 229-242 ◽  
Author(s):  
Robert Conrick ◽  
Joseph P. Zagrodnik ◽  
Clifford F. Mass
Keyword(s):  
Random Forest ◽  
Size Distribution ◽  
Pacific Northwest ◽  
Liquid Water Content ◽  
Random Forest Regression ◽  
Raindrop Size Distribution ◽  
Median Volume ◽  
Distribution Parameters ◽  
Rate Improvement ◽  
Raindrop Size

AbstractRadar retrievals of drop size distribution (DSD) parameters are developed and evaluated over the mountainous Olympic Peninsula of Washington State. The observations used to develop retrievals were collected during the 2015/16 Olympic Mountain Experiment (OLYMPEX) and included the NASA S-band dual-polarimetric (NPOL) radar and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometers over the windward slopes of the barrier. Nonlinear and random forest regressions are applied to the PARSIVEL2 data to develop retrievals for median volume diameter, liquid water content, and rain rate. Improvement in DSD retrieval accuracy, defined by the mean error of the retrieval relative to PARSIVEL2 observations, was achieved when using the random forest model when compared with nonlinear regression. Evaluation of disdrometer observations and the retrievals from NPOL indicate that the radar retrievals can accurately reproduce observed DSDs in this region, including the common wintertime regime of small but numerous raindrops that is important there. NPOL retrievals during the OLYMPEX period are further evaluated using two-dimensional video disdrometers (2DVD) and vertically pointing Micro Rain Radars. Results indicate that radar retrievals using random forests may be skillful in capturing DSD characteristics in the lowest portions of the atmosphere.

Estimation of raindrop size distribution parameters by maximum likelihood and L-moment methods: Effect of discretization

2012 ◽  
Vol 112 ◽  
pp. 1-11 ◽  
Author(s):  
Marzuki ◽  
Walter L. Randeu ◽  
Toshiaki Kozu ◽  
Toyoshi Shimomai ◽  
Michael Schönhuber ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Size Distribution ◽  
Moment Methods ◽  
Raindrop Size Distribution ◽  
Distribution Parameters ◽  
Raindrop Size

scholarly journals Characteristics of Raindrop Size Distribution in Typhoon Nida (2016) before and after Landfall in Southern China from 2D Video Disdrometer Data

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Lu Feng ◽  
Xiantong Liu ◽  
Hui Xiao ◽  
Liusi Xiao ◽  
Feng Xia ◽  
...  
Keyword(s):  
Size Distribution ◽  
Southern China ◽  
Spectral Width ◽  
Average Mass ◽  
Raindrop Size Distribution ◽  
The Pacific ◽  
Before And After ◽  
Precipitation Estimation ◽  
Distribution Parameters ◽  
Raindrop Size

During the passage of Typhoon Nida, the raindrop size distribution parameters, the raindrop spectra, the shape and slope (μ–Λ) relationship, the radar reflectivity factor, and rain rate (Z–R) relationship were investigated based on a two-dimensional (2D) video disdrometer in Guangdong, China, from August 1 to 2, 2016. Due to the underlying surface difference between the ocean and land, this process was divided into two distinct periods (before landfall and after landfall). The characteristics of raindrop size distribution between the period before landfall and the period after landfall were quite distinct. The period after landfall exhibited higher concentrations of each size bin (particularly small drops) and wider raindrop spectral width than the period before landfall. Compared with the period before landfall, the period after landfall had a higher average mass-weighted mean diameter Dm that was smaller than those of other TCs from the same ocean (the Pacific). The μ–Λ relationship and Z–R relationship in this study were also compared with other TCs from the same ocean (the Pacific). This investigation of the microphysical characteristics of Typhoon Nida before landfall and after landfall may improve radar quantitative precipitation estimation (QPE) products and microphysical schemes by providing useful information.

Vertical Variability of the Raindrop Size Distribution in Typhoons Observed at the Shenzhen 356-m Meteorological Tower

2020 ◽  
Vol 77 (12) ◽  
pp. 4171-4187
Author(s):  
Baojun Chen ◽  
Jun Yang ◽  
Ruiquan Gao ◽  
Keping Zhu ◽  
Chungen Zou ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Size Distribution ◽  
Weighted Mean ◽  
Meteorological Tower ◽  
Raindrop Size Distribution ◽  
Mean Diameter ◽  
Distribution Parameters ◽  
Low Altitude ◽  
Raindrop Size ◽  
Different Altitudes

AbstractRaindrop size distribution (DSD) characteristics at various altitudes in two landfalling typhoons in 2017 (Hato and Pakhar) were investigated by using laser-optical disdrometers mounted at four altitudes (10, 40, 160, and 320 m) of the Shenzhen 356-m meteorological tower. Significant differences of the DSD and derived parameters, mass-weighted mean diameter (Dm), normalized intercept parameter (NW), and standard deviation of the mass distribution σm, were observed at different altitudes for the two typhoons, while the rainwater content between the four altitudes had no statistically significant differences. The low-altitude DSDs had more midsize drops (1 < D < 3 mm), fewer large drops (D > 3 mm), and narrower distribution widths than the high-altitude ones, while the concentration of small drops varied nonlinearly with height. The value of NW decreased with height, while Dm and σm increased with height. The gamma distribution parameters N0, μ, and Λ are found to increase with decreasing height. Both the derived μ–Λ and Z–R relations were significantly varied in different altitudes.

Sign in / Sign up

Export Citation Format

Share Document