Articles | Volume 25, issue 10
https://doi.org/10.5194/acp-25-5313-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-5313-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 May 2025
Research article |
| 27 May 2025
| 27 May 2025
The critical number and size of precipitation embryos to accelerate warm rain initiation
Jung-Sub Lim
Meteorologisches Institut München, Ludwig-Maximilians-Universität, Munich, Germany
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea
now at: NOAA Chemical Science Laboratory (CSL), Boulder, CO, USA
now at: Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, USA
Yign Noh
CORRESPONDING AUTHOR
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea
Hyunho Lee
Department of Atmospheric Science, Kongju National University, Gongju-si, Republic of Korea
Meteorologisches Institut München, Ludwig-Maximilians-Universität, Munich, Germany
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Cited articles
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. a
Alfonso, L., Raga, G. B., and Baumgardner, D.: The validity of the kinetic collection equation revisited – Part 3: Sol–gel transition under turbulent conditions, Atmos. Chem. Phys., 13, 521–529, https://doi.org/10.5194/acp-13-521-2013, 2013. a, b
Alfonso, L., Raga, G. B., and Baumgardner, D.: The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 2: Observational evidence of gel formation in warm clouds, Atmos. Chem. Phys., 19, 14917–14932, https://doi.org/10.5194/acp-19-14917-2019, 2019. a, b
Ayala, O., Rosa, B., and Wang, L.-P.: Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization, New J. Phys., 10, 075016, https://doi.org/10.1088/1367-2630/10/9/099802, 2008. a
Baker, M., Corbin, R., and Latham, J.: The influence of entrainment on the evolution of cloud droplet spectra: I. A model of inhomogeneous mixing, Q. J. Roy. Meteor. Soc., 106, 581–598, https://doi.org/10.1002/qj.49710644914, 1980. a
Beard, K. V.: Terminal velocity and shape of cloud and precipitation drops aloft, J. Atmos. Sci., 33, 851–864, 1976. a
Blyth, A. M.: Entrainment in cumulus clouds, J. Appl. Meteorol. Clim., 32, 626–641, https://doi.org/10.1175/1520-0450(1993)032<0626:EICC>2.0.CO;2, 1993. a, b
Chandrakar, K. K., Morrison, H., Grabowski, W. W., and Lawson, R. P.: Are turbulence effects on droplet collision–coalescence a key to understanding observed rain formation in clouds?, P. Natl. Acad. Sci. USA, 121, e2319664121, https://doi.org/10.1073/pnas.2319664121, 2024. a, b, c
Chen, S., Xue, L., and Yau, M.-K.: Impact of aerosols and turbulence on cloud droplet growth: an in-cloud seeding case study using a parcel–DNS (direct numerical simulation) approach, Atmos. Chem. Phys., 20, 10111–10124, https://doi.org/10.5194/acp-20-10111-2020, 2020. a, b, c
Cooper, W. A., Lasher-Trapp, S. G., and Blyth, A. M.: The influence of entrainment and mixing on the initial formation of rain in a warm cumulus cloud, J. Atmos. Sci., 70, 1727–1743, 2013. a
Devenish, B., Bartello, P., Brenguier, J., Collins, L., Grabowski, W. W., IJzermans, R., Malinowski, S. P., Reeks, M., Vassilicos, J., and Wang, L.: Droplet growth in warm turbulent clouds, Q. J. Roy. Meteor. Soc., 138, 1401–1429, https://doi.org/10.1002/qj.1897, 2012. a
Exton, H., Latham, J., Park, P., Smith, M., and Allan, R.: The production and dispersal of maritime aerosol, in: Oceanic Whitecaps, Springer Netherlands, ISBN 9789400946682, 175–193, https://doi.org/10.1007/978-94-009-4668-2_17, 1986. a
Feingold, G., Cotton, W. R., Kreidenweis, S. M., and Davis, J. T.: The impact of giant cloud condensation nuclei on drizzle formation in stratocumulus: Implications for cloud radiative properties, J. Atmos. Sci., 56, 4100–4117, https://doi.org/10.1175/1520-0469(1999)056<4100:TIOGCC>2.0.CO;2, 1999. a, b, c, d, e
Gillespie, D. T.: The stochastic coalescence model for cloud droplet growth, J. Atmos. Sci., 29, 1496–1510, https://doi.org/10.1175/1520-0469(1972)029<1496:TSCMFC>2.0.CO;2, 1972. a
Grabowski, W. W. and Wang, L.-P.: Growth of cloud droplets in a turbulent environment, Annu. Rev. Fluid Mech., 45, 293–324, https://doi.org/10.1146/annurev-fluid-011212-140750, 2013. a, b
Hall, W. D.: A detailed microphysical model within a two-dimensional dynamic framework: model description and preliminary results, J. Atmos. Sci., 37, 2486–2507, https://doi.org/10.1175/1520-0469(1980)037<2486:ADMMWA>2.0.CO;2, 1980. a
