On the Relationships Between Radar Reflectivity and Rainfall Rate and Kinetic Energy Resulting From a Weibull Drop Size Distribution

2020 ◽  
Vol 56 (10) ◽  
Author(s):  
Shmuel Assouline
1991 ◽  
Vol 30 (7) ◽  
pp. 1025-1033 ◽  
Author(s):  
A. R. Jameson

Abstract The substantial upwelling microwave radiation emitted by rain, as well as the relative simplicity of radiometers, guarantees their continuing important role in measuring rain from space. However, for frequencies greater than around 20 GHz, ice clouds overlying rain often scatter much of the upwelling radiation out of the field of view. In addition, at these frequencies raindrops scatter so well that oven when a few more are added to an already low concentration of drops, the additional drops actually scatter away more radiation than they contribute to the field of view. Because of these two effects, the direct measurement of rainfall rate at high microwave frequencies using upwelling radiation is restricted to low rainfall rates. In contrast, from 3 to 10 GHz emissions from raindrops and from clouds dominate the radiative transfer equation. Because emission and absorption are reciprocal, the combined absorption coefficient of the cloud and the rain can be estimated from the upwelling radiation at these frequencies. After extracting the component due to rain (ka), it may be used to estimate the rainfall rate ξ(R). It is important, therefore, that R depend as strongly as possible on ka. The physical link between R and ka varies depending upon the microwave frequency. The weaker the relation the more sensitive ka and ξ(R) are to variations in the drop-size distribution. In this study it is shown that the scatter in ka and ξ(R), in response to variations in the drop-size distribution, is greatest at 8 and smallest at 3 GHz.


2008 ◽  
Vol 65 (6) ◽  
pp. 1795-1816 ◽  
Author(s):  
Charmaine N. Franklin

Abstract A warm rain parameterization has been developed by solving the stochastic collection equation with the use of turbulent collision kernels. The resulting parameterizations for the processes of autoconversion, accretion, and self-collection are functions of the turbulent intensity of the flow and are applicable to turbulent cloud conditions ranging in dissipation rates of turbulent kinetic energy from 100 to 1500 cm2 s−3. Turbulence has a significant effect on the acceleration of the drop size distribution and can reduce the time to the formation of raindrops. When the stochastic collection equation is solved with the gravitational collision kernel for an initial distribution with a liquid water content of 1 g m−3 and 240 drops cm−3 with a mean volume radius of 10 μm, the amount of mass that is transferred to drop sizes greater than 40 μm in radius after 20 min is 0.9% of the total mass. When the stochastic collection equation is solved with a turbulent collision kernel for collector drops in the range of 10–30 μm with a dissipation rate of turbulent kinetic energy equal to 100 cm2 s−3, this percentage increases to 21.4. Increasing the dissipation rate of turbulent kinetic energy to 500, 1000, and 1500 cm2 s−3 further increases the percentage of mass transferred to radii greater than 40 μm after 20 min to 41%, 52%, and 58%, respectively, showing a substantial acceleration of the drop size distribution when a turbulent collision kernel that includes both turbulent and gravitational forcing replaces the purely gravitational kernel. The warm rain microphysics parameterization has been developed from direct numerical simulation (DNS) results that are characterized by Reynolds numbers that are orders of magnitude smaller than those of atmospheric turbulence. The uncertainty involved with the extrapolation of the results to high Reynolds numbers, the use of gravitational collision efficiencies, and the range of the droplets for which the effect of turbulence has been included should all be considered when interpreting results based on these new microphysics parameterizations.


2019 ◽  
Author(s):  
Auguste Gires ◽  
Philippe Bruley ◽  
Anne Ruas ◽  
Daniel Schertzer ◽  
Ioulia Tchiguirinskaia

Abstract. The Hydrology, Meteorology and Complexity laboratory of Ecole des Ponts ParisTech (hmco.enpc.fr) and the Sense-City consortium (http://sense-city.ifsttar.fr/) make available a data set of optical disdrometers measurements coming from a cam-paign that took place in September 2017 under the rainfall simulator of the Sense-City climatic chamber which is located near Paris. Two OTT Parsivel2 were used. The size and velocity of drops falling through the sampling area of the devices of roughly few tens of cm2 is computed by disdrometers. This enables to estimate the drop size distribution and further study rainfall micro-physics or kinetic energy for example. Raw data, i.e. basically a matrix containing a number of drops according to classes of size and velocity, along with more aggregated ones such rain rate or drop size distribution with filtering is available. Link to the data set (Gires et al., 2019): http://doi.org/10.5281/zenodo.3347051.


