• Abade, G. C., W. W. Grabowski, and H. Pawlowska, 2018: Broadening of cloud droplet spectra through eddy hopping: Turbulent entraining parcel simulations. J. Atmos. Sci., 75, 33653379, https://doi.org/10.1175/JAS-D-18-0078.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ackerman, A. S., M. P. Kirkpatrick, D. E. Stevens, and O. B. Toon, 2004: The impact of humidity above stratiform clouds on indirect aerosol climate forcing. Nature, 432, 10141017, https://doi.org/10.1038/nature03174.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ackerman, A. S., and et al. , 2009: Large-eddy simulations of a drizzling, stratocumulus-topped marine boundary layer. Mon. Wea. Rev., 137, 10831110, https://doi.org/10.1175/2008MWR2582.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ahlm, L., A. Jones, C. W. Stjern, H. Muri, B. Kravitz, and J. E. Kristjánsson, 2017: Marine cloud brightening—As effective without clouds. Atmos. Chem. Phys., 17, 13 07113 087, https://doi.org/10.5194/acp-17-13071-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Albrecht, B. A., 1989: Aerosols, cloud microphysics, and fractional cloudiness. Science, 245, 12271230, https://doi.org/10.1126/science.245.4923.1227.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arrhenius, S., 1896: On the influence of carbonic acid in the air upon the temperature of the ground. Philos. Mag., 41, 237276, https://doi.org/10.1080/14786449608620846.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Betts, A. K., 2007: Coupling of water vapor convergence, clouds, precipitation, and land-surface processes. J. Geophys. Res., 112, D10108, https://doi.org/10.1029/2006JD008191.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C., P. N. Blossey, and J. Uchida, 2007: Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo. Geophys. Res. Lett., 34, L03813, https://doi.org/10.1029/2006GL027648.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bronshtein, I. N., K. A. Semendyayev, G. Musiol, and H. Mühlig, 2007: Handbook of Mathematics. Springer Science & Business Media, 1159 pp.

  • Chandrakar, K. K., W. Cantrell, K. Chang, D. Ciochetto, D. Niedermeier, M. Ovchinnikov, R. A. Shaw, and F. Yang, 2016: Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions. Proc. Natl. Acad. Sci. USA, 113, 14 24314 248, https://doi.org/10.1073/pnas.1612686113.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, J.-P., 1994: Theory of deliquescence and modified Köhler curves. J. Atmos. Sci., 51, 35053516, https://doi.org/10.1175/1520-0469(1994)051<3505:TODAMK>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, Y.-C., M. W. Christensen, G. L. Stephens, and J. H. Seinfeld, 2014: Satellite-based estimate of global aerosol–cloud radiative forcing by marine warm clouds. Nat. Geosci., 7, 643646, https://doi.org/10.1038/ngeo2214.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clark, T. L., 1973: Numerical modeling of the dynamics and microphysics of warm cumulus convection. J. Atmos. Sci., 30, 857878, https://doi.org/10.1175/1520-0469(1973)030<0857:NMOTDA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Connolly, P. J., G. B. McFiggans, R. Wood, and A. Tsiamis, 2014: Factors determining the most efficient spray distribution for marine cloud brightening. Philos. Trans. Roy. Soc., A372, 20140056, https://doi.org/10.1098/rsta.2014.0056.

    • Search Google Scholar
    • Export Citation
  • Cooper, G., D. Johnston, J. Foster, L. Galbraith, A. Neukermans, R. Ormond, J. Rush, and Q. Wang, 2013: A review of some experimental spray methods for marine cloud brightening. Int. J. Geosci., 4, 7897, https://doi.org/10.4236/ijg.2013.41009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cooper, G., J. Foster, L. Galbraith, S. Jain, A. Neukermans, and B. Ormond, 2014: Preliminary results for salt aerosol production intended for marine cloud brightening, using effervescent spray atomization. Philos. Trans. Roy. Soc., A372, 20140055, https://doi.org/10.1098/rsta.2014.0055.

