Lagrangian stochastic microphysics at unresolved scales in turbulent cloud simulations

Author(s):  
Gustavo Abade ◽  
Marta Waclawczyk ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska

<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>

2018 ◽  
Vol 75 (10) ◽  
pp. 3365-3379 ◽  
Author(s):  
Gustavo C. Abade ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska

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.


2011 ◽  
Vol 68 (12) ◽  
pp. 2921-2929 ◽  
Author(s):  
Jennifer L. Bewley ◽  
Sonia Lasher-Trapp

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.


2019 ◽  
Author(s):  
Steven K. Krueger

Abstract. In a laboratory cloud chamber that is undergoing Rayleigh-Bénard convection, supersaturation is produced by isobaric mixing. When aerosols (cloud condensation nuclei) are injected into the chamber at a constant rate, and the rate of droplet activation is balanced by the rate of droplet loss, an equilibrium droplet size distribution (DSD) can be achieved. We derived analytic equilibrium DSDs and PDFs of droplet radius and squared radius for conditions that could occur in such a turbulent cloud chamber when there is uniform supersaturation. The loss rate due to fall out that we used assumes that (1) the droplets are well-mixed by turbulence, (2) when a droplet becomes sufficiently close to the lower boundary, the droplet’s terminal velocity determines its probability of fall out per unit time, and (3) a droplet’s terminal velocity follows Stokes’ Law (so it is proportional to its radius squared). Given the chamber height, the analytic PDF is determined by the mean supersaturation alone. From the expression for the PDF of the radius, we obtained analytic expressions for the first five moments of the radius, including moments for truncated DSDs. We used statistics from a set of measured DSDs to check for consistency with the analytic PDF. We found consistency between the theoretical and measured moments, but only when the truncation radius of the measured DSDs was taken into account. This consistency allows us to infer the mean supersaturations that would produce the measured PDFs in the absence of supersaturation fluctuations. We found that accounting for the truncation radius of the measured DSDs is particularly important when comparing the theoretical and measured relative dispersions of the droplet radius. We also included some additional quantities derived from the analytic DSD: droplet sedimentation flux, precipitation flux, and condensation rate.


2014 ◽  
Vol 14 (14) ◽  
pp. 7573-7583 ◽  
Author(s):  
P. Reutter ◽  
J. Trentmann ◽  
A. Seifert ◽  
P. Neis ◽  
H. Su ◽  
...  

Abstract. Dynamical and microphysical processes in pyroconvective clouds in mid-latitude conditions are investigated using idealized three-dimensional simulations with the Active Tracer High resolution Atmospheric Model (ATHAM). A state-of-the-art two-moment microphysical scheme building upon a realistic parameterization of cloud condensation nuclei (CCN) activation has been implemented in order to study the influence of aerosol concentration on cloud development. The results show that aerosol concentration influences the formation of precipitation. For low aerosol concentrations (NCN = 200 cm−3), rain droplets are rapidly formed by autoconversion of cloud droplets. This also triggers the formation of large graupel and hail particles, resulting in an early onset of precipitation. With increasing aerosol concentration (NCN = 1000 cm−3 and NCN = 20 000 cm−3) the formation of rain droplets is delayed due to more but smaller cloud droplets. Therefore, the formation of ice crystals and snowflakes becomes more important for the eventual formation of graupel and hail, which is delayed at higher aerosol concentrations. This results in a delay of the onset of precipitation and a reduction of its intensity with increasing aerosol concentration. This study is the first detailed investigation of the interaction between cloud microphysics and the dynamics of a pyroconvective cloud using the combination of a high-resolution atmospheric model and a detailed microphysical scheme.


2010 ◽  
Vol 67 (9) ◽  
pp. 3006-3018 ◽  
Author(s):  
James G. Hudson ◽  
Stephen Noble ◽  
Vandana Jha

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.


2020 ◽  
Vol 20 (13) ◽  
pp. 7895-7909
Author(s):  
Steven K. Krueger

Abstract. In a laboratory cloud chamber that is undergoing Rayleigh–Bénard convection, supersaturation is produced by isobaric mixing. When aerosols (cloud condensation nuclei) are injected into the chamber at a constant rate, and the rate of droplet activation is balanced by the rate of droplet loss, an equilibrium droplet size distribution (DSD) can be achieved. We derived analytic equilibrium DSDs and probability density functions (PDFs) of droplet radius and squared radius for conditions that could occur in such a turbulent cloud chamber when there is uniform supersaturation. We neglected the effects of droplet curvature and solute on the droplet growth rate. The loss rate due to fallout that we used assumes that (1) the droplets are well-mixed by turbulence, (2) when a droplet becomes sufficiently close to the lower boundary, the droplet's terminal velocity determines its probability of fallout per unit time, and (3) a droplet's terminal velocity follows Stokes' law (so it is proportional to its radius squared). Given the chamber height, the analytic PDF is determined by the mean supersaturation alone. From the expression for the PDF of the radius, we obtained analytic expressions for the first five moments of the radius, including moments for truncated DSDs. We used statistics from a set of measured DSDs to check for consistency with the analytic PDF. We found consistency between the theoretical and measured moments, but only when the truncation radius of the measured DSDs was taken into account. This consistency allows us to infer the mean supersaturations that would produce the measured PDFs in the absence of supersaturation fluctuations. We found that accounting for the truncation radius of the measured DSDs is particularly important when comparing the theoretical and measured relative dispersions of the droplet radius. We also included some additional quantities derived from the analytic DSD: droplet sedimentation flux, precipitation flux, and condensation rate.


