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 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.

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.

Turbulence Effects of Collision Efficiency and Broadening of Droplet Size Distribution in Cumulus Clouds

2018 ◽  
Vol 75 (1) ◽  
pp. 203-217 ◽  
Author(s):  
Sisi Chen ◽  
M. K. Yau ◽  
Peter Bartello
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Droplet Growth ◽  
Small Scale ◽  
Cumulus Clouds ◽  
Collision Efficiency ◽  
Cloud Droplets ◽  
R Ratio ◽  
Condensational Growth

This paper aims to investigate and quantify the turbulence effect on droplet collision efficiency and explore the broadening mechanism of the droplet size distribution (DSD) in cumulus clouds. The sophisticated model employed in this study individually traces droplet motions affected by gravity, droplet disturbance flows, and turbulence in a Lagrangian frame. Direct numerical simulation (DNS) techniques are implemented to resolve the small-scale turbulence. Collision statistics for cloud droplets of radii between 5 and 25 μm at five different turbulence dissipation rates (20–500 cm2 s−3) are computed and compared with pure-gravity cases. The results show that the turbulence enhancement of collision efficiency highly depends on the r ratio (defined as the radius ratio of collected and collector droplets r/ R) but is less sensitive to the size of the collector droplet investigated in this study. Particularly, the enhancement is strongest among comparable-sized collisions, indicating that turbulence can significantly broaden the narrow DSD resulting from condensational growth. Finally, DNS experiments of droplet growth by collision–coalescence in turbulence are performed for the first time in the literature to further illustrate this hypothesis and to monitor the appearance of drizzle in the early rain-formation stage. By comparing the resulting DSDs at different turbulence intensities, it is found that broadening is most pronounced when turbulence is strongest and similar-sized collisions account for 21%–24% of total collisions in turbulent cases compared with only 9% in the gravitational case.

scholarly journals Development of a cloud microphysical model and parameterizations to describe the effect of CCN on warm cloud

2006 ◽  
Vol 6 (1) ◽  
pp. 1413-1453 ◽  
Author(s):  
N. Kuba ◽  
Y. Fujiyoshi
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Global Model ◽  
Lagrangian Framework ◽  
Cloud Droplet Size Distribution ◽  
Grid Points ◽  
Bin Method

Abstract. First, a hybrid cloud microphysical model was developed that incorporates both Lagrangian and Eulerian frameworks to study quantitatively the effect of cloud condensation nuclei (CCN) on the precipitation of warm clouds. A parcel model and a grid model comprise the cloud model. The condensation growth of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation and coalescence are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection are estimated in the Eulerian framework between grid points. Results from the cloud model show that an increase in the number of CCN affects both the amount and the location of precipitation. Additionally, results from the hybrid microphysical model and Kessler's parameterization were compared. Second, new parameterizations were developed that estimate the number and size distribution of cloud droplets given the updraft velocity and the number of CCN. The parameterizations were derived from the results of numerous numerical experiments that used the cloud microphysical parcel model. The input information of CCN for these parameterizations is only several values of CCN spectrum (they are given by CCN counter for example). It is more convenient than conventional parameterizations those need values concerned with CCN spectrum, C and k in the equation of N=CSk, or, breadth, total number and median radius, for example. The new parameterizations' predictions of initial cloud droplet size distribution for the bin method were verified by using the aforesaid hybrid microphysical model. The newly developed parameterizations will save computing time, and can effectively approximate components of cloud microphysics in a non-hydrostatic cloud model. The parameterizations are useful not only in the bin method in the regional cloud-resolving model but also both for a two-moment bulk microphysical model and for a global model. The effects of sea salt, sulfate, and organic carbon particles were also studied with these parameterizations and global model.

scholarly journals What does reflection from cloud sides tell us about vertical distribution of cloud droplet sizes?

