A numerical cloud model study of the Hallett-Mossop ice multiplication process in strong convection

1989 ◽  
Vol 23 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Nenad M. Aleksić ◽  
R.D. Farley ◽  
H.D. Orville
Keyword(s):  
Cloud Model ◽  
Multiplication Process ◽  
Model Study ◽  
Strong Convection ◽  
Ice Multiplication ◽  
Numerical Cloud Model

Empirical Formulation for number of ice crystal fragments by sublimational breakup

2020 ◽  
Author(s):  
Akash Deshmukh ◽  
Vaughan Phillips
Keyword(s):  
Relative Humidity ◽  
Cloud Model ◽  
Experimental Studies ◽  
Ice Crystal ◽  
Initial Size ◽  
Sublimation Process ◽  
Numerical Formulation ◽  
High Concentrations ◽  
Ice Multiplication ◽  
Ice Production

<p>There is much uncertainty about high concentrations of ice observed in clouds and their origins. In the literature, there have been previous experimental studies reported about the sublimation process of an ice crystal causes emission of fragments by breakup.   Such sublimational breakup is a type of secondary ice production, which in natural clouds can cause ice multiplication. </p><p>To represent this process of sublimation breakup in any cloud model, the present study proposes a numerical formulation of the number of ice fragments generated by sublimation of pristine ice crystal. This is done by amalgamating laboratory observations from previous published studies. The number of ice fragments determined by relative humidity (RH) and initial size of the ice particle were measured in the published experiments, and by simulating them we are able to infer parameters of a sublimation breakup scheme.   At small initial sizes, the dependency on size prevails, whereas at larger sizes both dependencies are comparable. This formulation is compared with observations to see the behaviour of it.</p>

scholarly journals Ice–Ice Collisions: An Ice Multiplication Process in Atmospheric Clouds

2011 ◽  
Vol 68 (2) ◽  
pp. 322-333 ◽  
Author(s):  
J.-I. Yano ◽  
V. T. J. Phillips
Keyword(s):  
Global Climate ◽  
Critical Role ◽  
Base Temperature ◽  
Physical Processes ◽  
Ice Breakup ◽  
Breakup Mechanism ◽  
Multiplication Process ◽  
Ice Particles ◽  
Ice Multiplication ◽  
Mixed Phase Clouds

Abstract Ice in atmospheric clouds undergoes complex physical processes, interacting especially with radiation, which leads to serious impacts on global climate. After their primary production, atmospheric ice crystals multiply extensively by secondary processes. Here, it is shown that a mostly overlooked process of mechanical breakup of ice particles by ice–ice collisions contributes to such observed multiplication. A regime for explosive multiplication is identified in its phase space of ice multiplication efficiency and number concentration of ice particles. Many natural mixed-phase clouds, if they have copious millimeter-sized graupel, fall into this explosive regime. The usual Hallett–Mossop (H–M) process of ice multiplication is shown to dominate the overall ice multiplication when active, as it starts sooner, compared to the breakup ice multiplication process. However, for deep clouds with a cold base temperature where the usual H–M process is inactive, the ice breakup mechanism should play a critical role. Supercooled rain, which may freeze to form graupel directly in only a few minutes, is shown to hasten such ice multiplication by mechanical breakup, with an ice enhancement ratio exceeding 104 approximately 20 min after small graupel first appear. The ascent-dependent onset of subsaturation with respect to liquid water during explosive ice multiplication is predicted to determine the eventual ice concentrations.

Lightning Generation in a Jovian Thundercloud: Results from an Axisymmetric Numerical Cloud Model

Icarus ◽  
1995 ◽  
Vol 115 (2) ◽  
pp. 421-434 ◽  
Author(s):  
Yoav Yair ◽  
Zev Levin ◽  
Shalva Tzivion
Keyword(s):  
Cloud Model ◽  
Numerical Cloud Model

scholarly journals Aerosols' influence on the interplay between condensation, evaporation and rain in warm cumulus cloud

2007 ◽  
Vol 7 (4) ◽  
pp. 12687-12714 ◽  
Author(s):  
O. Altaratz ◽  
I. Koren ◽  
T. Reisin ◽  
A. Kostinski ◽  
G. Feingold ◽  
...  
Keyword(s):  
Surface Area ◽  
Cloud Model ◽  
Volume Ratio ◽  
Meteorological Conditions ◽  
Drop Surface ◽  
Evaporation Process ◽  
Cumulus Cloud ◽  
Convective Clouds ◽  
Rain Drops ◽  
Numerical Cloud Model

Abstract. A numerical cloud model is used to study the influence of aerosol on the microphysics and dynamics of moderate-sized, coastal, convective clouds that develop under the same meteorological conditions. The results show that polluted convective clouds start their precipitation later and precipitate less than clean clouds but produce larger rain drops. The evaporation process is more significant at the margins of the polluted clouds (compared to the clean cloud) due to a higher drop surface area to volume ratio and it is mostly from small drops. It was found that the formation of larger raindrops in the polluted cloud is due to a more efficient collection process.

