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Hail suppression effectiveness for varying solubility of natural aerosols in water

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A Correction to this article was published on 16 April 2018

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Abstract

This sensitivity study examined the impact of natural aerosol on the results obtained by numerical cloud seeding experiments focused on hail suppression on the ground. A main concern was investigating the effects of the solubility of the natural aerosol on unseeded and seeded cloud simulations. A numerical model with a two-moment bulk microphysical scheme was used for this purpose. The numerical model calculated the mass and number concentrations of the following seven microphysical categories: cloud water, rain, cloud ice, snow, graupel, frozen raindrops and hail. The solubility values of the natural aerosol in water were varied, and the rain and hail production in clouds and the corresponding surface precipitation were analysed in unseeded and seeded cases. The effectiveness of hail suppression on the ground is reduced in atmospheric environments with natural aerosols that are less soluble in water. A low solubility of natural aerosol in water can result in overseeding. The sensitivity study showed that environments with predominantly soluble aerosol particles (such as sodium chloride) were suitable for hail suppression with a simultaneous increase in surface rain.

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  • 16 April 2018

    Because of a production error, the black line in Figure 13c is incorrect. The correct Figure 13c is shown below.

References

  • Abshaev GK, Sulakvelidze II, Burtsev LM, Fedchenko MK, Jekamukhov AM, Abshaev BK, Kuznetsov AM, Malkarova AD, Tebuev PA, Nesmeyanov II, Shakirov IN, Shevela GF (2006) Development of rocket and artillery technology for hail suppression. In: Achievements in weather modification. Department of Atmospheric studies, Abu Dhabi:109–127

  • Chen B, Xiao H (2010) Silver iodide seeding impact on the microphysics and dynamics of convective clouds in the high plains. Atmos Res 96:186–207

    Article  Google Scholar 

  • Cohard J-M, Pinty J-P (2000) A comprehensive two-moment warm microphysical bulk scheme. I: description and tests. Q J R Meteorol Soc 126:1815–1842

    Article  Google Scholar 

  • Cohard J-M, Pinty J-P, Bedos C (1998) Extending Twomey’s analytical estimate of nucleated cloud droplet concentrations from CCN spectra. J Atmos Sci 55(22):3348–3357

    Article  Google Scholar 

  • Cohard J-M, Pinty J-P, Suhre K (2000) On the parameterization of activation spectra from cloud condensation nuclei microphysical properties. J Geo Res 105(D9):11753–11766

    Article  Google Scholar 

  • Ćurić M, Janc D, Vučković V (1998) On the sensitivity of cloud microphysics under influence of cloud drop size distribution. Atmos Res 47–48:1–14

    Google Scholar 

  • Ćurić M, Janc D, Vučković V (2006) Seeding agent dispersion within convective cloud as simulated by a 3-D numerical model. Meteorol Atmos Phys 92:205–216

    Article  Google Scholar 

  • Ćurić M, Janc D, Vučković V (2007) Cloud seeding impact on precipitation as revealed by cloud-resolving mesoscale model. Meteorol Atmos Phys 95:179–193

    Article  Google Scholar 

  • Ćurić M, Janc D, Vučković V, Kovačević N (2009) An inadvertent transport of the seeding material as a result of cloud modification. Meteorol Atmos Phys 105:157–165

    Article  Google Scholar 

  • Dessens J, Sanchez JL, Berthet C, Hermida L, Merino A (2016) Hail prevention by ground-based silver iodide generators: results of historical and modern field projects. Atmos Res 170:98–111

    Article  Google Scholar 

  • Fletcher NH (1962) The physics of rainclouds, 1st edn. Cambridge University Press, Cambridge, p 386

    Google Scholar 

  • Gradshteyn IS, Ryzhik IM (2007) Table of integrals, series and products. Academic Press, New York, p 1171

