scholarly journals Adaptive method of lines for multi-component aerosol condensational growth and CCN activation

2011 ◽  
Vol 4 (1) ◽  
pp. 15-31 ◽  
Author(s):  
S. Arabas ◽  
H. Pawlowska
Keyword(s):  
Method Of Lines ◽  
Cloud Droplet ◽  
Adaptive Method ◽  
Size Spectrum ◽  
Grid Refinement ◽  
Cloud Droplets ◽  
Adaptive Grid Refinement ◽  
Refinement Procedure ◽  
Set Up ◽  
Condensational Growth

Abstract. The process of formation of cloud droplets on an ensemble of aerosol particles is modelled by numerous investigators using the method of lines (MOL). The method involves discretisation of the aerosol size spectrum into bins whose positions evolve with time. One of the drawbacks of the method is its poor representation of the aerosol spectrum shape in the region between the unactivated aerosol mode and the activated droplet mode. An adaptive grid refinement procedure is introduced. The procedure splits any overly wide bins into several narrower ones during integration. The number of new bins added is a function of particle concentration in the bin being split. Application of the grid refinement procedure results in suppression of the sensitivity of the computed cloud droplet spectrum characteristics such as droplet number concentration or effective radius to the initial grid choice. A model of droplet formation on multi-component aerosol is formulated for the purpose of the study. Model formulation includes explicit treatment of the droplet temperature evolution. Several examples of the model set-up are used to demonstrate model capabilities. Model results are compared to those without adaptivity. A C++ implementation of the model is available as an electronic supplement of the paper.

scholarly journals Adaptive method of lines for multi-component aerosol condensational growth and cloud droplet activation

2010 ◽  
Vol 3 (3) ◽  
pp. 1271-1315
Author(s):  
S. Arabas ◽  
H. Pawlowska
Keyword(s):  
Method Of Lines ◽  
Cloud Droplet ◽  
Adaptive Method ◽  
Size Spectrum ◽  
Model Formulation ◽  
Cloud Droplets ◽  
The Method Of Lines ◽  
Model Set ◽  
Set Up ◽  
Condensational Growth

Abstract. The process of formation of cloud droplets on an ensemble of aerosol particles is modelled by numerous investigators using the method of lines (MOL). The method involves discretization of the aerosol size spectrum into bins whose position and width evolve with time. One of the drawbacks of the method is its poor representation of the aerosol spectrum shape in the region between the unactivated aerosol mode and the activated cloud-droplet mode. An adaptive spectrum refinement procedure that improves the performance of the method is introduced and tested. A model of drop formation on multi-component aerosol is formulated for the purpose of the study. Model formulation includes explicit treatment of the drop temperature evolution. Several examples of the model set-up are used to demonstrate model capabilities. Model results are compared to those without adaptivity, and are compared to the Twomey's formul\\ae. A C++ implementation of the model is available as an electronic supplement of the paper.

scholarly journals Large-Eddy Simulations of Trade Wind Cumuli Using Particle-Based Microphysics with Monte Carlo Coalescence

2013 ◽  
Vol 70 (9) ◽  
pp. 2768-2777 ◽  
Author(s):  
Sylwester Arabas ◽  
Shin-ichiro Shima
Keyword(s):  
Monte Carlo ◽  
Droplet Size ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Large Eddy Simulations ◽  
Trade Wind ◽  
Type Model ◽  
Size Spectrum ◽  
Large Eddy ◽  
Condensational Growth

