Articles | Volume 19, issue 23
https://doi.org/10.5194/acp-19-14917-2019
https://doi.org/10.5194/acp-19-14917-2019
Research article
 | 
10 Dec 2019
Research article |  | 10 Dec 2019

The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 2: Observational evidence of gel formation in warm clouds

Lester Alfonso, Graciela B. Raga, and Darrel Baumgardner

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Cited articles

Aldous, D. J.: Deterministic and stochastic models for coalescence (aggregation, coagulation): A review of the mean-field theory for probabilistic, Bernoulli, 5, 3–48, 1999. 
Alfonso, L.: An algorithm for the numerical solution of the multivariate master equation for stochastic coalescence, Atmos. Chem. Phys., 15, 12315–12326, https://doi.org/10.5194/acp-15-12315-2015, 2015. 
Alfonso, L. and Raga, G. B.: The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 1: Numerical calculation of post-gel droplet size distribution, Atmos. Chem. Phys., 17, 6895–6905, https://doi.org/10.5194/acp-17-6895-2017, 2017. 
Alfonso, L., Raga, G. B., and Baumgardner, D.: The validity of the kinetic collection equation revisited, Atmos. Chem. Phys., 8, 969–982, https://doi.org/10.5194/acp-8-969-2008, 2008. 
Alfonso, L., Raga, G. B., and Baumgardner, D.: The validity of the kinetic collection equation revisited – Part 2: Simulations for the hydrodynamic kernel, Atmos. Chem. Phys., 10, 7189–7195, https://doi.org/10.5194/acp-10-7189-2010, 2010. 
Short summary
The aim of this paper is to find some observational evidence of gel formation in clouds, by analyzing the distribution of the largest droplet at an early stage of cloud formation, and to show that the mass of the gel (lucky droplet) is a mixture of Gaussian and Gumbel distributions. The results obtained may help advance the understanding of precipitation formation and are a novel application of the theory of critical phenomena in cloud physics.
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