Hoffmann, F. and Feingold, G.: Cloud microphysical implications for marine cloud brightening: the importance of the seeded particle size distribution, J. Atmos. Sci., 78, 3247–3262, https://doi.org/10.1175/jas-d-21-0077.1, 2021. a
Hoffmann, F. and Feingold, G.: A note on aerosol processing by droplet collision-coalescence, Geophys. Res. Lett., 50, e2023GL103716, https://doi.org/10.1029/2023gl103716, 2023. a
Hoffmann, F., Yamaguchi, T., and Feingold, G.: Inhomogeneous mixing in Lagrangian cloud models: effects on the production of precipitation embryos, J. Atmos. Sci., 76, 113–133, https://doi.org/10.1175/jas-d-18-0087.1, 2019. a
Hudson, J. G. and Noble, S.: CCN spectral shape and cumulus cloud and drizzle microphysics, J. Geophys. Res.-Atmos., 125, e2019JD031141, https://doi.org/10.1029/2019jd031141, 2020. a
Ivanova, E., Kogan, Y., Mazin, I., and Permyakov, M.: The ways of parameterization of condensation drop growth in numerical models, Izv. Atmos. Ocean. Phys.+, 13, 1193–1201, 1977. a
Jensen, J. B. and Nugent, A. D.: Condensational growth of drops formed on giant sea-salt aerosol particles, J. Atmos. Sci., 74, 679–697, https://doi.org/10.1175/jas-d-15-0370.1, 2017. a, b
Johnson, D. B.: The role of giant and ultragiant aerosol particles in warm rain initiation, J. Atmos. Sci., 39, 448–460, https://doi.org/10.1175/1520-0469(1982)039<0448:TROGAU>2.0.CO;2, 1982. a, b, c
Jung, E., Albrecht, B. A., Jonsson, H. H., Chen, Y.-C., Seinfeld, J. H., Sorooshian, A., Metcalf, A. R., Song, S., Fang, M., and Russell, L. M.: Precipitation effects of giant cloud condensation nuclei artificially introduced into stratocumulus clouds, Atmos. Chem. Phys., 15, 5645–5658, https://doi.org/10.5194/acp-15-5645-2015, 2015. a, b, c, d, e
Khain, A.: Notes on state-of-the-art investigations of aerosol effects on precipitation: a critical review, Environ. Res. Lett., 4, 015004, https://doi.org/10.1088/1748-9326/4/1/015004, 2009. a, b
Krueger, S. K., Su, C.-W., and McMurtry, P. A.: Modeling entrainment and finescale mixing in cumulus clouds, J. Atmos. Sci., 54, 2697–2712, https://doi.org/10.1175/1520-0469(1997)054<2697:MEAFMI>2.0.CO;2, 1997. a
Kuba, N. and Murakami, M.: Effect of hygroscopic seeding on warm rain clouds – numerical study using a hybrid cloud microphysical model, Atmos. Chem. Phys., 10, 3335–3351, https://doi.org/10.5194/acp-10-3335-2010, 2010. a, b, c
Lasher-Trapp, S. G., Cooper, W. A., and Blyth, A. M.: Broadening of droplet size distributions from entrainment and mixing in a cumulus cloud, Q. J. Roy. Meteor. Soc., 131, 195–220, 2005. a
Latham, J., Bower, K., Choularton, T., Coe, H., Connolly, P., Cooper, G., Craft, T., Foster, J., Gadian, A., Galbraith, L., Iacovides, H., Johnston, D., Launder, B., Leslie, B., Meyer, J., Neukermans, A., Ormond, B., Parkes, B., Rasch, P., Rush, J., Salter, S., Stevenson, T., Wang, H., Wang, Q., and Wood, R.: Marine cloud brightening, Philos. T. Roy. Soc. A, 370, 4217–4262, 2012. a
Lim, J.-S. and Hoffmann, F.: Between broadening and narrowing: how mixing affects the width of the droplet size distribution, J. Geophys. Res.-Atmos., 128, e2022JD037900, https://doi.org/10.1029/2022jd037900, 2023. a
Lim, J.-S. and Hoffmann, F.: Life cycle evolution of mixing in shallow cumulus clouds, J. Geophys. Res.-Atmos., 129, e2023JD040393, https://doi.org/10.1029/2023jd040393, 2024. a
Lim, J.-S. and Hoffmann, F.: jslim93/PyLCM_edu: ACP_paper_v1.0.0 (Paper), Zenodo [code], https://doi.org/10.5281/zenodo.15468311, 2025. a
Low, T. B. and List, R.: Collision, coalescence and breakup of raindrops. Part I: Experimentally established coalescence efficiencies and fragment size distributions in breakup, J. Atmos. Sci., 39, 1591–1606, 1982. a
Noh, Y., Oh, D., Hoffmann, F., and Raasch, S.: A cloud microphysics parameterization for shallow cumulus clouds based on Lagrangian cloud model simulations, J. Atmos. Sci., 75, 4031–4047, https://doi.org/10.1175/JAS-D-18-0080.1, 2018. a
O'Dowd, C. D., Smith, M. H., Consterdine, I. E., and Lowe, J. A.: Marine aerosol, sea-salt, and the marine sulphur cycle: a short review, Atmos. Environ., 31, 73–80, https://doi.org/10.1016/S1352-2310(96)00106-9, 1997. a