2019 ◽  
Author(s):  
Jiarong Li ◽  
Chao Zhu ◽  
Hui Chen ◽  
Defeng Zhao ◽  
Likun Xue ◽  
...  

Abstract. The influence of aerosols, both natural and anthropogenic, remains a major area of uncertainty when predicting the properties and behaviour of clouds and their influence on climate. In an attempt to understand better the microphysical properties of cloud droplets, the aerosol-cloud interactions, and the corresponding climate effect during cloud life cycles in the North China Plain, an intensive observation took place from 17 June to 30 July 2018 at the summit of Mt. Tai. Cloud microphysical parameters were monitored simultaneously with number concentrations of cloud condensation nuclei (NCCN) at different supersaturations, PM2.5 mass concentrations, particle size distributions and meteorological parameters. Number concentrations of cloud droplets (NC), liquid water content (LWC) and effective radius of cloud droplets (reff) show large variations among 40 cloud events observed during the campaign. Perturbations of aerosols will significantly increase the NC of cloud droplets and shift cloud droplets toward smaller size ranges. Clouds in clean days are more susceptible to the change in concentrations of particle number (NP). LWC shows positive correlation with reff. As NC increases, reff changes from a trimodal distribution to a unimodal distribution. By assuming a cloud thickness of 100 m, we find that the albedo can increase 36.4 % if the cloud gets to be disturbed by aerosols. This may induce a cooling effect on the local climate system. Our results contribute more information about regional cloud microphysics and will help to reduce the uncertainties in climate models when predicting climate responses to cloud-aerosol interactions.


2019 ◽  
Vol 19 (11) ◽  
pp. 7839-7857
Author(s):  
Lianet Hernández Pardo ◽  
Luiz Augusto Toledo Machado ◽  
Micael Amore Cecchini ◽  
Madeleine Sánchez Gácita

Abstract. This work uses the number concentration-effective diameter phase-space to test cloud sensitivity to variations in the aerosol population characteristics, such as the aerosol size distribution, number concentration and hygroscopicity. It is based on the information from the top of a cloud simulated by a bin-microphysics single-column model, for initial conditions typical of the Amazon, using different assumptions regarding the entrainment and the aerosol size distribution. It is shown that the cloud-top evolution can be very sensitive to aerosol properties, but the relative importance of each parameter is variable. The sensitivity to each aerosol characteristic varies as a function of the parameter tested and is conditioned by the base values of the other parameters, showing a specific dependence for each configuration of the model. When both the entrainment and the bin treatment of the aerosol are allowed, the largest influence on the droplet size distribution sensitivity was obtained for the median radius of the aerosols and not for the total number concentration of aerosols. Our results reinforce that the cloud condensation nuclei activity can not be predicted solely on the basis of the w∕Na supersaturation-based regimes.


Abstract This paper examines the impact of cloud-base turbulence on activation of cloud condensation nuclei (CCN). Following our previous studies, we contrast activation within a non-turbulent adiabatic parcel and an adiabatic parcel filled with turbulence. The latter is simulated by applying a forced implicit large eddy simulation within a triply periodic computational domain of 643 m3. We consider two monodisperse CCN. Small CCN have a dry radius of 0.01 micron and a corresponding activation (critical) radius and critical supersaturation of 0.6 micron and 1.3%, respectively. Large CCN have a dry radius of 0.2 micron and feature activation radius of 5.4 micron and critical supersaturation 0.15 %. CCN are assumed in 200 cm−3 concentration in all cases. Mean cloud base updraft velocities of 0.33, 1, and 3 m s−1 are considered. In the non-turbulent parcel, all CCN are activated and lead to a monodisperse droplet size distribution above the cloud base, with practically the same droplet size in all simulations. In contrast, turbulence can lead to activation of only a fraction of all CCN with a non-zero spectral width above the cloud base, of the order of 1 micron, especially in the case of small CCN and weak mean cloud base ascent. We compare our results to studies of the turbulent single-size CCN activation in the Pi chamber. Sensitivity simulations that apply a smaller turbulence intensity, smaller computational domain, and modified initial conditions document the impact of specific modeling assumptions. The simulations call for a more realistic high-resolution modeling of turbulent cloud base activation.


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