Geographical characteristics of raindrop size distribution in the southern parts of Korea

2020 ◽  
Author(s):  
Sung–Ho Suh ◽  
Hyeon–Joon Kim ◽  
Dong–In Lee ◽  
Tae–Hoon Kim
Keyword(s):  
Size Distribution ◽  
Coastal Area ◽  
Sea Breeze ◽  
Convective Precipitation ◽  
Drop Diameter ◽  
Local Maxima ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Stratiform Rainfall

AbstractThis study analyzed the regional characteristics of raindrop size distribution (DSD) in the southern coastal area of South Korea. Data from March 2016 to February 2017 were recorded by four PARSIVEL disdrometers installed at intervals of ~20 km from the coastline to inland. Within 20 km from the coastline, multiple local maxima in the probability density function (PDF) were observed at Dm (mass-weighted drop diameter) = 0.6 mm and logNw (normalized intercept parameter) = 5.2 for stratiform rainfall, but these features were not observed more than 20 km from the coastline. Based on mean Dm–logNw values, stratiform rainfall clearly differed between coastal and inland areas. For convective precipitation, there was a linear relationship between Dm and Nw with the distance from the coastline. PDF analyses of diurnal variation in DSD confirmed that in spring and autumn the multiple local maxima appear in the daytime. The multiple local maxima in Dm (logNw) values were lower (higher) at nighttime (NT) than DT in the spring and summer season. These features were highly dependent on the prevailing wind. There was a pattern of increasing A and decreasing b in the radar reflectivity–rainfall rate (Z–R) relationship (Z = ARb) with distance from the coastline, and these features were more pronounced in convective precipitation. These diurnal variabilities were regular in stratiform rainfall, and there were large differences in quantitative precipitation estimation depending on the land–sea breeze in the coastal area.

scholarly journals Observed Response of the Raindrop Size Distribution to Changes in the Melting Layer

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 319 ◽  
Author(s):  
Patrick Gatlin ◽  
Walter Petersen ◽  
Kevin Knupp ◽  
Lawrence Carey
Keyword(s):  
Size Distribution ◽  
Basic Assumption ◽  
Weighted Mean ◽  
Radar Rainfall ◽  
Melting Layer ◽  
Quantitative Precipitation Estimation ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Stratiform Rainfall

Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the RSD, in particular the mass-weighted mean diameter (Dm), of stratiform rainfall. We utilize ground-based polarimetric radar to map the ML and compare it with Dm observations from the ground upwards to the bottom of the ML. The results show definitive proof that a thickening, and to a lesser extent a lowering, of the ML causes an increase in raindrop diameter below the ML that extends to the surface. The connection between rainfall at the ground and the overlying microphysics in the column provide a means for improving radar QPE at far distances from a ground-based radar or close to the ground where satellite-based radar rainfall retrievals can be ill-defined.

scholarly journals STUDY ON SUMMER RAINDROP SIZE DISTRIBUTION AND RETRIEVED POLARIMETRIC RADAR PARAMETER OVER LEIZHOU PENINSULA

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 245-250
Author(s):  
Z. B. Zhou ◽  
J. J. Lv ◽  
S. J. Niu
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Least Squares Method ◽  
Convective Precipitation ◽  
Polarimetric Radar ◽  
Leizhou Peninsula ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Subtropical Monsoon Climate

Abstract. Leizhou peninsula is located in the south of Guangdong Province, near South China Sea, and has a tropical and subtropical monsoon climate. Based on observed drop size distribution (DSD) data from July 2007 to August 2007 with PARSIVEL disdrometers deployed at Zhanjiang and Suixi, the characterists of DSDs are studied. Non-linear least squares method is used to fit Gamma distribution. Convective and stratiform averaged DSDs are in good agreement with Gamma distribution, especially in stratiform case. Convective average DSDs have a wider spectrum and higher peak. Microphysical parameter differences between convective and stratiform are discussed, convective precipitation has a higher mass-weighted mean diameter (Dm) and generalized intercepts (Nw) in both areas. The constrained relations between Gamma distribution parameter (μ, Λ, N0) is derived. The retrieved polarimetric radar parameter (KDP, ZDR, Zh) have a good self-consistency, which can be used to improve the accuracy of KDP calculation. R-KDP-ZDR is superior to the R-KDP, R-ZDR-Zh in quantitative precipitation estimation (QPE), with a correlation coefficient higher than 0.98.

