Abstract. Evolution of monodisperse and polydisperse droplet size distributions (DSD) during homogeneous mixing is analyzed. Time-dependent universal analytical expressions for supersaturation and liquid water content are derived. For an initial monodisperse DSD, these quantities are shown to depend on a sole non-dimensional parameter. The evolution of moments and moment-related functions in the course of homogeneous evaporation of polydisperse DSD is analyzed using a parcel model.It is shown that the classic conceptual scheme, according to which homogeneous mixing leads to a decrease in droplet mass at constant droplet concentration, is valid only in cases of monodisperse or initially very narrow polydisperse DSD. In cases of wide polydisperse DSD, mixing and successive evaporation lead to a decrease of both mass and concentration, so the characteristic droplet sizes remain nearly constant. As this feature is typically associated with inhomogeneous mixing, we conclude that in cases of an initially wide DSD at cloud top, homogeneous mixing is nearly indistinguishable from inhomogeneous mixing.
The final published version of this manuscript will replace the preliminary version at the above DOI once it is available.If you would like to cite this EOR in a separate work, please use the following full citation:Magaritz, L., M. Pinsky, and A. Khain, 2013: Effects of turbulent mixing on the structure and macroscopic properties of stratocumulus clouds demonstrated by a Lagrangian trajectory model. J. Atmos. Sci. Abstract 19The role of turbulent mixing in formation of the structure of stratocumulus clouds is 20 investigated using a Lagrangian-Eulerian parcel cloud model containing ~2000-5000 adjacent 21 parcels with the linear size of 25-40 m, moving with a turbulent-like velocity field with 22 observed energetic and statistical properties. The process of turbulent mixing of Lagrangian 23 parcels is parameterized using the k-epsilon theory extended to the case of mixing of non-24 conservative values. The model includes the interaction of cloud and the overlying inversion 25 layer. The stratocumulus clouds observed during flight RF01 of the DYCOMS-II field 26 experiment are simulated. 27 Effects of turbulent mixing are analyzed by comparing simulations with and without 28 mixing. When mixing between parcels is included, the thermodynamical and microphysical 29 structure of the measured stratocumulus clouds is properly reproduced. Mixing leads to a 30 more uniform cloud structure with well defined borders. Good agreement is found between 31 Paluch diagrams calculated in the model and those reproduced from measurements. The 32 radius of correlation of liquid water content and other variables calculated in the model is on 33 the order of several hundred meters and agrees well with observations. When mixing is not 34 included, the radius of correlation is on the scale of a single parcel and the cloud layer 35 contains dry entrained parcels making the microphysical structure unrealistic. It is also shown 36 that turbulent mixing leads to an increase in the effective radius, facilitates and accelerates 37 drizzle formation. The time in which a 40 m air parcel preserves its identification is estimated 38 from the results and is found to be on the order of 25 min. 39 40 Key words: stratocumulus clouds, effects of mixing on thermodynamics and statistical 41 properties of stratocumulus clouds, numerical modeling 42 43 3 65 mixing supersaturation in different parts of the mixing volumes is different and some fraction 66 of the droplets evaporates in dry air.67 4 There are contradictory opinions concerning the role played by extremely inhomogeneous 68 mixing in the formation of large droplets and first raindrops in cumulus clouds. Numerical 69 results of Cooper et al. (2013) seem to lend some support for the idea that inhomogeneous 70 mixing leads to an increase in drop size. In contrast, a numerical study by Schlüter (2006) have 71 shown that extremely inhomogeneous mixing does not result in formation of larger droplets, 72 but leads to spectrum broadening towards smaller drop sizes. These results were reached even 73 thou...
Abstract. The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian-Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ∼ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic and characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. It was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.
The role of turbulent mixing in formation of low horizontal variability of effective radius near the top of nondrizzling stratocumulus clouds is investigated in simulations of clouds observed during the Second Dynamics and Chemistry of Marine Stratocumulus field experiment. The clouds are simulated using a spectral bin microphysics Lagrangian‐Eulerian model consisting of ~2000 adjacent parcels moving in a turbulence‐like field with observed correlation properties. The parcels interact through drop sedimentation and turbulent mixing. It was found that the effective radius variability in the horizontal direction near cloud top does not exceed ~10% of the averaged value. Three different types of cloud parcels are revealed to be differently influenced by mixing: ascending slightly diluted parcels, cloudy parcels experiencing intense mixing with parcels from inversion, and initially dry parcels. The evolution of droplet size distributions in parcels belonging to these types is investigated. It is shown that in parcels of the first two types the values of effective radii do not change or change only slightly remaining close to the adiabatic value. In initially droplet‐free parcels effective radius rapidly reaches a value close to the adiabatic value, while liquid water content remains low. Therefore, turbulent mixing leads to establishing vertical profiles of effective radius, which are close to the adiabatic profile.
Abstract. The mechanism of drizzle formation in shallow stratocumulus clouds and the effect of turbulent mixing on this process are investigated. A Lagrangian-Eularian model of the cloud-topped boundary layer is used to simulate the cloud measured during flight RF07 of the DYCOMS-II field experiment. The model contains ~ 2000 air parcels that are advected in a turbulence-like velocity field. In the model all microphysical processes are described for each Lagrangian air volume, and turbulent mixing between the parcels is also taken into account. It was found that the first large drops form in air volumes that are closest to adiabatic and characterized by high humidity, extended residence near cloud top, and maximum values of liquid water content, allowing the formation of drops as a result of efficient collisions. The first large drops form near cloud top and initiate drizzle formation in the cloud. Drizzle is developed only when turbulent mixing of parcels is included in the model. Without mixing, the cloud structure is extremely inhomogeneous and the few large drops that do form in the cloud evaporate during their sedimentation. It was found that turbulent mixing can delay the process of drizzle initiation but is essential for the further development of drizzle in the cloud.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.