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.

scholarly journals Ultraclean Layers and Optically Thin Clouds in the Stratocumulus-to-Cumulus Transition. Part II: Depletion of Cloud Droplets and Cloud Condensation Nuclei through Collision–Coalescence

2018 ◽  
Vol 75 (5) ◽  
pp. 1653-1673 ◽  
Author(s):  
Kuan-Ting O ◽  
Robert Wood ◽  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Marine Boundary Layer ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Condensation Nuclei ◽  
Cloud Droplets ◽  
Droplet Concentration ◽  
Cloud Thickness

In Part I, aircraft observations are used to show that ultraclean layers (UCLs) in the marine boundary layer (MBL) are a common feature of the stratocumulus-to-cumulus transition (SCT) region over the northeast Pacific. The ultraclean layers are defined as layers of either cloud or clear air in which the concentration of particles with diameter larger than 0.1 μm is below 10 cm−3. Here, idealized microphysical parcel modeling shows that in the cumulus regime, collision–coalescence can strongly deplete cloud droplet concentration in cumulus (Cu) updrafts, thereby removing cloud condensation nuclei (CCN) from the atmosphere, suggesting that collision scavenging is likely the key process causing the low particle concentration in UCLs. Furthermore, the model results suggest that the stratocumulus regime is typically not favorable for UCL formation, because condensate amounts are generally not large enough to deplete drops in the time it takes to loft air to the upper planetary boundary layer (PBL). A bulk parameterization of the coalescence-scavenging rate is derived based on in situ measurements. The fractional coalescence-scavenging rate is found to be strongly dependent upon liquid water content (LWC) and, hence, the height above cloud base, indicating that a higher cloud top and thus a greater cloud thickness in a Cu updraft is an important factor accounting for the observed sharp rise of UCL coverage in the SCT region. An important implication is that PBL height, which controls maximum cloud thickness, and therefore LWC in updrafts, could be a crucial factor constraining coalescence scavenging and thus the formation of UCLs in the MBL.

CCN and Vertical Velocity Influences on Droplet Concentrations and Supersaturations in Clean and Polluted Stratus Clouds

2013 ◽  
Vol 71 (1) ◽  
pp. 312-331 ◽  
Author(s):  
James G. Hudson ◽  
Stephen Noble
Keyword(s):  
Vertical Velocity ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Cloud Droplets ◽  
Stratus Cloud ◽  
Marine Stratus ◽  
Lower Cloud ◽  
High Concentrations ◽  
Positive Correlations

Abstract Cloud microphysics and cloud condensation nuclei (CCN) measurements from two marine stratus cloud projects are presented and analyzed. Results show that the increase of cloud droplet concentrations Nc with CCN concentrations NCCN rolls off for NCCN at 1% supersaturation (S)N1% above 400 cm−3. Moreover, at such high concentrations Nc was not so well correlated with NCCN but tended to be more closely related to vertical velocity W or variations of W (σw). This changeover from predominate Nc dependence on NCCN to Nc dependence on W or σw is due to the higher slope k of CCN spectra at lower S, which is made more relevant by the lower cloud S that is forced by higher NCCN. Higher k makes greater influence of W or σw variations than NCCN variations on Nc. This changeover at high NCCN thus seems to limit the indirect aerosol effect (IAE). On the other hand, in clean-air stratus cloud S often exceeded 1% and decreased to slightly less than 0.1% in polluted conditions. This means that smaller CCN [those with higher critical S (Sc)], which are generally more numerous than larger CCN (lower Sc), are capable of producing stratus cloud droplets, especially when they are advected into clean marine air masses where they can induce IAE. Positive correlations between turbulence σw and NCCN are attributed to greater differential latent heat exchange of smaller more numerous cloud droplets that evaporate more readily. Such apparent CCN influences on cloud dynamics tend to support trends that oppose conventional IAE, that is, less rather than greater cloudiness in polluted environments.

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 The evolution of cloud microphysics upon aerosol interaction at the summit of Mt. Tai, China

2019 ◽  
Author(s):  
Jiarong Li ◽  
Chao Zhu ◽  
Hui Chen ◽  
Defeng Zhao ◽  
Likun Xue ◽  
...  
Keyword(s):  
Climate Models ◽  
Cloud Condensation Nuclei ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Life Cycles ◽  
Cloud Droplets ◽  
Climate Effect ◽  
Local Climate ◽  
The North ◽  
Microphysical Properties

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.

scholarly journals Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics

2017 ◽  
Vol 74 (10) ◽  
pp. 3145-3166 ◽  
Author(s):  
K. Gayatri ◽  
S. Patade ◽  
T. V. Prabha
Keyword(s):  
Size Distribution ◽  
Cloud Condensation Nuclei ◽  
Wrf Model ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Large Area ◽  
Surface Precipitation ◽  
Aerosol Cloud ◽  
Bin Microphysics

Abstract The Weather Research and Forecasting (WRF) Model coupled with a spectral bin microphysics (SBM) scheme is used to investigate aerosol effects on cloud microphysics and precipitation over the Indian peninsular region. The main emphasis of the study is in comparing simulated cloud microphysical structure with in situ aircraft observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX). Aerosol–cloud interaction over the rain-shadow region is investigated with observed and simulated size distribution spectra of cloud droplets and ice particles in monsoon clouds. It is shown that size distributions as well as other microphysical characteristics obtained from simulations such as liquid water content, cloud droplet effective radius, cloud droplet number concentration, and thermodynamic parameters are in good agreement with the observations. It is seen that in clouds with high cloud condensation nuclei (CCN) concentrations, snow and graupel size distribution spectra were broader compared to clouds with low concentrations of CCN, mainly because of enhanced riming in the presence of a large number of droplets with a diameter of 10–30 μm. The Hallett–Mossop ice multiplication process is illustrated to have an impact on snow and graupel mass. The changes in CCN concentrations have a strong effect on cloud properties over the domain, amounts of cloud water, and the glaciation of the clouds, but the effects on surface precipitation are small when averaged over a large area. Overall enhancement of cold-phase cloud processes in the high-CCN case contributed to slight enhancement (5%) in domain-averaged surface precipitation.