scholarly journals Measurements and Modeling of the Full Rain Drop Size Distribution

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo
Keyword(s):  
Size Distribution ◽  
Small Drop ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Rain Drop ◽  
Double Moment ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Global Precipitation

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite.

scholarly journals Small-Scale Variability of the Raindrop Size Distribution and Its Effect on Areal Rainfall Retrieval

2016 ◽  
Vol 17 (7) ◽  
pp. 2077-2104 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Integration Time ◽  
Small Scale ◽  
Drop Diameter ◽  
Weather Model ◽  
Raindrop Size Distribution ◽  
Areal Rainfall ◽  
Raindrop Size ◽  
Microphysical Processes

Abstract The drop size distribution (DSD) describes the microstructure of liquid precipitation. The high variability of the DSD reflects the variety of microphysical processes controlling raindrop properties and affects the retrieval of rainfall. An analysis of the effects of DSD subgrid variability on areal estimation of precipitation is presented. Data used were recorded with a network of disdrometers in Ardèche, France. DSD variability was studied over two typical scales: 5 km × 5 km, similar to the ground footprint size of the Global Precipitation Measurement (GPM) spaceborne weather radar, and 2.8 km × 2.8 km, an operational pixel size of the Consortium for Small-Scale Modeling (COSMO) numerical weather model. Stochastic simulation was used to generate high-resolution grids of DSD estimates over the regions of interest, constrained by experimental DSDs measured by disdrometers. From these grids, areal DSD estimates were derived. The error introduced by assuming a point measurement to be representative of the areal DSD was quantitatively characterized and was shown to increase with the size of the considered area and with drop size and to decrease with the integration time. The controlled framework allowed for the accuracy of retrieval algorithms to be investigated. Rainfall variables derived by idealized simulations of GPM- and COSMO-style algorithms were compared to subgrid distributions of the same variables. While rain rate and radar reflectivity were well represented, the estimated drop concentration and mass-weighted mean drop diameter were often less representative of subgrid values.

scholarly journals Raindrop Size Distribution and Radar Parameters in Coastal Tropical Rain Systems of Northeastern Brazil

2012 ◽  
Vol 51 (11) ◽  
pp. 1960-1970 ◽  
Author(s):  
Ricardo Sarmento Tenório ◽  
Marcia Cristina da Silva Moraes ◽  
Henri Sauvageot
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
The Other ◽  
Northeastern Brazil ◽  
Drop Diameter ◽  
Coastal Site ◽  
Raindrop Size Distribution ◽  
The Mean ◽  
Raindrop Size ◽  
Bearing System

AbstractA dataset on raindrop size distribution (DSD) gathered in a coastal site of the Alagoas state in northeastern Brazil is used to analyze some differences between continental and maritime rainfall parameters. The dataset is divided into two subsets. One is composed of rainfall systems coming from the continent and moving eastward (i.e., offshore), representing the continental subset. The other is composed of rainfall systems that developed over the sea and are moving westward (i.e., inshore), representing the maritime subset. The mean conditional rain rate (i.e., for rain rate R > 0) is found to be higher for maritime (4.6 mm h−1) than for continental (3.2 mm h−1) conditions. The coefficient of variation of the conditional rain rate is lower for the maritime (1.75) than for the continental (2.25) subset. The continental and maritime DSDs display significant differences. For drop diameter D smaller than about 2 mm, the number of drops is higher for maritime rain than for continental rain. This reverses for D > 2 mm, in such a way that radar reflectivity factor Z for the maritime case is lower than for the continental case at the same rain rate. These results show that, to estimate precipitation by radar in the coastal area of northeastern Brazil, coefficients of the Z–R relation need to be adapted to the direction of motion of the rain-bearing system, inshore or offshore.