    • Search Google Scholar
    • Export Citation
  • Cui, Z., A. Gadian, A. Blyth, J. Crosier, and I. Crawford, 2014: Observations of the variation in aerosol and cloud microphysics along the 20°S transect on 13 November 2008 during VOCALS-REx. J. Atmos. Sci., 71, 29272943, https://doi.org/10.1175/JAS-D-13-0245.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dziekan, P., and H. Pawlowska, 2017: Stochastic coalescence in Lagrangian cloud microphysics. Atmos. Chem. Phys., 17, 13 50913 520, https://doi.org/10.5194/acp-17-13509-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feingold, G., W. Cotton, B. Stevens, and A. Frisch, 1996: The relationship between drop in-cloud residence time and drizzle production in numerically simulated stratocumulus clouds. J. Atmos. Sci., 53, 11081122, https://doi.org/10.1175/1520-0469(1996)053<1108:TRBDIC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feingold, G., R. Boers, B. Stevens, and W. R. Cotton, 1997: A modeling study of the effect of drizzle on cloud optical depth and susceptibility. J. Geophys. Res., 102, 13 52713 534, https://doi.org/10.1029/97JD00963.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feingold, G., W. R. Cotton, S. M. Kreidenweis, and J. T. Davis, 1999: The impact of giant cloud condensation nuclei on drizzle formation in stratocumulus: Implications for cloud radiative properties. J. Atmos. Sci., 56, 41004117, https://doi.org/10.1175/1520-0469(1999)056<4100:TIOGCC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feingold, G., I. Koren, T. Yamaguchi, and J. Kazil, 2015: On the reversibility of transitions between closed and open cellular convection. Atmos. Chem. Phys., 15, 73517367, https://doi.org/10.5194/acp-15-7351-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ghan, S. J., G. Guzman, and H. Abdul-Razzak, 1998: Competition between sea salt and sulfate particles as cloud condensation nuclei. J. Atmos. Sci., 55, 33403347, https://doi.org/10.1175/1520-0469(1998)055<3340:CBSSAS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gillespie, D. T., 1975: An exact method for numerically simulating the stochastic coalescence process in a cloud. J. Atmos. Sci., 32, 19771989, https://doi.org/10.1175/1520-0469(1975)032<1977:AEMFNS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Glassmeier, F., F. Hoffmann, J. S. Johnson, T. Yamaguchi, K. S. Carslaw, and G. Feingold, 2021: Aerosol-cloud-climate cooling overestimated by ship-track data. Science, 371, 485489, https://doi.org/10.1126/science.abd3980.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Glenn, I. B., G. Feingold, J. J. Gristey, and T. Yamaguchi, 2020: Quantification of the radiative effect of aerosol–cloud interactions in shallow continental cumulus clouds. J. Atmos. Sci., 77, 29052920, https://doi.org/10.1175/JAS-D-19-0269.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gryspeerdt, E., and et al. , 2019: Constraining the aerosol influence on cloud liquid water path. Atmos. Chem. Phys., 19, 53315347, https://doi.org/10.5194/acp-19-5331-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartmann, D., and et al. , 2013: Observations: Atmosphere and surface. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 159–254.