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 Understanding aerosol–cloud interactions through modeling the development of orographic cumulus congestus during IPHEx

2019 ◽  
Vol 19 (3) ◽  
pp. 1413-1437 ◽  
Author(s):  
Yajuan Duan ◽  
Markus D. Petters ◽  
Ana P. Barros
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Turbulent Dispersion ◽  
Cloud Base ◽  
Droplet Growth ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

Abstract. A new cloud parcel model (CPM) including activation, condensation, collision–coalescence, and lateral entrainment processes is used to investigate aerosol–cloud interactions (ACIs) in cumulus development prior to rainfall onset. The CPM was applied with surface aerosol measurements to predict the vertical structure of cloud development at early stages, and the model results were evaluated against airborne observations of cloud microphysics and thermodynamic conditions collected during the Integrated Precipitation and Hydrology Experiment (IPHEx) in the inner region of the southern Appalachian Mountains (SAM). Sensitivity analysis was conducted to examine the model response to variations in key ACI physiochemical parameters and initial conditions. The CPM sensitivities mirror those found in parcel models without entrainment and collision–coalescence, except for the evolution of the droplet spectrum and liquid water content with height. Simulated cloud droplet number concentrations (CDNCs) exhibit high sensitivity to variations in the initial aerosol concentration at cloud base, but weak sensitivity to bulk aerosol hygroscopicity. The condensation coefficient ac plays a governing role in determining the evolution of CDNC, liquid water content (LWC), and cloud droplet spectra (CDS) in time and with height. Lower values of ac lead to higher CDNCs and broader CDS above cloud base, and higher maximum supersaturation near cloud base. Analysis of model simulations reveals that competitive interference among turbulent dispersion, activation, and droplet growth processes modulates spectral width and explains the emergence of bimodal CDS and CDNC heterogeneity in aircraft measurements from different cloud regions and at different heights. Parameterization of nonlinear interactions among entrainment, condensational growth, and collision–coalescence processes is therefore necessary to simulate the vertical structures of CDNCs and CDSs in convective clouds. Comparisons of model predictions with data suggest that the representation of lateral entrainment remains challenging due to the spatial heterogeneity of the convective boundary layer and the intricate 3-D circulations in mountainous regions.

scholarly journals Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

2015 ◽  
Vol 15 (11) ◽  
pp. 15755-15790
Author(s):  
C. Zhou ◽  
X. Zhang ◽  
S. Gong ◽  
Y. Wang ◽  
M. Xue
Keyword(s):  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Time Step ◽  
Cloud Droplets ◽  
Weather Model ◽  
Weather Modeling ◽  
Almost All ◽  
Aerosol Activation ◽  
Precipitation Events

Abstract. A comprehensive aerosol–cloud–precipitation interaction (ACI) scheme has been developed under CMA chemical weather modeling system GRAPES/CUACE. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) is fed online interactively into a two-moment cloud scheme (WDM6) and a convective parameterization to drive the cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred. The results show that interactive aerosols with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content and cloud droplet number concentrations while decrease the mean diameter of cloud droplets with varying magnitudes of the changes in each case and region. These interactive micro-physical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48% enhancements of TS scoring for 6 h precipitation in almost all regions. The interactive aerosols with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

scholarly journals The effects of heating by transported dust layers on cloud and precipitation: a numerical study

2007 ◽  
Vol 7 (13) ◽  
pp. 3497-3505 ◽  
Author(s):  
Y. Yin ◽  
L. Chen
Keyword(s):  
Mineral Dust ◽  
Numerical Study ◽  
Cloud Model ◽  
Cloud Condensation Nuclei ◽  
Dust Particles ◽  
Cloud Base ◽  
Cloud Droplets ◽  
Cloud Optical Depth ◽  
Mineral Aerosols ◽  
Lower Cloud

Abstract. There have been numerous recent publications showing that mineral dust might be a good absorber for solar radiation in addition to its capability to act as cloud condensation nuclei (CCN) and ice forming nuclei (IFN), and could lead to reduced cloud cover and precipitation in the region where it is present. This effect is investigated using a dynamic cloud model with detailed microphysics of both warm and ice phase processes. The model is initialized using measured size distributions and concentrations of mineral dust particles. Our results show that when dust appears at the cloud-base height and below 3 km, where the temperature is warmer than −5°C, the heating induced by the presence of dust layers can inhibit the formation of cloud droplets and suppresses the development of precipitation, leading to lower cloud optical depth and albedo. On the other hand, when the dust layers are located at altitudes with temperature colder than −5°C, or above the −5°C level, mineral aerosols can act as effective ice nuclei, intensify the ice-forming processes, and may enhance the development of cloud and precipitation. It is also found that the heating effect is more pronounced in continental clouds than in maritime clouds.

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.

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