2006 ◽  
Vol 6 (4) ◽  
pp. 7207-7233 ◽  
Author(s):  
A. Marshak ◽  
J. V. Martins ◽  
V. Zubko ◽  
Y. J. Kaufman
Keyword(s):  
Solar Radiation ◽  
Radiative Transfer ◽  
Droplet Size ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Retrieval Algorithm ◽  
Satellite Mission ◽  
Bayesian Theorem ◽  
Droplet Sizes

Abstract. Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from CloudSat.  The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3-D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimentional (3-D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 μm) and one with liquid water efficient absorption of solar radiation (2.1 μm). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3-D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

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

2016 ◽  
Author(s):  
Fan Yang ◽  
Raymond Shaw ◽  
Huiwen Xue
Keyword(s):  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Critical Height ◽  
Growth Region ◽  
Cloud Droplets ◽  
Cloud Properties ◽  
Environment Temperature ◽  
Environmental Air

Abstract. Cloud droplet response to entrainment and mixing between a cloud and its environment is often considered by itself, without accounting for subsequent growth after the mixing event. Here we consider the change in cloud properties when the mixed parcel rises adiabatically after the mixing event. The vertical profile for liquid water mixing ratio after a mixing event is derived analytically, allowing the reduction due to mixing to be predicted from the mixing fraction and the cloud and environment temperature and humidity. 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 by 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 mixing 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 under polydisperse conditions. The findings have implications for the origin of large cloud droplets that may contribute to onset of collision-coalescence in warm clouds.

scholarly journals A New Mechanism of Droplet Size Distribution Broadening during Diffusional Growth

2013 ◽  
Vol 70 (7) ◽  
pp. 2051-2071 ◽  
Author(s):  
Alexei Korolev ◽  
Mark Pinsky ◽  
Alex Khain
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Initial Conditions ◽  
Droplet Size Distribution ◽  
Cloud Base ◽  
Diffusional Growth ◽  
Cloud Droplets ◽  
Droplet Concentration ◽  
Droplet Sizes ◽  
Precipitation Formation

Abstract A new mechanism has been developed for size distribution broadening toward large droplet sizes. This mechanism may explain the rapid formation of large cloud droplets, which may subsequently trigger precipitation formation through the collision–coalescence process. The essence of the new mechanism consists of a sequence of mixing events between ascending and descending parcels. When adiabatically ascending and descending parcels having the same initial conditions at the cloud base arrive at the same level, they will have different droplet sizes and temperatures, as well as different supersaturations. Isobaric mixing between such parcels followed by further ascents and descents enables the enhanced growth of large droplets. The numerical simulation of this process suggests that the formation of large 30–40-μm droplets may occur within 20–30 min inside a shallow adiabatic stratiform layer. The dependencies of the rate of the droplet size distribution broadening on the intensity of the vertical fluctuations, their spatial amplitude, rate of mixing, droplet concentration, and other parameters are considered here. The effectiveness of this mechanism in different types of clouds is discussed.

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 Condensational and Collisional Growth of Cloud Droplets in a Turbulent Environment

2019 ◽  
Vol 77 (1) ◽  
pp. 337-353 ◽  
Author(s):  
Xiang-Yu Li ◽  
Axel Brandenburg ◽  
Gunilla Svensson ◽  
Nils E. L. Haugen ◽  
Bernhard Mehlig ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Early Stage ◽  
Droplet Size Distribution ◽  
Energy Dissipation Rate ◽  
Cloud Droplets ◽  
Navier Stokes Equation ◽  
Droplet Dynamics ◽  
Condensational Growth ◽  
Rain Formation

Abstract We investigate the effect of turbulence on the combined condensational and collisional growth of cloud droplets by means of high-resolution direct numerical simulations of turbulence and a superparticle approximation for droplet dynamics and collisions. The droplets are subject to turbulence as well as gravity, and their collision and coalescence efficiencies are taken to be unity. We solve the thermodynamic equations governing temperature, water vapor mixing ratio, and the resulting supersaturation fields together with the Navier–Stokes equation. We find that the droplet size distribution broadens with increasing Reynolds number and/or mean energy dissipation rate. Turbulence affects the condensational growth directly through supersaturation fluctuations, and it influences collisional growth indirectly through condensation. Our simulations show for the first time that, in the absence of the mean updraft cooling, supersaturation-fluctuation-induced broadening of droplet size distributions enhances the collisional growth. This is contrary to classical (nonturbulent) condensational growth, which leads to a growing mean droplet size, but a narrower droplet size distribution. Our findings, instead, show that condensational growth facilitates collisional growth by broadening the size distribution in the tails at an early stage of rain formation. With increasing Reynolds numbers, evaporation becomes stronger. This counteracts the broadening effect due to condensation at late stages of rain formation. Our conclusions are consistent with results of laboratory experiments and field observations, and show that supersaturation fluctuations are important for precipitation.

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