    Google Scholar 

  • Guo X, Zheng G, Jin D (2006) A numerical comparison study of cloud seeding by silver iodide and liquid carbon dioxide. Atmos Res 79:183–226

    Article  Google Scholar 

  • Hu Z, He G (1988) Numerical simulation of microphysical processes in cumulonimbus—part I: microphysical model. Acta Meteorol Sin 2:471–489

    Google Scholar 

  • Jaenicke R (1993) Tropospheric Aerosol. In: Hobbs PV (ed) Aerosol-cloud-climate interactions. Academic Press, San Diego, pp 1–31

    Google Scholar 

  • Kim CK, Yum SS, Oh S-N, Nam J-C, Chang K-H (2005) A feasibility study of winter orographic cloud seeding experiments in the Korean Peninsula. J Korean Meteor Soc 41(6):997–1014

    Google Scholar 

  • Kim CK, Yum SS, Park Y-S (2016) A numerical study of winter orographic seeding experiments in Korea using the Weather Research and Forecasting model. Meteorol Atmos Phys 128:23–38

    Article  Google Scholar 

  • Klemp JB, Wilhelmson RB (1978) The simulation of three-dimensional convective storm dynamics. J Atmos Sci 35:1070–1096

    Article  Google Scholar 

  • Kovačević N, Ćurić M (2013) The impact of the hailstone embryos on simulated surface precipitation. Atmos Res 132–133:154–163

    Google Scholar 

  • Kovačević N, Ćurić M (2014) Sensitivity study of the influence of cloud droplet concentration on hail suppression effectiveness. Meteorol Atmos Phys 123:195–207

    Article  Google Scholar 

  • Krauss TW (2003) Aircraft seeding technology and some outstanding issues of hail suppression Meeting of experts on hail suppression (in collaboration with Roshydromet), World Meteorological Organization, pp 57–61 (WMP 41, WMO/TD 1233)

  • Lin Y-L, Farley RD, Orville HD (1983) Bulk parameterization of the snow field in a cloud model. J Appl Meteor 22:1065–1092

    Article  Google Scholar 

  • Mesinger F, Mesinger N (1992) Has hail suppression in eastern Yugoslavia led to a reduction in the frequency of hail? J Appl Meteorol 31:104–111

    Article  Google Scholar 

  • Meyers MP, DeMott PJ, Cotton WR (1995) A comparison of seeded and nonseeded orographic cloud simulations with an explicit cloud model. J Appl Meteor 34:834–846

    Article  Google Scholar 

  • Meyers MP, Walko RL, Harrington JY, Cotton WR (1997) New RAMS cloud microphysics parameterization. Part II: The two-moment scheme. Atmos Res 45(1):3–39

    Article  Google Scholar 

  • Murakami M (1990) Numerical modeling of dynamical and microphysical evolution of an isolated convective cloud—the 19 July 1981 CCOPE cloud. J Meteorol Soc Jpn 68:107–127

    Article  Google Scholar 

  • Orville HD (1996) A review of cloud modeling in weather modification. Bull Am Meteor Soc 77:1535–1555

    Article  Google Scholar 

  • Pokharel B, Geerts B, Jing X, Friedrich K, Ikeda K, Rasmussen R (2017) A multi-sensor study of the impact of ground-based glaciogenic seeding on clouds and precipitation over mountains in Wyoming. Part II: seeding impact analysis. Atmos Res 183:42–57

    Article  Google Scholar 

  • Pruppacher HR, Klett JD (1997) Microphysics of clouds and precipitation, 2nd edn. Kluwer, Dordrecht, p 954

    Google Scholar 

  • Tao WK, Simpson J, McCumber M (1989) An ice-water saturation adjustment. Mon Weather Rev 117(1):231–235

    Article  Google Scholar 

  • Wang G, Lou X, Hu Z, You L, Feng D, Zhang J, Shi A, Li S, Guo E, Wang Y, Fang W, Shi Y, Sun J (2006) Main achievements of Institute of Weather Modification. