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 Modeling the relation between CCN and the vertical evolution of cloud drop size distribution in convective clouds with parcel model

2007 ◽  
Vol 22 (3) ◽  
pp. 313-321
Author(s):  
Gérson Paiva Almeida ◽  
Rômulo Rodrigues dos Santos
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Liquid Water Content ◽  
Drop Size Distribution ◽  
Amazon Forest ◽  
Polluted Environment ◽  
Cloud Drop ◽  
Microphysical Process ◽  
Warm Rain ◽  
Rain Formation

In this work we use values of effective radius of cloud drop size distribution and modal radius of liquid water content generated with a parcel model with detailed treatment of liquid phase microphysical process to evaluate the warm rain formation suppression over the Amazon due to the presence of aerosols generated by forest burning. Four cases based on observations are simulated: a clean marine environment as the one observed close to Fortaleza; a clean environment as the ones observed over the apparently unpolluted Amazon forest; a environment observed during the intense burning season in the polluted part of the Amazon; and the same polluted environment observed during the transition season from dry to wet. It is shown that the model reproduces quantitatively some of the observed features of clouds in different environments. The model indicated that in very polluted environment the warm rain formation process can be completely suppressed. Nevertheless, in certain situations the formation of warm rain can still be achieved and significant amount of rainwater can be formed.

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.

A Near-Wall Eddy Conductivity Model for Fluids With Different Prandtl Numbers

1994 ◽  
Vol 116 (4) ◽  
pp. 844-854 ◽  
Author(s):  
R. M. C. So ◽  
T. P. Sommer
Keyword(s):  
Kinetic Energy ◽  
Prandtl Number ◽  
Turbulent Kinetic Energy ◽  
Dissipation Rate ◽  
Reynolds Numbers ◽  
Turbulence Statistics ◽  
Temperature Variance ◽  
Prandtl Numbers ◽  
Good Agreement ◽  
Near Wall

Near-wall turbulence models for the velocity and temperature fields based on the transport equations for the Reynolds stresses, the dissipation rate of turbulent kinetic energy, and the temperature variance and its dissipation rate are formulated for flows with widely different Prandtl numbers. Conventional high-Reynolds-number models are used to close these equations and modifications are proposed to render them asymptotically correct near a wall compared to the behavior of the corresponding exact equations. Thus formulated, two additional constants are introduced into the definition of the eddy conductivity. These constants are found to be parametric in the Prandtl number. The near-wall models are used to calculate flows with different wall thermal boundary conditions covering a wide range of Reynolds numbers and Prandtl numbers. The calculated Nusselt number variations with Prandtl number are in good agreement with established formulae at two different Reynolds numbers. Furthermore, the mean profiles, turbulence statistics, heat flux, temperature variance, and the dissipation rates of turbulent kinetic energy and temperature variance are compared with measurements and direct numerical simulation data. These comparisons show that correct near-wall asymptotic behavior is recovered for the calculated turbulence statistics and the calculations are in good agreement with measurements over the range of Prandtl numbers investigated.

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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