  • Hoffmann, F., 2017: On the limits of Köhler activation theory: How do collision and coalescence affect the activation of aerosols? Atmos. Chem. Phys., 17, 83438356, https://doi.org/10.5194/acp-17-8343-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, F., 2020: Effects of entrainment and mixing on the Wegener–Bergeron–Findeisen process. J. Atmos. Sci., 77, 22792296, https://doi.org/10.1175/JAS-D-19-0289.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, F., and G. Feingold, 2019: Entrainment and mixing in stratocumulus: Effects of a new explicit subgrid-scale scheme for large-eddy simulations with particle-based microphysics. J. Atmos. Sci., 76, 19551973, https://doi.org/10.1175/JAS-D-18-0318.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, F., S. Raasch, and Y. Noh, 2015: Entrainment of aerosols and their activation in a shallow cumulus cloud studied with a coupled LCM-LES approach. Atmos. Res., 156, 4357, https://doi.org/10.1016/j.atmosres.2014.12.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, F., Y. Noh, and S. Raasch, 2017: The route to raindrop formation in a shallow cumulus cloud simulated by a Lagrangian cloud model. J. Atmos. Sci., 74, 21252142, https://doi.org/10.1175/JAS-D-16-0220.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, F., T. Yamaguchi, and G. Feingold, 2019: Inhomogeneous mixing in Lagrangian cloud models: Effects on the production of precipitation embryos. J. Atmos. Sci., 76, 113133, https://doi.org/10.1175/JAS-D-18-0087.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, F., F. Glassmeier, T. Yamaguchi, and G. Feingold, 2020: Liquid water path steady states in stratocumulus: Insights from process-level emulation and mixed-layer theory. J. Atmos. Sci., 77, 22032215, https://doi.org/10.1175/JAS-D-19-0241.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jenkins, A. K. L., P. M. Forster, and L. S. Jackson, 2013: The effects of timing and rate of marine cloud brightening aerosol injection on albedo changes during the diurnal cycle of marine stratocumulus clouds. Atmos. Chem. Phys., 13, 16591673, https://doi.org/10.5194/acp-13-1659-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jensen, J. B., and A. D. Nugent, 2017: Condensational growth of drops formed on giant sea-salt aerosol particles. J. Atmos. Sci., 74, 679697, https://doi.org/10.1175/JAS-D-15-0370.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kazil, J., T. Yamaguchi, and G. Feingold, 2017: Mesoscale organization, entrainment, and the properties of a closed-cell stratocumulus cloud. J. Adv. Model. Earth Syst., 9, 22142229, https://doi.org/10.1002/2017MS001072.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kerstein, A. R., 1988: A linear-eddy model of turbulent scalar transport and mixing. Combust. Sci. Technol., 60, 391421, https://doi.org/10.1080/00102208808923995.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M. F., and Y. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229243, https://doi.org/10.1175/1520-0493(2000)128<0229:ANCPPI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M. F., and D. A. Randall, 2003: Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities. J. Atmos. Sci., 60, 607625, https://doi.org/10.1175/1520-0469(2003)060<0607:CRMOTA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Khvorostyanov, V. I., and J. A. Curry, 1999: A simple analytical model of aerosol properties with account for hygroscopic growth: 1. Equilibrium size spectra and cloud condensation nuclei activity spectra. J. Geophys. Res., 104, 21752184, https://doi.org/10.1029/98JD02673.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Köhler, H., 1936: The nucleus in and the growth of hygroscopic droplets. Trans. Faraday Soc., 32, 11521161, https://doi.org/10.1039/TF9363201152.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamb, D., and J. Verlinde, 2011: Physics and Chemistry of Clouds. Cambridge University Press, 584 pp.

  • Lasher-Trapp, S. G., W. A. Cooper, and A. M. Blyth, 2005: Broadening of droplet size distributions from entrainment and mixing in a cumulus cloud. Quart. J. Roy. Meteor. Soc., 131, 195220, https://doi.org/10.1256/qj.03.199.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Latham, J., and M. Smith, 1990: Effect on global warming of wind-dependent aerosol generation at the ocean surface. Nature, 347, 372373, https://doi.org/10.1038/347372a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Latham, J., and et al. , 2012: Marine cloud brightening. Philos. Trans. Roy. Soc., A370, 42174262, https://doi.org/10.1098/rsta.2012.0086.

  • Lewis, E., and S. E. Schwartz, 2004: Sea Salt Aerosol Production: Mechanisms, Methods, Measurements, and Models. Geophys. Monogr., Vol. 152, Amer. Geophys. Union, 413 pp.

