Scale dependence of entrainment‐mixing mechanisms in cumulus clouds

Lu, Chen; Liu, Yangang; Niu, Shengjie; Endo, Satoshi

doi:10.1002/2014jd022265

Cited by 55 publications

(75 citation statements)

References 54 publications

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“…Within these ranges the effective radius can change by more than 10-15 %. Standard mixing diagrams do not include this range that, to our knowledge, has never been investigated despite the fact that multiple in situ measurements indicate its existence (e.g., Lu et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Theoretical analysis of mixing in liquid clouds – Part 3: Inhomogeneous mixing

2016

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Abstract. An idealized diffusion-evaporation model of timedependent mixing between a cloud volume and a dropletfree volume is analyzed. The initial droplet size distribution (DSD) in the cloud volume is assumed to be monodisperse. It is shown that evolution of the microphysical variables and the final equilibrium state are unambiguously determined by two non-dimensional parameters. The first one is the potential evaporation parameter R, proportional to the ratio of the saturation deficit to the liquid water content in the cloud volume, that determines whether the equilibrium state is reached at 100 % relative humidity, or is characterized by a complete evaporation of cloud droplets. The second parameter Da is the Damkölher number equal to the ratio of the characteristic mixing time to the phase relaxation time. Parameters R and Da determine the type of mixing.The results are analyzed within a wide range of values of R and Da. It is shown that there is no pure homogeneous mixing, since the first mixing stage is always inhomogeneous. The mixing type can change during the mixing process. Any mixing type leads to formation of a tail of small droplets in DSD and, therefore, to DSD broadening that depends on Da. At large Da, the final DSD dispersion can be as large as 0.2. The total duration of mixing varies from several to 100 phase relaxation time periods, depending on R and Da.The definitions of homogeneous and inhomogeneous types of mixing are reconsidered and clarified, enabling a more precise delimitation between them. The paper also compares the results obtained with those based on the classic mixing concepts.

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Section: Discussionmentioning

confidence: 99%

Theoretical analysis of mixing in liquid clouds – Part 3: Inhomogeneous mixing

2016

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“…The criterion of the in‐cloud drizzle water content (radius > 25 μm) averaged over the observation period of the flight smaller than 0.005 g m −3 is used to select the nondrizzling cumulus clouds. In total, there are 186 nondrizzling growing cumulus clouds from eight flights (22–24 May, 11 June, 19 June, 23 June, 24 June, and 26 June 2009); the same data set was used in Cheng et al () and Lu et al (). As shown in Table , the total number of cloud droplet size distributions was 13,652 from 186 clouds.…”

Section: Observational Analysismentioning

confidence: 99%

On Which Microphysical Time Scales to Use in Studies of Entrainment‐Mixing Mechanisms in Clouds

Liu

Zhu

et al. 2018

JGR Atmospheres

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The commonly used time scales in entrainment‐mixing studies are examined to seek the most appropriate one, based on aircraft observations of cumulus clouds from the RACORO campaign and numerical simulations with the Explicit Mixing Parcel Model. The time scales include the following: τevap, the time for droplet complete evaporation; τphase, the time for saturation ratio deficit (S) to reach 1/e of its initial value; τsatu, the time for S to reach −0.5%; and τreact, the time for complete droplet evaporation or S to reach −0.5%. It is found that the proper time scale to use depends on the specific objectives of entrainment‐mixing studies. First, if the focus is on the variations of liquid water content (LWC) and S, then τreact for saturation, τsatu and τphase are almost equivalently appropriate, because they all represent the rate of dry air reaching saturation or of LWC decrease. Second, if one focuses on the variations of droplet size and number concentration, τreact for complete evaporation and τevap are proper because they characterize how fast droplets evaporate and whether number concentration decreases. Moreover, τreact for complete evaporation and τevap are always positively correlated with homogeneous mixing degree (ψ); thus, the two time scales, especially τevap, are recommended for developing parameterizations. However, ψ and the other time scales can be negatively, positively, or not correlated, depending on the dominant factors of the entrained air (i.e., relative humidity or aerosols). Third, all time scales are proportional to each other under certain microphysical and thermodynamic conditions.

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“…The existence of the turbulent energy cascade implies that there is a range of turbulence time scales, from the large‐scale eddy turnover time (short: large‐eddy time) T L to the dissipation (or Kolmogorov) time τ η . It is thus possible that within the turbulence cascade, both D a > 1 and D a < 1 can exist at different spatial scales, so that one can also expect a different microphysical response at different scales (Andrejczuk et al, ; Beals et al, ; Korolev & Mazin, ; Lehmann et al, ; Lu et al, , ; Siebert et al, ). For example, some DNS results suggested that a transition from inhomogeneous to homogeneous mixing could lead to an inhomogeneous offset in the microphysical trajectory in a mixing diagram (Kumar et al, ).…”

Section: Introductionmentioning

confidence: 99%

Scale Dependence of Cloud Microphysical Response to Turbulent Entrainment and Mixing

Kumar

Götzfried

Suresh

et al. 2018

J Adv Model Earth Syst

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The dynamics and lifetime of atmospheric clouds are tightly coupled to entrainment and turbulent mixing. This paper presents direct numerical simulations of turbulent mixing followed by droplet evaporation at the cloud‐clear air interface in a meter‐sized volume, with an ensemble of up to almost half a billion individual cloud water droplets. The dependence of the mixing process on domain size reveals that inhomogeneous mixing becomes increasingly important as the domain size is increased. The shape of the droplet size distribution varies strongly with spatial scale, with the appearance of a pronounced negative exponential tail. The increase of relative dispersion during the transient mixing process is strongly dependent on the scale of the mixing and therefore on the Damköhler number, defined as the turbulence large‐eddy time scale divided by the cloud supersaturation relaxation time.

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Scale dependence of entrainment‐mixing mechanisms in cumulus clouds

Cited by 55 publications

References 54 publications

Theoretical analysis of mixing in liquid clouds – Part 3: Inhomogeneous mixing

Theoretical analysis of mixing in liquid clouds – Part 3: Inhomogeneous mixing

On Which Microphysical Time Scales to Use in Studies of Entrainment‐Mixing Mechanisms in Clouds

Scale Dependence of Cloud Microphysical Response to Turbulent Entrainment and Mixing

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