scholarly journals Impact of high- and low-vorticity turbulence on cloud–environment mixing and cloud microphysics processes

2021 ◽  
Vol 21 (16) ◽  
pp. 12317-12329
Author(s):  
Bipin Kumar ◽  
Rahul Ranjan ◽  
Man-Kong Yau ◽  
Sudarsan Bera ◽  
Suryachandra A. Rao
Keyword(s):  
Turbulent Flows ◽  
Droplet Size ◽  
Turbulent Mixing ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Size Spectrum ◽  
Turbulent Structures ◽  
Cloud Droplets ◽  
The Impact ◽  
Entrainment Mixing

Abstract. Turbulent mixing of dry air affects the evolution of the cloud droplet size spectrum via various mechanisms. In a turbulent cloud, high- and low-vorticity regions coexist, and inertial clustering of cloud droplets can occur in low-vorticity regions. The nonuniformity in the spatial distribution of the size and in the number of droplets, variable vertical velocity in vortical turbulent structures, and dilution by entrainment/mixing may result in spatial supersaturation variability, which affects the evolution of the cloud droplet size spectrum via condensation and evaporation processes. To untangle the processes involved in mixing phenomena, a 3D direct numerical simulation of turbulent mixing followed by droplet evaporation/condensation in a submeter-sized cubed domain consisting of a large number of droplets was performed in this study. The analysis focused on the thermodynamic and microphysical characteristics of the droplets and the flow in high- and low-vorticity regions. The impact of vorticity generation in turbulent flows on mixing and cloud microphysics is illustrated.

scholarly journals Impact of high and low vorticity turbulence on cloud environment mixing and cloud microphysics processes

2021 ◽  
Author(s):  
Bipin Kumar ◽  
Rahul Ranjan ◽  
Man-Kong Yau ◽  
Sudarsan Bera ◽  
Suryachadra A. Rao
Keyword(s):  
Turbulent Flows ◽  
Droplet Size ◽  
Turbulent Mixing ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Size Spectrum ◽  
Turbulent Structures ◽  
Cloud Droplets ◽  
Vorticity Production ◽  
The Impact

Abstract. Turbulent mixing of dry air affects evolution of cloud droplet size spectrum through various mechanisms. In a turbulent cloud, high and low vorticity regions coexist and inertial clustering of cloud droplets can occur in a low vorticity region. The non-uniformity in spatial distribution of size and number of droplets, variable vertical velocity in vortical turbulent structures, and dilution by entrainment/mixing may result in spatial supersaturation variability, which affects the evolution of the cloud droplet size spectrum by condensation and evaporation processes. To untangle the processes involved in mixing phenomena, a direct numerical simulation (DNS) of turbulent-mixing followed by droplet evaporation/condensation in a submeter-cubed-sized domain with a large number of droplets is performed in this study. Analysis focused on the thermodynamic and microphysical characteristics of the droplets and flow in high and low vorticity regions. The impact of vorticity production in turbulent flows on mixing and cloud microphysics is illustrated.

scholarly journals Broadening of Cloud Droplet Spectra through Eddy Hopping: Turbulent Entraining Parcel Simulations

2018 ◽  
Vol 75 (10) ◽  
pp. 3365-3379 ◽  
Author(s):  
Gustavo C. Abade ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska
Keyword(s):  
Droplet Size ◽  
Turbulent Mixing ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Droplet Growth ◽  
Size Spectrum ◽  
Entrainment Rate ◽  
The Mean ◽  
The Impact

This paper discusses the effects of cloud turbulence, turbulent entrainment, and entrained cloud condensation nuclei (CCN) activation on the evolution of the cloud droplet size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events modeled as a random process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet activation and growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate, CCN concentration, and the mean fraction of environmental air entrained in an event are all specified as independent external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. These are either unactivated CCN or cloud droplets that grow from activated CCN. The model accounts for the addition of environmental CCN into the cloud by entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using the classical linear relaxation to the mean model. We show that turbulence plays an important role in aiding entrained CCN to activate, and thus broadening the droplet size distribution. These findings are consistent with previous large-eddy simulations (LESs) that consider the impact of variable droplet growth histories on the droplet size spectra in small cumuli. The scheme developed in this work is ready to be used as a stochastic subgrid-scale scheme in LESs of natural clouds.

scholarly journals Monte Carlo-based subgrid parameterization of vertical velocity and stratiform cloud microphysics in ECHAM5.5-HAM2

2013 ◽  
Vol 13 (2) ◽  
pp. 5477-5507
Author(s):  
J. Tonttila ◽  
P. Räisänen ◽  
H. Järvinen
Keyword(s):  
Monte Carlo ◽  
Vertical Velocity ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Radiative Effects ◽  
Cloud Droplets ◽  
Microphysical Properties ◽  
Cloud Radiative Effects ◽  
Cloud Activation ◽  
The Impact