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.

scholarly journals Reconstructing the Drizzle Mode of the Raindrop Size Distribution Using Double-Moment Normalization

2019 ◽  
Vol 58 (1) ◽  
pp. 145-164 ◽  
Author(s):  
Timothy H. Raupach ◽  
Merhala Thurai ◽  
V. N. Bringi ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Drop Diameter ◽  
Light Rain ◽  
Raindrop Size Distribution ◽  
Shoulder Region ◽  
Double Moment ◽  
Best Fitting ◽  
Raindrop Size ◽  
Fitting Model

AbstractCommonly used disdrometers tend not to accurately measure concentrations of very small drops in the raindrop size distribution (DSD), either through truncation of the DSD at the small-drop end or because of large uncertainties on these measurements. Recent studies have shown that, as a result of these inaccuracies, many if not most ground-based disdrometers do not capture the “drizzle mode” of precipitation, which consists of large concentrations of small drops and is often separated from the main part of the DSD by a shoulder region. We present a technique for reconstructing the drizzle mode of the DSD from “incomplete” measurements in which the drizzle mode is not present. Two statistical moments of the DSD that are well measured by standard disdrometers are identified and used with a double-moment normalized DSD function that describes the DSD shape. A model representing the double-moment normalized DSD is trained using measurements of DSD spectra that contain the drizzle mode obtained using collocated Meteorological Particle Spectrometer and 2D video disdrometer instruments. The best-fitting model is shown to depend on temporal resolution. The result is a method to estimate, from truncated or uncertain measurements of the DSD, a more complete DSD that includes the drizzle mode. The technique reduces bias on low-order moments of the DSD that influence important bulk variables such as the total drop concentration and mass-weighted mean drop diameter. The reconstruction is flexible and often produces better rain-rate estimations than a previous DSD correction routine, particularly for light rain.

scholarly journals An Inverse Model for Raindrop Size Distribution Retrieval with Polarimetric Variables

2018 ◽  
Vol 10 (8) ◽  
pp. 1179 ◽  
Author(s):  
Guang Wen ◽  
Haonan Chen ◽  
Guifu Zhang ◽  
Jiming Sun
Keyword(s):  
Size Distribution ◽  
Liquid Water Content ◽  
Radar Data ◽  
Inverse Model ◽  
Training Data ◽  
Training Dataset ◽  
Drop Diameter ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Nearest Neighborhood

This paper proposes an inverse model for raindrop size distribution (DSD) retrieval with polarimetric radar variables. In this method, a forward operator is first developed based on the simulations of monodisperse raindrops using a T-matrix method, and then approximated with a polynomial function to generate a pseudo training dataset by considering the maximum drop diameter in a truncated Gamma model for DSD. With the pseudo training data, a nearest-neighborhood method is optimized in terms of mass-weighted diameter and liquid water content. Finally, the inverse model is evaluated with simulated and real radar data, both of which yield better agreement with disdrometer observations compared to the existing Bayesian approach. In addition, the rainfall rate derived from the DSD by the inverse model is also improved when compared to the methods using the power-law relations.

scholarly journals Improving the rainfall rate estimation in the midstream of the Heihe River Basin using raindrop size distribution

2011 ◽  
Vol 15 (3) ◽  
pp. 943-951 ◽  
Author(s):  
G. Zhao ◽  
R. Chu ◽  
T. Zhang ◽  
J. Li ◽  
J. Shen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Tibet Plateau ◽  
Heihe River ◽  
Drop Diameter ◽  
Observation Data ◽  
Polarimetric Radar ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size

Abstract. During the intensive observation period of the Watershed Allied Telemetry Experimental Research (WATER), a total of 1074 raindrop size distribution were measured by the Parsivel disdrometer, the latest state-of-the-art optical laser instrument. Because of the limited observation data in Qinghai-Tibet Plateau, the modelling behaviour was not well done. We used raindrop size distributions to improve the rain rate estimator of meteorological radar in order to obtain many accurate rain rate data in this area. We got the relationship between the terminal velocity of the raindrop and the diameter (mm) of a raindrop: v(D) = 4.67D0.53. Then four types of estimators for X-band polarimetric radar are examined. The simulation results show that the classical estimator R (ZH) is most sensitive to variations in DSD and the estimator R (KDP, ZH, ZDR) is the best estimator for estimating the rain rate. An X-band polarimetric radar (714XDP) is used for verifying these estimators. The lowest sensitivity of the rain rate estimator R (KDP, ZH, ZDR) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 3rd power of the drop diameter. On the other hand, the exponent of the backscatter cross-section, which contributes to ZH, is proportional to the 6th power of the drop diameter. Because the rain rate R is proportional to the 3.57th power of the drop diameter, KDP is less sensitive to DSD variations than ZH.

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