2021 ◽  
Author(s):  
Harris Ramli ◽  
Siti Aimi Nadia Mohd Yusoff ◽  
Mastura Azmi ◽  
Nuridah Sabtu ◽  
Muhd Azril Hezmi

Abstract. It is difficult to define the hydrologic and hydraulic characteristics of rain for research purposes, especially when trying to replicate natural rainfall using artificial rain on a small laboratory scale model. The aim of this paper was to use a drip-type rainfall simulator to design, build, calibrate, and run a simulated rainfall. Rainfall intensities of 40, 60 and 80 mm/h were used to represent heavy rainfall events of 1-hour duration. Flour pellet methods were used to obtain the drop size distribution of the simulated rainfall. The results show that the average drop size for all investigated rainfall intensities ranges from 3.0–3.4 mm. The median value of the drop size distribution or known as D50 of simulated rainfall for 40, 60 and 80 mm/h are 3.4, 3.6, and 3.7 mm, respectively. Due to the comparatively low drop height (1.5 m), the terminal velocities monitored were between 63–75 % (8.45–8.65 m/s), which is lower than the value for natural rainfall with more than 90 % for terminal velocities. This condition also reduces rainfall kinetic energy of 25.88–28.51 J/m2mm compared to natural rainfall. This phenomenon is relatively common in portable rainfall simulators, representing the best exchange between all relevant rainfall parameters obtained with the given simulator set-up. Since the rainfall can be controlled, the erratic and unpredictable changeability of natural rainfall is eliminated. Emanating from the findings, drip-types rainfall simulator produces rainfall characteristics almost similar to natural rainfall-like characteristic is the main target.


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.


2014 ◽  
Vol 59 (12) ◽  
pp. 2203-2215 ◽  
Author(s):  
Derege Tsegaye Meshesha ◽  
Atsushi Tsunekawa ◽  
Mitsuru Tsubo ◽  
Nigussie Haregeweyn ◽  
Enyew Adgo

2004 ◽  
Vol 8 (5) ◽  
pp. 1001-1007 ◽  
Author(s):  
N. I. Fox

Abstract. To relate observed rainfall rates (R) to the kinetic energy flux (E) that affects soil erosion it is necessary to develop relationships between the two. This paper explores theoretical E–R relationships based on gamma distributions of drop size. The relationship is poorly defined unless assumptions are made about changes in the shape of the drop-size distribution (DSD) with rainfall rate. The study suggests that the assumption of an exponential DSD leads to overestimation of kinetic energy flux. Further, incorporation of a horizontal component of kinetic energy allows for a clearer relationship between kinetic energy and rainfall intensity to be defined, but a question remains regarding the most appropriate definition of the horizontal component of drop velocity. Keywords: drop-size distribution, drop kinetic energy, soil erosion


2018 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer

Abstract. The Hydrology, Meteorology and Complexity laboratory of Ecole des Ponts ParisTech (hmco.enpc.fr) makes available a data set of optical disdrometers measurements coming from a campaign involving three collocated devices from two different manufacturers relying on different underlying technologies (one Campbell Scientific PWS100 and two OTT Parsivel2). The campaign took place on January–February 2016 in the Paris area (France). Disdrometers give access to the size and velocity of drops falling through the sampling area of the devices of roughly few tens of cm2. It enables to estimate the drop size distribution and further study rainfall micro-physics, kinetic energy or radar quantities for example. Raw data, i.e. basically a matrix containing a number of drops according to classes of size and velocity, along with more aggregated one such rain rate or drop size distribution with filtering is available. Link to the data set: https://zenodo.org/record/1125583


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