Abstract. A new method for parameterizing the subgrid variations of vertical velocity and cloud droplet number concentration (CDNC) is presented for GCMs. These parameterizations build on top of existing parameterizations that create stochastic subgrid cloud columns inside the GCM grid-cells, which can be employed by the Monte Carlo independent column approximation approach for radiative transfer. The new model version adds a description for vertical velocity in individual subgrid columns, which can be used to compute cloud activation and the subgrid distribution of the number of cloud droplets explicitly. This provides a consistent way for simulating the cloud radiative effects with two-moment cloud microphysical properties defined in subgrid-scale. The primary impact of the new parameterizations is to decrease the CDNC over polluted continents, while over the oceans the impact is smaller. This promotes changes in the global distribution of the cloud radiative effects and might thus have implications on model estimation of the indirect radiative effect of aerosols.

scholarly journals Comparisons of CCN with Supercooled Clouds

2010 ◽  
Vol 67 (9) ◽  
pp. 3006-3018 ◽  
Author(s):  
James G. Hudson ◽  
Stephen Noble ◽  
Vandana Jha
Keyword(s):  
Droplet Size ◽  
Cloud Condensation Nuclei ◽  
Correlation Coefficients ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Cloud Base ◽  
Cloud Droplets ◽  
Lower Cloud ◽  
Droplet Sizes

Abstract More than 140 supercooled clouds were compared with corresponding out-of-cloud cloud condensation nuclei (CCN) measurements. In spite of significant differences in altitude, temperature, distances from cloud base, updraft velocity (W), entrainment, and so on, the correlation coefficients (R) between droplet and CCN concentrations were substantial although not as high as those obtained in warm clouds with less variability of nonaerosol influences. CCN at slightly lower altitudes than the clouds had higher R values than CCN measured at the same altitude. Ice particle concentrations appeared to reduce droplet concentrations and reduce R between CCN and droplet concentrations, but only above 6-km altitude and for temperatures below −20°C. Although higher CCN concentrations generally resulted in higher droplet concentrations, increases in droplet concentrations were generally less than the increases in CCN concentrations. This was apparently due to the expected lower cloud supersaturations (S) when CCN concentrations are higher as was usually the case at lower altitudes. Cloud supersaturations showed more variability at higher altitudes and often very high values at higher altitudes. The use of liquid water content rather than droplet concentrations for cloud threshold resulted in higher R between CCN and droplet concentrations. The same R pattern for cumulative droplet–CCN concentrations as a function of threshold droplet sizes as that recently uncovered in warm clouds was found. This showed R changing rapidly from positive values when all cloud droplets were considered to negative values for slightly larger droplet size thresholds. After reaching a maximum negative value at intermediate droplet sizes, R then reversed direction to smaller negative or even positive values for larger cloud droplet size thresholds. This R pattern of CCN concentrations versus cumulative droplet concentrations for increasing size thresholds is consistent with adiabatic model predictions and thus suggests even greater CCN influence on cloud microphysics.

DROPLET FEEDBACK ON VAPOR IN A WARM CLOUD

2009 ◽  
Vol 23 (28n29) ◽  
pp. 5434-5443 ◽  
Author(s):  
ANTONIO CELANI ◽  
ANDREA MAZZINO ◽  
MARCO TIZZI
Keyword(s):  
Numerical Simulations ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Direct Numerical Simulations ◽  
Cloud Droplets ◽  
Size Spectra ◽  
New Model ◽  
Warm Cloud ◽  
Local Reduction ◽  
The One

A new model to study the effect of turbulence on the cloud droplets in the condensation phase is proposed and its behavior investigated by direct numerical simulations. The model is a generalization of the one by Celani, Mazzino, Tizzi, New J. Phys.10, 075021 (2008), where the droplet feedback on vapor is now explicitly taken into account. Physically, it amounts to considering the fact that when a cloud droplet increases its size, vapor is subtracted from the ambient with the net result of a local reduction in the supersaturation field. It is shown how this effect plays to reduce the broadening of droplet size spectra in the condensation stage and thus to produce results in closer agreement with observations.

Broadening of the Cloud Droplet Size Distribution due to Thermal Radiative Cooling: Turbulent Parcel Simulations

2020 ◽  
Vol 77 (6) ◽  
pp. 1993-2010
Author(s):  
Mares Barekzai ◽  
Bernhard Mayer
Keyword(s):  
Thermal Radiation ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Growth Efficiency ◽  
Droplet Growth ◽  
Radiative Cooling ◽  
Radiative Effect ◽  
Diffusional Growth ◽  
The Impact

Abstract Despite impressive advances in rain forecasts over the past decades, our understanding of rain formation on a microphysical scale is still poor. Droplet growth initially occurs through diffusion and, for sufficiently large radii, through the collision of droplets. However, there is no consensus on the mechanism to bridge the condensation coalescence bottleneck. We extend the analysis of prior methods by including radiatively enhanced diffusional growth (RAD) to a Markovian turbulence parameterization. This addition increases the diffusional growth efficiency by allowing for emission and absorption of thermal radiation. Specifically, we quantify an upper estimate for the radiative effect by focusing on droplets close to the cloud boundary. The strength of this simple model is that it determines growth-rate dependencies on a number of parameters, like updraft speed and the radiative effect, in a deterministic way. Realistic calculations with a cloud-resolving model are sensitive to parameter changes, which may cause completely different cloud realizations and thus it requires considerable computational power to obtain statistically significant results. The simulations suggest that the addition of radiative cooling can lead to a doubling of the droplet size standard deviation. However, the magnitude of the increase depends strongly on the broadening established by turbulence, due to an increase in the maximum droplet size, which accelerates the production of drizzle. Furthermore, the broadening caused by the combination of turbulence and thermal radiation is largest for small updrafts and the impact of radiation increases with time until it becomes dominant for slow synoptic updrafts.