    • Crossref
    • Export Citation
  • Maahn, M., F. Hoffmann, M. D. Shupe, G. Boer, S. Y. Matrosov, and E. P. Luke, 2019: Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration? Atmos. Meas. Tech., 12, 31513171, https://doi.org/10.5194/amt-12-3151-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., 2000: Parameterization of the Mie extinction and absorption coefficients for water clouds. J. Atmos. Sci., 57, 13111326, https://doi.org/10.1175/1520-0469(2000)057<1311:POTMEA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mordy, W., 1959: Computations of the growth by condensation of a population of cloud droplets. Tellus, 11, 1644, https://doi.org/10.1111/j.2153-3490.1959.tb00003.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pinsky, M., and A. Khain, 2002: Effects of in-cloud nucleation and turbulence on droplet spectrum formation in cumulus clouds. Quart. J. Roy. Meteor. Soc., 128, 501533, https://doi.org/10.1256/003590002321042072.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Platnick, S., and S. Twomey, 1994: Determining the susceptibility of cloud albedo to changes in droplet concentration with the advanced very high resolution radiometer. J. Appl. Meteor. Climatol., 33, 334347, https://doi.org/10.1175/1520-0450(1994)033<0334:DTSOCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. 2nd ed. Kluwer Academic Publishers, 954 pp.

  • Qian, L., and J. Lin, 2011: Modeling on effervescent atomization: A review. Sci. China Phys. Mech. Astron., 54, 21092129, https://doi.org/10.1007/s11433-011-4536-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schwenkel, J., F. Hoffmann, and S. Raasch, 2018: Improving collisional growth in Lagrangian cloud models: Development and verification of a new splitting algorithm. Geosci. Model Dev., 11, 39293944, https://doi.org/10.5194/gmd-11-3929-2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sedunov, Y. S., 1974: Physics of Drop Formation in the Atmosphere. John Wiley and Sons, 234 pp.

  • Seinfeld, J. H., and S. N. Pandis, 2016: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. John Wiley and Sons, 1120 pp.

  • Shima, S.-I., K. Kusano, A. Kawano, T. Sugiyama, and S. Kawahara, 2009: 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. Quart. J. Roy. Meteor. Soc., 135, 13071320, https://doi.org/10.1002/qj.441.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevens, B., and G. Feingold, 2009: Untangling aerosol effects on clouds and precipitation in a buffered system. Nature, 461, 607613, https://doi.org/10.1038/nature08281.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Twomey, S., 1959: The nuclei of natural cloud formation. Part II: The supersaturation in natural clouds and the variation of cloud droplet concentration. Pure Appl. Geophys., 43, 243249, https://doi.org/10.1007/BF01993560.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Twomey, S., 1974: Pollution and the planetary albedo. Atmos. Environ., 8, 12511256, https://doi.org/10.1016/0004-6981(74)90004-3.

  • Twomey, S., 1977: The influence of pollution on the shortwave albedo of clouds. J. Atmos. Sci., 34, 11491152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Unterstrasser, S., F. Hoffmann, and M. Lerch, 2017: Collection/aggregation algorithms in Lagrangian cloud microphysical models: Rigorous evaluation in box model simulations. Geosci. Model Dev., 10, 15211548, https://doi.org/10.5194/gmd-10-1521-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Unterstrasser, S., F. Hoffmann, and M. Lerch, 2020: Collisional growth in a particle-based cloud microphysical model: Insights from column model simulations using LCM1D (v1. 0). Geosci. Model Dev., 13, 51195145, https://doi.org/10.5194/gmd-13-5119-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vaughan, N. E., and T. M. Lenton, 2011: A review of climate geoengineering proposals. Climatic Change, 109, 745790, https://doi.org/10.1007/s10584-011-0027-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Victor, D. G., D. Zhou, E. H. M. Ahmed, P. K. Dadhich, J. G. J. Olivier, H.-H. Rogner, K. Sheikho, and M. Yamaguchi, 2014: Introductory chapter. Climate Change 2014: Mitigation of Climate Change, O. Edenhofer et al., Ed., Cambridge University Press, 111–150, https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_chapter1.pdf.

