Kinetic Potential and Barrier Crossing: A Model for Warm Cloud Drizzle Formation

McGraw, Robert; Liu, Yangang

doi:10.1103/physrevlett.90.018501

Cited by 41 publications

(40 citation statements)

References 21 publications

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“…In the atmosphere, feedbacks between the microphysical evolution and σs may exist (e.g., due to varying radiative flux divergence). In this context, the results presented here certainly provide support for similar stochastic differential equation approaches for cloud microphysics (9,20,28) and perhaps even for macroscopic cloud properties (36). It will be intriguing to investigate exactly how the current turbulence-induced aerosol effect relates to that observed in closed parcel studies that consider wide ranges of aerosol concentrations (37,38).…”

Section: Atmospheric Implicationssupporting

confidence: 65%

Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

Chandrakar

Cantrell

Chang

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

124

215

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The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics (τc < τ t ) for high aerosol concentration, and slow microphysics (τc > τ t ) for low aerosol concentration; here, τc is the phase-relaxation time and τ t is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as τ, and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.aerosol indirect effect | cloud-droplet size distribution | cloud-turbulence interactions T he optical properties of warm clouds depend on the droplet size distribution and its moments such as number density and effective radius, which, in turn, are influenced by the aerosol particles that act as nuclei for the formation of cloud droplets (1, 2). Thus, aerosol indirect effects are considered among the largest uncertainties in climate response to changes in radiative forcing (3). This work addresses how the aerosol number concentration affects the cloud-droplet size distribution in a turbulent environment, which is relevant to both the aerosol first and second indirect effects (albedo and lifetime effects). The lifetime effect links the development of precipitation, and thus cloud lifetime, to aerosol number concentration. The logic is that a higher aerosol concentration leads to smaller cloud droplets and narrower size distributions, and therefore suppression of the collision and coalescence of droplets, thereby increasing cloud lifetime and maintaining higher cloud liquid water content (4-7). The microphysical details of the transition from condensation growth to collision growth are not fully understood, however, and it is fair to say that the underlying mechanism of the second indirect effect is still a matter of active research (2, 8). Initiation of precipitation in warm clouds ...

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Section: Atmospheric Implicationssupporting

confidence: 65%

Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

Chandrakar

Cantrell

Chang

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

124

215

View full text Add to dashboard Cite

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“…Since the nucleation and condensation processes are not yet included in this model, future developments will attempt to include the combined effect of turbulent collection and condensation (McGraw and Liu, 2003) on droplet growth.…”

Section: Atmosmentioning

confidence: 99%

The validity of the kinetic collection equation revisited – Part 3: Sol–gel transition under turbulent conditions

2013

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Abstract. Warm rain in real clouds is produced by the collision and coalescence of an initial population of small droplets. The production of rain in warm cumulus clouds is still one of the open problems in cloud physics, and although several mechanisms have been proposed in the past, at present there is no complete explanation for the rapid growth of cloud droplets within the size range of diameters from 10 to 50 µm. By using a collection kernel enhanced by turbulence and a fully stochastic simulation method, the formation of a runaway droplet is modeled through the turbulent collection process. When the runaway droplet forms, the traditional calculation using the kinetic collection equation is no longer valid, since the assumption of a continuous distribution breaks down. There is in essence a phase transition in the system from a continuous distribution to a continuous distribution plus a runaway droplet. This transition can be associated to gelation (also called sol-gel transition) and is proposed here as a mechanism for the formation of large droplets required to trigger warm rain development in cumulus clouds. The fully stochastic turbulent model reveals gelation and the formation of a droplet with mass comparable to the mass of the initial system. The time when the sol-gel transition occurs is estimated with a Monte Carlo method when the parameter ρ (the ratio of the standard deviation for the largest droplet mass over all the realizations to the averaged value) reaches its maximum value. Moreover, we show that the non-turbulent case does not exhibit the sol-gel transition that can account for the impossibility of producing raindrop embryos in such a system. In the context of cloud physics theory, gelation can be interpreted as the formation of the "lucky droplet" that grows at a much faster rate than the rest of the population and becomes the embryo for runaway raindrops.

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“…The explanation of some of these issues, like the lack of fundamental understanding of the glaciation of clouds, or the extent by which warm rain dominates clouds that extend to very cold temperatures near the tropopause under different aerosol conditions have been targeted by the scientific community for a long time (e.g. McGraw and Liu, 2003). To alleviate some of this uncertainty several field campaigns have been performed to study developing convective systems (CRYSTAL-FACE, CAMEX, SMOCC, TC4 and others).…”

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confidence: 99%

Remote sensing the vertical profile of cloud droplet effective radius, thermodynamic phase, and temperature

et al. 2011

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Abstract. Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei.Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile Correspondence to: J. V. Martins (martins@umbc.edu) of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.The CLAIM-3D (3-Dimensional Cloud Aerosol Interaction Mission) satellite concept proposed here combines several techniques to simultaneously measure the vertical profile of cloud microphysics, thermodynamic phase, brightness temperature, and aerosol amount and type in the neighborhood of the clouds. The wide wavelength range, and the use of multi-angle polarization measurements proposed for this mission allow us to estimate the availability and characteristics of aerosol particles acting as cloud condensation nuclei, and their effects on the cloud microphysical structure. These results can provide unprecedented details on the response of cloud droplet microphysics to natural and anthropogenic aerosols in the size scale where the interaction really happens.

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Kinetic Potential and Barrier Crossing: A Model for Warm Cloud Drizzle Formation

Cited by 41 publications

References 21 publications

Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

The validity of the kinetic collection equation revisited – Part 3: Sol–gel transition under turbulent conditions

Remote sensing the vertical profile of cloud droplet effective radius, thermodynamic phase, and temperature

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