Lagrangian stochastic microphysics at unresolved scales in turbulent cloud simulations

2020 ◽  
Author(s):  
Gustavo Abade ◽  
Marta Waclawczyk ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska
Keyword(s):  
Droplet Size ◽  
Cloud Condensation Nuclei ◽  
Droplet Size Distribution ◽  
Cloud Microphysics ◽  
Cloud Droplets ◽  
Adiabatic Cooling ◽  
Subgrid Scales ◽  
The Mean ◽  
Microphysical Processes ◽  
Droplet Size Distributions

<p>Turbulent clouds are challenging to model and simulate due to uncertainties in microphysical processes occurring at unresolved subgrid scales (SGS). These processes include the transport of cloud particles, supersaturation fluctuations, turbulent mixing, and the resulting stochastic droplet activation and growth by condensation. In this work, we apply two different Lagrangian stochastic schemes to model SGS cloud microphysics. Collision and coalescence of droplets are not considered. Cloud droplets and unactivated cloud condensation nuclei (CCN) are described by Lagrangian particles (superdroplets). The first microphysical scheme directly models the supersaturation fluctuations experienced by each Lagrangian superdroplet as it moves with the air flow. Supersaturation fluctuations are driven by turbulent fluctuations of the droplet vertical velocity through the adiabatic cooling/warming effect. The second, more elaborate scheme uses both temperature and vapor mixing ratio as stochastic attributes attached to each superdroplet. It is based on the probability density function formalism that provides a consistent Eulerian-Lagrangian formulation of scalar transport in a turbulent flow. Both stochastic microphysical schemes are tested in a synthetic turbulent-like cloud flow that mimics a stratocumulus topped boundary layer. It is shown that SGS turbulence plays a key role in broadening the droplet-size distribution towards larger sizes. Also, the feedback on water vapor of stochastically activated droplets buffers the variations of the mean supersaturation driven the resolved transport. This extends the distance over which entrained CNN are activated inside the cloud layer and produces multimodal droplet-size distributions.</p>

scholarly journals Conditions for super-adiabatic droplet growth after entrainment mixing

2016 ◽  
Vol 16 (14) ◽  
pp. 9421-9433 ◽  
Author(s):  
Fan Yang ◽  
Raymond Shaw ◽  
Huiwen Xue
Keyword(s):  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Critical Height ◽  
Growth Region ◽  
Cloud Droplets ◽  
Environmental Air ◽  
Bin Microphysics ◽  
Entrainment Mixing

Abstract. Cloud droplet response to entrainment and mixing between a cloud and its environment is considered, accounting for subsequent droplet growth during adiabatic ascent following a mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction to be predicted from the mixing fraction and from the temperature and humidity for both the cloud and environment. It is derived for the limit of homogeneous mixing. The expression leads to a critical height above the mixing level: at the critical height the cloud droplet radius is the same for both mixed and unmixed parcels, and the critical height is independent of the updraft velocity and mixing fraction. Cloud droplets in a mixed parcel are larger than in an unmixed parcel above the critical height, which we refer to as the “super-adiabatic” growth region. Analytical results are confirmed with a bin microphysics cloud model. Using the model, we explore the effects of updraft velocity, aerosol source in the environmental air, and polydisperse cloud droplets. Results show that the mixed parcel is more likely to reach the super-adiabatic growth region when the environmental air is humid and clean. It is also confirmed that the analytical predictions are matched by the volume-mean cloud droplet radius for polydisperse size distributions. The findings have implications for the origin of large cloud droplets that may contribute to onset of collision–coalescence in warm clouds.

Chaotic stirring in quasi-turbulent flows

2007 ◽  
Vol 365 (1861) ◽  
pp. 3061-3084 ◽  
Author(s):  
Francois Lekien ◽  
Chad Coulliette
Keyword(s):  
Turbulent Flows ◽  
Turbulent Mixing ◽  
Pollution Source ◽  
Laminar Flows ◽  
Coastal Pollution ◽  
Monterey Bay ◽  
Thin Filaments ◽  
Isotropic Mixing ◽  
Recent Developments ◽  
The Impact

Transport in laminar flows is governed by chaotic stirring and striation in long thin filaments. In turbulent flows, isotropic mixing dominates and tracers behave like stochastic variables. In this paper, we investigate the quasi-turbulent, intermediate regime where both chaotic stirring and turbulent mixing coexist. In these flows, the most common in nature, aperiodic Lagrangian coherent structures (LCSs) delineate particle transport and chaotic stirring. We review the recent developments in LCS theory and apply these techniques to measured surface currents in Monterey Bay, California. In the bay, LCSs can be used to optimize the release of drifting buoys or to minimize the impact of a coastal pollution source.

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