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Fluctuations and growth histories of cloud droplets: super-particle simulations of the collision-coalescence process
Stockholm University, Faculty of Science, Department of Meteorology . Stockholm University, Nordic Institute for Theoretical Physics (Nordita).ORCID iD: 0000-0002-5722-0018
Stockholm University, Faculty of Science, Department of Meteorology .
Stockholm University, Nordic Institute for Theoretical Physics (Nordita).
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Direct numerical simulations of collisional aggregation in turbulent aerosols are computationally demanding. Many authors therefore use an approximate model of the collision-coalescence process that is computationally more efficient: it relies on representing physical particles in terms of ‘superparticles’. One monitors collisions between superparticles and accounts for collisions between physical particles using a Monte-Carlo algorithm. It has been shown that this algorithm can faithfully represent mean particle growth in turbulent aerosols. Here we investigate how fluctuations are represented in this algorithm. We study particles of different sizes settling under gravity, assuming that the effect of turbulence is simply to mix the particles horizontally. We compute the statistics of growth histories and analyze their fluctuations in terms of the ‘lucky-droplet’ model. We discuss under which circumstances artefacts change the fluctuations of the growth histories, how these can be avoided, and which questions remain to be answered when turbulent fluctuations are explicitly incorporated.

National Category
Climate Research
Research subject
Atmospheric Sciences and Oceanography
Identifiers
URN: urn:nbn:se:su:diva-158540OAI: oai:DiVA.org:su-158540DiVA, id: diva2:1237427
Funder
The Research Council of Norway, FRINATEK grant 231444Knut and Alice Wallenberg Foundation, Dnr. KAW 2014.0048Swedish Research Council, 2012-5797, 2013-03992, and 2017-03865Available from: 2018-08-08 Created: 2018-08-08 Last updated: 2018-08-14Bibliographically approved
In thesis
1. Droplet growth in atmospheric turbulence: A direct numerical simulation study
Open this publication in new window or tab >>Droplet growth in atmospheric turbulence: A direct numerical simulation study
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This Ph.D. thesis examines the challenging problem of how turbulence affects the growth of cloud droplets in warm clouds. Droplets grow by either condensation or collision. Without turbulence, the condensation process driven by a uniform supersaturation field is only efficient when droplets are smaller than 15 μm (radius). Gravitational collision becomes effective when the radius of droplets is larger than 50 μm. The size gap of 15–50 μm, in which neither condensation nor collision processes dominate droplet growth, has puzzled the cloud microphysics community for around 70 years. It is the key to explaining the rapid warm rain formation with a timescale of about 20 minutes. Turbulence has been proposed to bridge this size gap by enhancing droplet growth processes, and thereby, to explain rapid warm rain formation. Since cloud–climate interaction is one of the greatest uncertainties for climate models, the fundamental understanding of rapid warm rain formation may help improve climate models.

The condensational and collisional growth of cloud droplets in atmospheric turbulence is essentially the problem of turbulence-droplet interaction. However, turbulence alone is one of the unresolved and most challenging problems in classical physics. The turbulence–droplet interaction is even more difficult due to its strong nonlinearity and multi-scale properties in both time and space. In this thesis, Eulerian and Lagrangian models are developed and compared to tackle turbulence–droplet interactions. It is found that the Lagrangian superparticle model is computationally less demanding than the Eulerian Smoluchowski model.

The condensation process is then investigated by solving the hydrodynamic and thermodynamic equations using direct numerical simulations with droplets modeled as Lagrangian particles. With turbulence included, the droplet size distribution is found to broaden, which is contrary to the classical theory without supersaturation fluctuations, where condensational growth leads to progressively narrower droplet size distributions. Furthermore, the time evolution of droplet size distributions is observed to strongly depend on the Reynolds number and only weakly on the mean energy dissipation rate. Subsequently, the effect of turbulence on the collision process driven by both turbulence and gravity is explored. It is found that the droplet size distribution depends moderately on the mean energy dissipation rate, but is insensitive to the Reynolds number. Finally, the effect of turbulence on the combined condensational and collisional growth is investigated. In this case, the droplet size distribution is found to depend on both the Reynolds number and the mean energy dissipation rate. Considering small values of the mean energy dissipation rate and high Reynolds numbers in warm clouds, it is concluded that turbulence enhances the condensational growth with increasing Reynolds number, while the collision process is indirectly affected by turbulence through the condensation process. Therefore, turbulence facilitates warm rain formation by enhancing the condensation process, which predominantly depends on the Reynolds number.

Place, publisher, year, edition, pages
Stockholm: Department of Meteorology, Stockholm University, 2018. p. 26
Keywords
cloud micro-physics, turbulence, inertial particles, DNS, condensation, collision, coalescence
National Category
Climate Research
Research subject
Atmospheric Sciences and Oceanography
Identifiers
urn:nbn:se:su:diva-158537 (URN)978-91-7797-358-4 (ISBN)978-91-7797-359-1 (ISBN)
Public defence
2018-09-21, Högbomsalen, Geovetenskapens hus, Svante Arrhenius väg 12, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
The Research Council of Norway, FRINATEK grant 231444
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Submitted. Paper 4: Manuscript. Paper 5: Submitted.

Available from: 2018-08-29 Created: 2018-08-08 Last updated: 2018-08-29Bibliographically approved

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