Abstract A series of simulations employing the superdroplet method (SDM) for representing aerosol, cloud, and rain microphysics in large-eddy simulations (LES) is discussed. The particle-based formulation treats all particles in the same way, subjecting them to condensational growth and evaporation, transport of the particles by the flow, gravitational settling, and collisional growth. SDM features a Monte Carlo–type numerical scheme for representing the collision and coalescence process. All processes combined cover representation of cloud condensation nuclei (CCN) activation, drizzle formation by autoconversion, accretion of cloud droplets, self-collection of raindrops, and precipitation, including aerosol wet deposition. The model setup used in the study is based on observations from the Rain in Cumulus over the Ocean (RICO) field project. Cloud and rain droplet size spectra obtained in the simulations are discussed in context of previously published analyses of aircraft observations carried out during RICO. The analysis covers height-resolved statistics of simulated cloud microphysical parameters such as droplet number concentration, effective radius, and parameters describing the width of the cloud droplet size spectrum. A reasonable agreement with measurements is found for several of the discussed parameters. The sensitivity of the results to the grid resolution of the LES, as well as to the sampling density of the probabilistic Monte Carlo–type model, is explored.

scholarly journals Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

2017 ◽  
Author(s):  
Fan Yang ◽  
Pavlos Kollias ◽  
Raymond A. Shaw ◽  
Andrew M. Vogelmann
Keyword(s):  
Droplet Size ◽  
Dynamic Models ◽  
Ostwald Ripening ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Diffusional Growth ◽  
Cloud Droplets ◽  
Cloud Properties ◽  
Condensational Growth

Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and lifetime, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a Lagrangian bin-microphysics cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, sub-micrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with Korolev (1995). The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are: (1) droplets form on polydisperse aerosols of varying hygroscopicity and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in-situ measurements and 3-D dynamic models.

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 Regional New Particle Formation as Modulators of Cloud Condensation Nuclei and Cloud Droplet Number in the Eastern Mediterranean

2018 ◽  
Author(s):  
Panayiotis Kalkavouras ◽  
Aikaterini Bougiatioti ◽  
Nikos Kalivitis ◽  
Maria Tombrou ◽  
Athanasios Nenes ◽  
...  
Keyword(s):  
Gas Phase ◽  
Particle Number ◽  
Eastern Mediterranean ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Significant Fraction ◽  
Size Distributions ◽  
Condensation Nuclei ◽  
Cloud Droplets ◽  
Condensational Growth

Abstract. A significant fraction of atmospheric particles that serve as cloud condensation nuclei (CCN), and furthermore as cloud droplets are thought to originate from the condensational growth of new particles formed from the gas phase. Here, particle number size distributions (

scholarly journals Impact of hygroscopic CCN and turbulence on cloud droplet growth: A parcel-DNS approach

2019 ◽  
Author(s):  
Sisi Chen ◽  
Lulin Xue ◽  
Man-Kong Yau
Keyword(s):  
Cloud Condensation Nuclei ◽  
Hybrid Approach ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Relative Dispersion ◽  
Droplet Growth ◽  
Cloud Droplets ◽  
Cloud Development ◽  
Condensational Growth ◽  
Opposing Trend

Abstract. This paper investigates the relative importance of turbulence, hygroscopicity of cloud condensation nuclei (CCN), and aerosol loading on early cloud development. A parcel-DNS hybrid approach is developed to seamlessly simulate the evolution of cloud droplets in warm clouds. The results show that turbulence and CCN hygroscopicity have a dominant effect on the formation of large droplets. When CCN hygroscopicity is considered, condensational growth has a strong effect in the first minute, providing sufficient collector droplets. In the meantime, turbulence effectively accelerates the collisions among the collector droplets and the small droplets and continues to broaden the droplet size distribution (DSD). In contrast, seeding of extra aerosols modulates the growth of small droplets by inhibiting condensational growth while the growth of large droplets remains unaffected, resulting in a similar tail of the DSD. Overall, seeding reduces the LWC and effective radius but increases the relative dispersion. This opposing trend of the bulk properties suggests that the traditional Kessler-type or Sundqvist-type autoconversion parameterizations which mainly depend on the LWC or mean radius might not represent the drizzle formation process well. Properties related to the width or the shape of the DSD are also needed, suggesting that the Berry-and-Reinhardt scheme is conceptually better.