  • Wang, H., P. J. Rasch, and G. Feingold, 2011: Manipulating marine stratocumulus cloud amount and albedo: A process-modelling study of aerosol-cloud-precipitation interactions in response to injection of cloud condensation nuclei. Atmos. Chem. Phys., 11, 42374249, https://doi.org/10.5194/acp-11-4237-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, S., Q. Wang, and G. Feingold, 2003: Turbulence, condensation, and liquid water transport in numerically simulated nonprecipitating stratocumulus clouds. J. Atmos. Sci., 60, 262278, https://doi.org/10.1175/1520-0469(2003)060<0262:TCALWT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Warner, J., 1973: The microstructure of cumulus cloud: Part IV. The effect on the droplet spectrum of mixing between cloud and environment. J. Atmos. Sci., 30, 256261, https://doi.org/10.1175/1520-0469(1973)030<0256:TMOCCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wood, R., 2012: Stratocumulus clouds. Mon. Wea. Rev., 140, 23732423, https://doi.org/10.1175/MWR-D-11-00121.1.

  • Wood, R., 2021: Assessing the potential efficacy of marine cloud brightening for cooling Earth using a simple heuristic model. Atmos. Chem. Phys., https://doi.org/10.5194/acp-2021-327, in press.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 140 140 140
Full Text Views 44 44 44
PDF Downloads 61 61 61

Cloud Microphysical Implications for Marine Cloud Brightening: The Importance of the Seeded Particle Size Distribution

View More View Less
  • 1 a Ludwig-Maximilans-Universität München, Meteorologisches Institut, Munich, Germany
  • | 2 b Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado
  • | 3 c Chemical Sciences Laboratory, NOAA/Earth System Research Laboratories, Boulder, Colorado
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

Marine cloud brightening (MCB) has been proposed as a viable way to counteract global warming by artificially increasing the albedo and lifetime of clouds via deliberate seeding of aerosol particles. Stratocumulus decks, which cover wide swaths of Earth’s surface, are considered the primary target for this geoengineering approach. The macroscale properties of this cloud type exhibit a high sensitivity to cloud microphysics, exposing the potential for undesired changes in cloud optical properties in response to MCB. In this study, we apply a highly detailed Lagrangian cloud model, coupled to an idealized parcel model as well as a full three-dimensional large-eddy simulation model, to show that the choice of seeded particle size distribution is crucial to the success of MCB, and that its efficacy can be significantly reduced by undesirable microphysical processes. The presence of even a small number of large particles in the seeded size spectrum may trigger significant precipitation, which will reduce cloud water and may even break up the cloud deck, reducing the scene albedo and hence counteracting MCB. On the other hand, a seeded spectrum comprising a large number of small particles reduces the fraction of activated cloud droplets and increases entrainment and evaporation of cloud water, which also reduces the efficiency of MCB. In between, there may exist an aerosol size distribution that minimizes undesirable microphysical processes and enables optimal MCB. This optimal size distribution is expected to be case dependent.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fabian Hoffmann, fa.hoffmann@lmu.de

Abstract

Marine cloud brightening (MCB) has been proposed as a viable way to counteract global warming by artificially increasing the albedo and lifetime of clouds via deliberate seeding of aerosol particles. Stratocumulus decks, which cover wide swaths of Earth’s surface, are considered the primary target for this geoengineering approach. The macroscale properties of this cloud type exhibit a high sensitivity to cloud microphysics, exposing the potential for undesired changes in cloud optical properties in response to MCB. In this study, we apply a highly detailed Lagrangian cloud model, coupled to an idealized parcel model as well as a full three-dimensional large-eddy simulation model, to show that the choice of seeded particle size distribution is crucial to the success of MCB, and that its efficacy can be significantly reduced by undesirable microphysical processes. The presence of even a small number of large particles in the seeded size spectrum may trigger significant precipitation, which will reduce cloud water and may even break up the cloud deck, reducing the scene albedo and hence counteracting MCB. On the other hand, a seeded spectrum comprising a large number of small particles reduces the fraction of activated cloud droplets and increases entrainment and evaporation of cloud water, which also reduces the efficiency of MCB. In between, there may exist an aerosol size distribution that minimizes undesirable microphysical processes and enables optimal MCB. This optimal size distribution is expected to be case dependent.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Fabian Hoffmann, fa.hoffmann@lmu.de
Save