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 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 Broadening of Modeled Cloud Droplet Spectra Using Bin Microphysics in an Eulerian Spatial Domain

2018 ◽  
Vol 75 (11) ◽  
pp. 4005-4030 ◽  
Author(s):  
Hugh Morrison ◽  
Mikael Witte ◽  
George H. Bryan ◽  
Jerry Y. Harrington ◽  
Zachary J. Lebo
Keyword(s):  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Dynamical Models ◽  
Mixing Processes ◽  
Numerical Diffusion ◽  
Vertical Advection ◽  
1D Model ◽  
Bin Microphysics ◽  
Condensational Growth

Abstract This study investigates droplet size distribution (DSD) characteristics from condensational growth and transport in Eulerian dynamical models with bin microphysics. A hierarchy of modeling frameworks is utilized, including parcel, one-dimensional (1D), and three-dimensional large-eddy simulation (LES). The bin DSDs from the 1D model, which includes only vertical advection and condensational growth, are nearly as broad as those from the LES and in line with observed DSD widths for stratocumulus clouds. These DSDs are much broader than those from Lagrangian microphysical calculations within a parcel framework that serve as a numerical benchmark for the 1D tests. In contrast, the bin-modeled DSDs are similar to the Lagrangian microphysical benchmark for a rising parcel in which Eulerian transport is not considered. These results indicate that numerical diffusion associated with vertical advection is a key contributor to broadening DSDs in the 1D model and LES. This DSD broadening from vertical numerical diffusion is unphysical, in contrast to the physical mixing processes that previous studies have indicated broaden DSDs in real clouds. It is proposed that artificial DSD broadening from vertical numerical diffusion compensates for underrepresented horizontal variability and mixing of different droplet populations in typical LES configurations with bin microphysics, or the neglect of other mechanisms that broaden DSDs such as growth of giant cloud condensation nuclei. These results call into question the ability of Eulerian dynamical models with bin microphysics to investigate the physical mechanisms for DSD broadening, even though they may reasonably simulate overall DSD characteristics.

A study of shallow cumulus cloud droplet dispersion by large eddy simulations

2011 ◽  
Vol 25 (2) ◽  
pp. 166-175 ◽  
Author(s):  
Xiaofeng Wang ◽  
Huiwen Xue ◽  
Wen Fang ◽  
Guoguang Zheng
Keyword(s):  
Cloud Droplet ◽  
Large Eddy Simulations ◽  
Cumulus Cloud ◽  
Droplet Dispersion ◽  
Shallow Cumulus ◽  
Large Eddy

scholarly journals Broadening of Cloud Droplet Size Spectra by Stochastic Condensation: Effects of Mean Updraft Velocity and CCN Activation

2018 ◽  
Vol 75 (2) ◽  
pp. 451-467 ◽  
Author(s):  
Gaetano Sardina ◽  
Stéphane Poulain ◽  
Luca Brandt ◽  
Rodrigo Caballero
Keyword(s):  
Chemical Composition ◽  
Droplet Size ◽  
Isotropic Turbulence ◽  
Cloud Condensation Nuclei ◽  
Collision Probability ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Size Spectrum ◽  
Similar Reduction ◽  
Size Spectra

Abstract The authors study the condensational growth of cloud droplets in homogeneous isotropic turbulence by means of a large-eddy simulation (LES) approach. The authors investigate the role of a mean updraft velocity and of the chemical composition of the cloud condensation nuclei (CCN) on droplet growth. The results show that a mean constant updraft velocity superimposed onto a turbulent field reduces the broadening of the droplet size spectra induced by the turbulent fluctuations alone. Extending the authors’ previous results regarding stochastic condensation, the authors introduce a new theoretical estimation of the droplet size spectrum broadening that accounts for this updraft velocity effect. A similar reduction of the spectra broadening is observed when the droplets reach their critical size, which depends on the chemical composition of CCN. The analysis of the square of the droplet radius distribution, proportional to the droplet surface, shows that for large particles the distribution is purely Gaussian, while it becomes strongly non-Gaussian for smaller particles, with the left tail characterized by a peak around the haze activation radius. This kind of distribution can significantly affect the later stages of the droplet growth involving turbulent collisions, since the collision probability kernel depends on the droplet size, implying the need for new specific closure models to capture this effect.

scholarly journals Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization

2019 ◽  
Vol 12 (2) ◽  
pp. 1183-1206 ◽  
Author(s):  
Florian Ewald ◽  
Tobias Zinner ◽  
Tobias Kölling ◽  
Bernhard Mayer
Keyword(s):  
Remote Sensing ◽  
Solar Radiation ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Properties ◽  
Trade Wind ◽  
Small Scale ◽  
Passive Remote Sensing ◽  
Remote Sensing Techniques

