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 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 Measurement and computation of kinetic energy of simulated rainfall in comparison with natural rainfall

2018 ◽  
Vol 13 (No. 4) ◽  
pp. 226-233 ◽  
Author(s):  
Petrů Jan ◽  
Kalibová Jana
Keyword(s):  
Kinetic Energy ◽  
Drop Size ◽  
Rainfall Intensity ◽  
Soil Aggregates ◽  
Meteorological Parameter ◽  
Simulated Rainfall ◽  
Fall Velocity ◽  
Rainfall Simulator ◽  
Rainfall Characteristics ◽  
Natural Rainfall

Rainfall characteristics such as total amount and rainfall intensity (I) are important inputs in calculating the kinetic energy (KE) of rainfall. Although KE is a crucial indicator of the raindrop potential to disrupt soil aggregates, it is not a routinely measured meteorological parameter. Therefore, KE is derived from easily accessible variables, such as I, in empirical laws. The present study examines whether the equations which had been derived to calculate KE of natural rainfall are suitable for the calculation of KE of simulated rainfall. During the experiment presented in this paper, the measurement of rainfall characteristics was carried out under laboratory conditions using a rainfall simulator. In total, 90 measurements were performed and evaluated to describe the rainfall intensity, drop size distribution and velocity of rain drops using the Thies laser disdrometer. The duration of each measurement of rainfall event was 5 minutes. Drop size and fall velocity were used to calculate KE and to derive a new equation of time-specific kinetic energy (KE<sub>time</sub> – I). When comparing the newly derived equation for KE of simulated rainfall with the six most commonly used equations for KE<sub>time</sub> – I of natural rainfall, KE of simulated rainfall was discovered to be underestimated. The higher the rainfall intensity, the higher the rate of underestimation. KE of natural rainfall derived from theoretical equations exceeded KE of simulated rainfall by 53–83% for I = 30 mm/h and by 119–275% for I = 60 mm/h. The underestimation of KE of simulated rainfall is probably caused by smaller drops formed by the rainfall simulator at higher intensities (94% of all drops were smaller than 1 mm), which is not typical of natural rainfall.

scholarly journals Measurement and computation of kinetic energy of simulated rainfall in comparison with natural rainfall.

2018 ◽  
Author(s):  
Petrů Jan ◽  
Kalibová Jana
Keyword(s):  
Kinetic Energy ◽  
Drop Size ◽  
Rainfall Intensity ◽  
Soil Aggregates ◽  
Meteorological Parameter ◽  
Simulated Rainfall ◽  
Fall Velocity ◽  
Rainfall Simulator ◽  
Rainfall Characteristics ◽  
Natural Rainfall

Rainfall characteristics such as total amount and rainfall intensity (I) are important inputs in calculating the kinetic energy (KE) of rainfall. Although KE is a crucial indicator of the raindrop potential to disrupt soil aggregates, it is not a routinely measured meteorological parameter. Therefore, KE is derived from easily accessible variables, such as I, in empirical laws. The present study examines whether the equations which had been derived to calculate KE of natural rainfall are suitable for the calculation of KE of simulated rainfall. During the experiment presented in this paper, the measurement of rainfall characteristics was carried out under laboratory conditions using a rainfall simulator. In total, 90 measurements were performed and evaluated to describe the rainfall intensity, drop size distribution and velocity of rain drops using the Thies laser disdrometer. The duration of each measurement of rainfall event was 5 minutes. Drop size and fall velocity were used to calculate KE and to derive a new equation of time-specific kinetic energy (KE<sub>time</sub> – I). When comparing the newly derived equation for KE of simulated rainfall with the six most commonly used equations for KE<sub>time</sub> – I of natural rainfall, KE of simulated rainfall was discovered to be underestimated. The higher the rainfall intensity, the higher the rate of underestimation. KE of natural rainfall derived from theoretical equations exceeded KE of simulated rainfall by 53–83% for I = 30 mm/h and by 119–275% for I = 60 mm/h. The underestimation of KE of simulated rainfall is probably caused by smaller drops formed by the rainfall simulator at higher intensities (94% of all drops were smaller than 1 mm), which is not typical of natural rainfall.  

scholarly journals Disdrometer measurements under Sense-City rainfall simulator

2020 ◽  
Vol 12 (2) ◽  
pp. 835-845 ◽  
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 ◽  
Raw Data ◽  
Rainfall Simulator

Abstract. The Hydrology, Meteorology and Complexity Laboratory of École des Ponts ParisTech (http://hmco.enpc.fr, last access: 24 March 2020) and the Sense-City consortium (http://sense-city.ifsttar.fr/, last access: 24 March 2020) made available a dataset of optical disdrometer measurements stemming from a campaign that took place in September 2017 under the rainfall simulator of the Sense-City climatic chamber, which is located near Paris. Two OTT Parsivel2 disdrometers were used. The size and velocity of drops falling through the sampling area of the devices of roughly a few tens of square centimetres are computed by disdrometers. This enables the estimation of the drop size distribution and the further study of rainfall microphysics or kinetic energy for example. Raw data – basically a matrix containing a number of drops according to classes of size and velocity, along with more aggregated ones such as rain rate and drop size distribution with filtering – are available. The dataset is publicly available at https://doi.org/10.5281/zenodo.3347051(Gires et al., 2019).

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.

Application of an optical disdrometer to characterize simulated rainfall and measure drop-size distribution

2018 ◽  
Vol 63 (10) ◽  
pp. 1574-1587
Author(s):  
Derege Tsegaye Meshesha ◽  
Atsushi Tsunekawa ◽  
Nigussie Haregeweyen
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Drop Size Distribution ◽  
Simulated Rainfall

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
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