scholarly journals Drop size distribution and kinetic energy load of rainfall events in the highlands of the Central Rift Valley, Ethiopia

2014 ◽  
Vol 59 (12) ◽  
pp. 2203-2215 ◽  
Author(s):  
Derege Tsegaye Meshesha ◽  
Atsushi Tsunekawa ◽  
Mitsuru Tsubo ◽  
Nigussie Haregeweyn ◽  
Enyew Adgo
Keyword(s):  
Kinetic Energy ◽  
Size Distribution ◽  
Rift Valley ◽  
Drop Size ◽  
Drop Size Distribution ◽  
Rainfall Events

scholarly journals A Warm Rain Microphysics Parameterization that Includes the Effect of Turbulence

2008 ◽  
Vol 65 (6) ◽  
pp. 1795-1816 ◽  
Author(s):  
Charmaine N. Franklin
Keyword(s):  
Kinetic Energy ◽  
Size Distribution ◽  
Turbulent Kinetic Energy ◽  
Dissipation Rate ◽  
Drop Size ◽  
Reynolds Numbers ◽  
Liquid Water Content ◽  
Drop Size Distribution ◽  
Collision Kernel ◽  
Warm Rain

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.

scholarly journals Disdrometer measurements under Sense-City rainfall simulator

2019 ◽  
Author(s):  
Auguste Gires ◽  
Philippe Bruley ◽  
Anne Ruas ◽  
Daniel Schertzer ◽  
Ioulia Tchiguirinskaia
Keyword(s):  
Kinetic Energy ◽  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Drop Size Distribution ◽  
Climatic Chamber ◽  
Sampling Area ◽  
Data Set ◽  
Raw Data ◽  
Rainfall Simulator

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.

scholarly journals Influence of drop size distribution and kinetic energy in precipitation modelling for laboratory rainfall simulators

2021 ◽  
Author(s):  
Harris Ramli ◽  
Siti Aimi Nadia Mohd Yusoff ◽  
Mastura Azmi ◽  
Nuridah Sabtu ◽  
Muhd Azril Hezmi
Keyword(s):  
Kinetic Energy ◽  
Size Distribution ◽  
Drop Size ◽  
Drop Size Distribution ◽  
Scale Model ◽  
Simulated Rainfall ◽  
Rainfall Simulator ◽  
Natural Rainfall ◽  
Set Up ◽  
The Given

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.

scholarly journals TECHNICAL NOTE: The representation of rainfall drop-size distribution and kinetic energy

2004 ◽  
Vol 8 (5) ◽  
pp. 1001-1007 ◽  
Author(s):  
N. I. Fox
Keyword(s):  
Soil Erosion ◽  
Kinetic Energy ◽  
Size Distribution ◽  
Energy Flux ◽  
Drop Size ◽  
Technical Note ◽  
Drop Size Distribution ◽  
Horizontal Component ◽  
Gamma Distributions ◽  
Definition Of

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

A novel classification rainfall type using a clustering approach in the tropical Andes.

2020 ◽  
Author(s):  
Gabriela Urgiles ◽  
Johanna Orellana-Alvear ◽  
Katja Trachte ◽  
Jörg Bendix ◽  
Rolando Célleri
Keyword(s):  
Size Distribution ◽  
Vertical Profile ◽  
Drop Size ◽  
Drop Size Distribution ◽  
Tropical Andes ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Rainfall Type ◽  
Clustering Approach ◽  
Microphysical Processes

<p>Information on the vertical profile of rainfall is important to improve our knowledge about microphysical processes that govern the formation of the hydrometeors. In addition, the vertical profile helps improving the quantitative precipitation estimation from scanning weather radars and may be useful to improve the parameterization of cloud microphysical processes in numerical models. Usually, rainfall types (e.g, stratiform and convective) are defined by using some rainfall characteristics of its vertical profile such as intensity and velocity. Furthermore, certain thresholds for these variables need to be defined to separate the rainfall classes. However, studies about the vertical profile of rainfall showed that the vertical variability of rainfall highly depends on the local climate and the study area. In consequence, these thresholds are a constraining factor for the rainfall class definitions because they cannot be generalized. Besides, the identification of thresholds can become too subjective and, thus, influence the identification of rainfall types. In regions of complex topography such as the Tropical Andes, rainfall vertical profile studies are very scarce and they show that rainfall classification has similar drawbacks such as the identification of thresholds. Thus, this study aims to develop a new methodology for rainfall events classification by using a data-driven clustering approach based on the k-means algorithm that allows accounting for the similarities of rainfall characteristics (e.g., duration, intensity, drop size distribution) of each rainfall type. The study was carried out using data retrieved from a K-band Doppler Micro Rain Radar (MRR) that records rainfall characteristics such as rainfall intensity, drop velocity, reflectivity profile, drop size distribution (DSD), and liquid water content (LWC). The MRR was located in the tropical Andes, at 2600 m a.s.l., in the city of Cuenca, Ecuador.  Three years of data were available for the study with a temporal resolution of 1 minute.  First, the rainfall events were identified by using three criteria: minimum inter-event, minimum total accumulation, and minimum duration. Then, by using the k-means approach, several iterations with different number of clusters each were evaluated and consequently, three representative rainfall classes were found. These classes showed certain transitions (e.g., for rainfall intensity, velocity and drop size distribution) that separated the rainfall classes. The distributions of these rainfall event characteristics were compared with those found in the literature. This novel classification provided new insights about the variability of the rainfall in this tropical mountain setting and how its characteristics revealed distinctive patterns of the rainfall processes. Finally, since the rain types were identified by a data-driven method, it ensured an objective separation of the rainfall events. Thus, the application of this method in other sites will allow contrasting previous findings regarding the suitability of the tailor-used thresholds for rainfall classification.</p>

scholarly journals Two months of disdrometer data in the Paris area

2018 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer
Keyword(s):  
Kinetic Energy ◽  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Drop Size Distribution ◽  
Sampling Area ◽  
Data Set ◽  
Raw Data ◽  
Paris Area

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

scholarly journals Two months of disdrometer data in the Paris area

2018 ◽  
Vol 10 (2) ◽  
pp. 941-950 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer
Keyword(s):  
Kinetic Energy ◽  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Drop Size Distribution ◽  
Access To Information ◽  
Sampling Area ◽  
Data Set ◽  
Raw Data ◽  
Paris Area

Abstract. The Hydrology, Meteorology, and Complexity laboratory of École des Ponts ParisTech (hmco.enpc.fr) has made a data set of optical disdrometer measurements available that come from a campaign involving three collocated devices from two different manufacturers, relying on different underlying technologies (one Campbell Scientific PWS100 and two OTT Parsivel2 instruments). The campaign took place in January–February 2016 in the Paris area (France). Disdrometers provide access to information on the size and velocity of drops falling through the sampling area of the devices of roughly a few tens of cm2. It enables the drop size distribution to be estimated and rainfall microphysics, kinetic energy, or radar quantities, for example, to be studied further. 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 as the rain rate or drop size distribution with filtering, are available. Link to the data set: https://zenodo.org/record/1240168 (DOI: https://doi.org/10.5281/zenodo.1240168).

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