Growth and Decay of Error in a Numerical Cloud Model Due to Small Initial Perturbations and Parameter Changes

1995 ◽  
Vol 34 (7) ◽  
pp. 1622-1632 ◽  
Author(s):  
Qihang Li ◽  
Rafael L. Bras ◽  
Shafiqul Islam
Keyword(s):  
Boundary Conditions ◽  
Cloud Model ◽  
Grid Point ◽  
Potential Temperature ◽  
Temperature Perturbation ◽  
Lateral Boundary ◽  
Error Growth ◽  
Time Step ◽  
Lateral Boundary Conditions ◽  
Numerical Cloud Model

Abstract The behavior of a numerical cloud model is investigated in terms of its sensitivity to perturbations with two kinds of lateral boundary conditions: 1) with cyclic lateral boundary conditions, the model is sensitive to many aspects of its structure, including a very small potential temperature perturbation at only one grid point, changes in time step, and small changes in parameters such as the autoconversion rate from cloud water to rainwater and the latent heat of vaporization; 2) with prescribed lateral boundary conditions, growth and decay of perturbations are highly dependent on the flow conditions inside the domain. It is shown that under relatively uniform (unidirectional) advection across the domain, the perturbations will decay. On the other hand, convergence, divergence, or, in general, flow patterns with changing directions support error growth. This study shows that it is the flow structure inside the model domain that is important in determining whether the prescribed lateral boundary conditions will result in decaying or growing perturbations. The numerical model is inherently sensitive to initial perturbations, but errors can decay due to advection of information from lateral boundaries across the domain by uniform flow. This result provides one explanation to the reported results in earlier studies showing both error growth and decay.

scholarly journals Aerosols' influence on the interplay between condensation, evaporation and rain in warm cumulus cloud

2008 ◽  
Vol 8 (1) ◽  
pp. 15-24 ◽  
Author(s):  
O. Altaratz ◽  
I. Koren ◽  
T. Reisin ◽  
A. Kostinski ◽  
G. Feingold ◽  
...  
Keyword(s):  
Surface Area ◽  
Cloud Model ◽  
Volume Ratio ◽  
Meteorological Conditions ◽  
Drop Surface ◽  
Evaporation Process ◽  
Cumulus Cloud ◽  
Convective Clouds ◽  
Rain Drops ◽  
Numerical Cloud Model

Abstract. A numerical cloud model is used to study the influence of aerosol on the microphysics and dynamics of moderate-sized, coastal, convective clouds that develop under the same meteorological conditions. The results show that polluted convective clouds start their precipitation later and precipitate less than clean clouds but produce larger rain drops. The evaporation process is more significant at the margins of the polluted clouds (compared to the clean cloud) due to a higher drop surface area to volume ratio and it is mostly from small drops. It was found that the formation of larger raindrops in the polluted cloud is due to a more efficient collection process.

scholarly journals University of Warsaw Lagrangian Cloud Model (UWLCM) 2.0: Adaptation of a mixed Eulerian-Lagrangian numerical model for heterogeneous computing clusters

2021 ◽  
Author(s):  
Piotr Dziekan ◽  
Piotr Zmijewski
Keyword(s):  
Fluid Flow ◽  
Numerical Model ◽  
Distributed Memory ◽  
Heterogeneous Computing ◽  
Cloud Model ◽  
Memory Systems ◽  
Lagrangian Particles ◽  
Numerical Cloud Model

Abstract. A numerical cloud model with Lagrangian particles coupled to an Eulerian flow is adapted for distributed memory systems. Eulerian and Lagrangian calculations can be done in parallell on CPUs and GPUs, respectively. Scaling efficiency and the amount of parallelization of CPU and GPU calculations both exceed 50 % for up to 40 nodes. A sophisticated Lagrangian microphysics model slows down simulation by only 50 % compared to a simplistic bulk microphysics model, thanks to the use of GPUs. Overhead of communications between cluster nodes is mostly related to the pressure solver. Presented method of adaptation for computing clusters can be used in any numerical model with Lagrangian particles coupled to an Eulerian fluid flow.

Sign in / Sign up

Export Citation Format

Share Document