Characterization of Vertical Velocity and Drop Size Distribution Parameters in Widespread Precipitation at ARM Facilities

2012 ◽  
Vol 51 (2) ◽  
pp. 380-391 ◽  
Author(s):  
Scott E. Giangrande ◽  
Edward P. Luke ◽  
Pavlos Kollias

AbstractExtended, high-resolution measurements of vertical air motion and median volume drop diameter D0 in widespread precipitation from three diverse Atmospheric Radiation Measurement Program (ARM) locations [Lamont, Oklahoma, Southern Great Plains site (SGP); Niamey, Niger; and Black Forest, Germany] are presented. The analysis indicates a weak (0–10 cm−1) downward air motion beneath the melting layer for all three regions, a magnitude that is to within the typical uncertainty of the retrieval methods. On average, the hourly estimated standard deviation of the vertical air motion is 0.25 m s−1 with no pronounced vertical structure. Profiles of D0 vary according to region and rainfall rate. The standard deviation of 1-min-averaged D0 profiles for isolated rainfall rate intervals is 0.3–0.4 mm. Additional insights into the form of the raindrop size distribution are provided using available dual-frequency Doppler velocity observations at SGP. The analysis suggests that gamma functions better explain paired velocity observations and radar retrievals for the Oklahoma dataset. This study will be useful in assessing uncertainties introduced in the measurement of precipitation parameters from ground-based and spaceborne remote sensors that are due to small-scale variability.

2008 ◽  
Vol 25 (12) ◽  
pp. 2282-2292 ◽  
Author(s):  
Laura Kanofsky ◽  
Phillip Chilson

Abstract Vertically pointed wind profiling radars can be used to obtain measurements of the underlying drop size distribution (DSD) for a rain event by means of the Doppler velocity spectrum. Precipitation parameters such as rainfall rate, radar reflectivity factor, liquid water content, mass-weighted mean drop diameter, and median volume drop diameter can then be calculated from the retrieved DSD. The DSD retrieval process is complicated by the presence of atmospheric turbulence, vertical ambient air motion, selection of fall speed relationships, and velocity thresholding. In this note, error analysis is presented to quantify the effect of each of those factors on rainfall rate. The error analysis results are then applied to two precipitation events to better interpret the rainfall-rate retrievals. It was found that a large source of error in rain rate is due to unaccounted-for vertical air motion. For example, in stratiform rain with a rainfall rate of R = 10 mm h−1, a mesoscale downdraft of 0.6 m s−1 can result in a 34% underestimation of the estimated value of R. The fall speed relationship selection and source of air density information both caused negligible errors. Errors due to velocity thresholding become more important in the presence of significant contamination near 0 m s−1, such as ground clutter. If particles having an equivalent volume diameter of 0.8 mm and smaller are rejected, rainfall rate errors from −4% to −10% are possible, although these estimates depend on DSD and rainfall rate.


2016 ◽  
Vol 17 (7) ◽  
pp. 2077-2104 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne

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.


Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo

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.


Author(s):  
Sung–Ho Suh ◽  
Hyeon–Joon Kim ◽  
Dong–In Lee ◽  
Tae–Hoon Kim

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.


2019 ◽  
Vol 58 (4) ◽  
pp. 787-796 ◽  
Author(s):  
Paul L. Smith ◽  
Roger W. Johnson ◽  
Donna V. Kliche

AbstractUse of the standard deviation σm of the drop mass distribution as one of the three parameters of raindrop size distribution (DSD) functions was introduced for application to disdrometer data supporting the Global Precipitation Measurement dual-frequency radar system. The other two parameters are a normalized drop number concentration Nw and the mass-weighted mean diameter Dm. This paper presents an evaluation of that formulation of the DSD functions, in two parts. First is a mathematical analysis showing that the procedure for estimating σm, along with the other DSD parameters, from disdrometer data is in essence another moment method. As such, it is subject to the biases and errors inherent in all moment methods. When the form of the DSD function is specified, it is inferior (like all moment methods) to the maximum likelihood technique for fitting parameters to sampled data. The second part is a series of sampling simulations illustrating the biases and errors involved in applying the formulation to the specific case of gamma DSDs. It leads to underestimates of σm and consequently to overestimates of the gamma shape parameter—with large root-mean-square errors. Comparison with maximum likelihood estimates shows the degree of improvement that could be obtained in the estimates of the shape parameter. The propensity to underestimate σm will be pervasive, and users of this DSD formulation should be cognizant of the biases and errors that can occur.


2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Kun Song ◽  
Xichuan Liu ◽  
Taichang Gao ◽  
Binsheng He

Estimation of raindrop size distribution (DSD) is essential in many meteorological and hydrologic fields. This paper proposes a method for retrieving path-averaged DSD parameters using joint dual-frequency and dual-polarization microwave links of the telecommunication system. Detailed analyses of the rain-induced attenuation calculation are performed based on the T-matrix method. A forward model is established for describing the relation between the DSD and the rain-induced attenuation. Then, the method is proposed to retrieve propagation path DSD parameters based on Levenberg–Marquardt optimization algorithm. The numerical simulation for path-averaged DSD retrieval shows that the RMSEs of three gamma DSD parameters are 0.34 mm−1, 0.81, and 3.21×103 m−3·mm−1, respectively, in rainfall intensity above 30 mm/h. Meanwhile, the method can retrieve the rainfall intensity without the influence of variational DSD. Theoretical analyses and numerical simulations confirm that the method for retrieving path-averaged DSD parameters is promising. The method can complement existing DSD monitoring systems such as the disdrometer and provide high-resolution rainfall measurements with widely distributed microwave links without additional cost.


2012 ◽  
Vol 51 (11) ◽  
pp. 1960-1970 ◽  
Author(s):  
Ricardo Sarmento Tenório ◽  
Marcia Cristina da Silva Moraes ◽  
Henri Sauvageot

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.


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