Onishi, R., Matsuda, K., and Takahashi, K.: Lagrangian tracking simulation of droplet growth in turbulence–turbulence enhancement of autoconversion rate, J. Atmos. Sci., 72, 2591–2607, https://doi.org/10.1175/JAS-D-14-0292.1, 2015. a, b
Pinsky, M., Khain, A., and Krugliak, H.: Collisions of cloud droplets in a turbulent flow. Part V: Application of detailed tables of turbulent collision rate enhancement to simulation of droplet spectra evolution, J. Atmos. Sci., 65, 357–374, https://doi.org/10.1175/2007jas2358.1, 2008. a, b
Pruppacher, H. R. and Klett, J. D.: Microphysics of Clouds and Precipitation: Reprinted 1980, Springer Dordrecht, ISBN 978-90-277-1106-9, https://doi.org/10.1007/978-94-009-9905-3, 1980. a, b
Saffman, P. and Turner, J.: On the collision of drops in turbulent clouds, J. Fluid Mech., 1, 16–30, 1956. a
Seifert, A., Nuijens, L., and Stevens, B.: Turbulence effects on warm-rain autoconversion in precipitating shallow convection, Q. J. Roy. Meteor. Soc., 136, 1753–1762, https://doi.org/10.1002/qj.684, 2010. a
Shaw, R. A.: Particle-turbulence interactions in atmospheric clouds, Annu. Rev. Fluid Mech., 35, 183–227, 2003. a
Shima, S.-I., Kusano, K., Kawano, A., Sugiyama, T., and Kawahara, S.: The super droplet method for the numerical simulation of clouds and precipitation: a particle based and probabilistic microphysics model coupled with a non hydrostatic model, Q. J. Roy. Meteor. Soc., 135, 1307–1320, https://doi.org/10.1002/qj.441, 2009. a, b, c, d
Siebert, H., Lehmann, K., and Wendisch, M.: Observations of small-scale turbulence and energy dissipation rates in the cloudy boundary layer, J. Atmos. Sci., 63, 1451–1466, https://doi.org/10.1175/JAS3687.1, 2006. a
Squires, P.: The microstructure and colloidal stability of warm clouds: Part I – The relation between structure and stability, Tellus, 10, 256–261, 1958. a
Sölch, I. and Kärcher, B.: A large eddy model for cirrus clouds with explicit aerosol and ice microphysics and Lagrangian ice particle tracking, Q. J. Roy. Meteor. Soc., 136, 2074–2093, https://doi.org/10.1002/qj.689, 2010. a
Telford, J.: A new aspect of coalescence theory, J. Meteorol., 12, 436–444, https://doi.org/10.1175/1520-0469(1955)012<0436:ANAOCT>2.0.CO;2, 1955. a, b, c, d
Teller, A. and Levin, Z.: The effects of aerosols on precipitation and dimensions of subtropical clouds: a sensitivity study using a numerical cloud model, Atmos. Chem. Phys., 6, 67–80, https://doi.org/10.5194/acp-6-67-2006, 2006. a, b
Unterstrasser, S., Hoffmann, F., and Lerch, M.: Collisional growth in a particle-based cloud microphysical model: insights from column model simulations using LCM1D (v1.0), Geosci. Model Dev., 13, 5119–5145, https://doi.org/10.5194/gmd-13-5119-2020, 2020. a, b
Wang, L. and Grabowski, W. W.: The role of air turbulence in warm rain initiation, Atmos. Sci. Lett., 10, 1–8, https://doi.org/10.1002/asl.210, 2009. a, b
Wang, L., Xue, Y., Ayala, O., and Grabowski, W. W.: Effects of stochastic coalescence and air turbulence on the size distribution of cloud droplets, Atmos. Res., 82, 416–432, https://doi.org/10.1016/j.atmosres.2005.12.011, 2006. a
Wilkinson, M.: Large deviation analysis of rapid onset of rain showers, Phys. Rev. Lett., 116, 018501, https://doi.org/10.1103/PhysRevLett.116.018501, 2016. a
Woodcock, A. H.: Salt nuclei in marine air as a function of altitude and wind force, J. Atmos. Sci., 10, 362–371, https://doi.org/10.1175/1520-0469(1953)010<0366:SNIMAA>2.0.CO;2, 1953. a, b
Yin, Y., Levin, Z., Reisin, T. G., and Tzivion, S.: The effects of giant cloud condensation nuclei on the development of precipitation in convective clouds – a numerical study, Atmos. Res., 53, 91–116, https://doi.org/10.1016/S0169-8095(99)00046-0, 2000. a
Short summary
Rain formation in warm clouds begins when small droplets collide, but this process can be slow without larger droplets. We used simulations to explore the role of bigger droplets, known as precipitation embryos, in triggering rain. We found that they speed up rain only when their size and number exceed a critical threshold. This threshold becomes larger when collisions are naturally efficient, such as in clouds with broad droplet size distributions or strong turbulence.
Rain formation in warm clouds begins when small droplets collide, but this process can be slow...
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