scholarly journals Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

2018 ◽  
Vol 18 (10) ◽  
pp. 7313-7328 ◽  
Author(s):  
Fan Yang ◽  
Pavlos Kollias ◽  
Raymond A. Shaw ◽  
Andrew M. Vogelmann
Keyword(s):  
Droplet Size ◽  
Dynamic Models ◽  
Ostwald Ripening ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Diffusional Growth ◽  
Cloud Droplets ◽  
Cloud Properties ◽  
Condensational Growth

Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models.

scholarly journals Cloud-droplet growth due to supersaturation fluctuations in stratiform clouds

2018 ◽  
Author(s):  
Xiang-Yu Li ◽  
Gunilla Svensson ◽  
Axel Brandenburg ◽  
Nils E. L. Haugen
Keyword(s):  
Reynolds Number ◽  
Size Distribution ◽  
Cloud Droplet ◽  
Energy Dissipation Rate ◽  
Droplet Growth ◽  
Size Distributions ◽  
Cloud Droplets ◽  
Stratiform Clouds ◽  
Water Vapor Mixing Ratio ◽  
Condensational Growth

Abstract. Condensational growth of cloud droplets due to supersaturation fluctuations is investigated by solving the hydrodynamic and thermodynamic equations using direct numerical simulations with droplets being modeled as Lagrangian particles. We find that the width of droplet size distributions increases with time, which is contrary to the classical theory without supersaturation fluctuations, where condensational growth leads to progressively narrower size distributions. Nevertheless, in agreement with earlier Lagrangian stochastic models of the condensational growth, the standard deviation of the surface area of droplets increases as t1/2. Also, we numerically confirm that the time evolution of the size distribution depends strongly on the Reynolds number and only weakly on the mean energy dissipation rate. This is shown to be due to the fact that temperature fluctuations and water vapor mixing ratio fluctuations increases with increasing Reynolds number, therefore the resulting supersaturation fluctuations are enhanced with increasing Reynolds number. Our simulations may explain the broadening of the size distribution in stratiform clouds qualitatively, where the updraft velocity is almost zero.

scholarly journals On numerical broadening of particle size spectra: a condensational growth study using PyMPDATA 1.0

2021 ◽  
Author(s):  
Michael Olesik ◽  
Sylwester Arabas ◽  
Jakub Banaśkiewicz ◽  
Piotr Bartman ◽  
Manuel Baumgartner ◽  
...  
Keyword(s):  
Particle Size ◽  
Computational Cost ◽  
Donor Cell ◽  
Diffusion Problem ◽  
Size Spectrum ◽  
Test Case ◽  
Diffusional Growth ◽  
Double Pass ◽  
Cloud Droplets ◽  
Condensational Growth

Abstract. The work discusses the diffusional growth in particulate systems such as atmospheric clouds. It focuses on the Eulerian modeling approach in which the evolution of the probability density function describing the particle size spectrum is carried out using a fixed-bin discretization. The numerical diffusion problem inherent to the employment of the fixed-bin discretization is scrutinized. The work focuses on the applications of MPDATA family of numerical schemes. Several MPDATA variants are explored including: infinite-gauge, non-oscillatory, third-order-terms and recursive antidiffusive correction (double pass donor cell, DPDC) options. Methodology for handling coordinate transformations associated with both particle size distribution variable choice and numerical grid layout are expounded. The study uses PyMPDATA – a new open-source Python implementation of MPDATA. Analysis of the performance of the scheme for different discretization parameters and different settings of the algorithm is performed using an analytically solvable test case pertinent to condensational growth of cloud droplets. The analysis covers spatial and temporal convergence, computational cost, conservativeness and quantification of the numerical broadening of the particle size spectrum. Presented results demonstrate that, for the problem considered, even a tenfold decrease of the spurious numerical spectral broadening can be obtained by a proper choice of the MPDATA variant (maintaining the same spatial and temporal resolution).

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