Abstract. Convective clouds play an essential role for Earth's climate as well as for regional weather events since they have a large influence on the radiation budget and the water cycle. In particular, cloud albedo and the formation of precipitation are influenced by aerosol particles within clouds. In order to improve the understanding of processes from aerosol activation, from cloud droplet growth to changes in cloud radiative properties, remote sensing techniques become more and more important. While passive retrievals for spaceborne observations have become sophisticated and commonplace for inferring cloud optical thickness and droplet size from cloud tops, profiles of droplet size have remained largely uncharted territory for passive remote sensing. In principle they could be derived from observations of cloud sides, but faced with the small-scale heterogeneity of cloud sides, “classical” passive remote sensing techniques are rendered inappropriate. In this work the feasibility is demonstrated to gain new insights into the vertical evolution of cloud droplet effective radius by using reflected solar radiation from cloud sides. Central aspect of this work on its path to a working cloud side retrieval is the analysis of the impact unknown cloud surface geometry has on effective radius retrievals. This study examines the sensitivity of reflected solar radiation to cloud droplet size, using extensive 3-D radiative transfer calculations on the basis of realistic droplet size resolving cloud simulations. Furthermore, it explores a further technique to resolve ambiguities caused by illumination and cloud geometry by considering the surroundings of each pixel. Based on these findings, a statistical approach is used to provide an effective radius retrieval. This statistical effective radius retrieval is focused on the liquid part of convective water clouds, e.g., cumulus mediocris, cumulus congestus, and trade-wind cumulus, which exhibit well-developed cloud sides. Finally, the developed retrieval is tested using known and unknown cloud side scenes to analyze its performance.

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 Cloud droplet growth in shallow cumulus clouds considering 1-D and 3-D thermal radiative effects

2019 ◽  
Vol 19 (9) ◽  
pp. 6295-6313 ◽  
Author(s):  
Carolin Klinger ◽  
Graham Feingold ◽  
Takanobu Yamaguchi
Keyword(s):  
Thermal Radiation ◽  
Three Dimensional ◽  
Cloud Droplet ◽  
Large Eddy Simulations ◽  
Droplet Growth ◽  
Radiative Effects ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Large Eddy ◽  
Thermal Cooling

Abstract. The effect of 1-D and 3-D thermal radiation on cloud droplet growth in shallow cumulus clouds is investigated using large eddy simulations with size-resolved cloud microphysics. A two-step approach is used for separating microphysical effects from dynamical feedbacks. In step one, an offline parcel model is used to describe the onset of rain. The growth of cloud droplets to raindrops is simulated with bin-resolved microphysics along previously recorded Lagrangian trajectories. It is shown that thermal heating and cooling rates can enhance droplet growth and raindrop production. Droplets grow to larger size bins in the 10–30 µm radius range. The main effect in terms of raindrop production arises from recirculating parcels, where a small number of droplets are exposed to strong thermal cooling at cloud edge. These recirculating parcels, comprising about 6 %–7 % of all parcels investigated, make up 45 % of the rain for the no-radiation simulation and up to 60 % when 3-D radiative effects are considered. The effect of 3-D thermal radiation on rain production is stronger than that of 1-D thermal radiation. Three-dimensional thermal radiation can enhance the rain amount up to 40 % compared to standard droplet growth without radiative effects in this idealized framework. In the second stage, fully coupled large eddy simulations show that dynamical effects are stronger than microphysical effects, as far as the production of rain is concerned. Three-dimensional thermal radiative effects again exceed one-dimensional thermal radiative effects. Small amounts of rain are produced in more clouds (over a larger area of the domain) when thermal radiation is applied to microphysics. The dynamical feedback is shown to be an enhanced cloud circulation with stronger subsiding shells at the cloud edges due to thermal cooling and stronger updraft velocities in the cloud center. It is shown that an evaporation–circulation feedback reduces the amount of rain produced in simulations where 3-D thermal radiation is applied to microphysics and dynamics, in comparison to where 3-D thermal radiation is only applied to dynamics.

scholarly journals Progress on Predicting the Breadth of Droplet Size Distributions Observed in Small Cumuli

2011 ◽  
Vol 68 (12) ◽  
pp. 2921-2929 ◽  
Author(s):  
Jennifer L. Bewley ◽  
Sonia Lasher-Trapp
Keyword(s):  
Droplet Size ◽  
Cloud Condensation Nuclei ◽  
Droplet Diameter ◽  
Droplet Size Distribution ◽  
Trade Wind ◽  
Droplet Growth ◽  
Size Distributions ◽  
Model Resolution ◽  
Modeling Framework ◽  
Droplet Size Distributions

Abstract A modeling framework representing variations in droplet growth by condensation, resulting from different saturation histories experienced as a result of entrainment and mixing, is used to predict the breadth of droplet size distributions observed at different altitudes within trade wind cumuli observed on 10 December 2004 during the Rain in Cumulus over the Ocean (RICO) field campaign. The predicted droplet size distributions are as broad as those observed, contain similar numbers of droplets, and are generally in better agreement with the observations when some degree of inhomogeneous droplet evaporation is considered, allowing activation of newly entrained cloud condensation nuclei. The variability of the droplet growth histories, resulting primarily from entrainment, appears to explain the magnitude of the observed droplet size distribution widths, without representation of other broadening mechanisms. Additional work is needed, however, as the predicted mean droplet diameter is too large relative to the observations and likely results from the model resolution limiting dilution of the simulated cloud.

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.

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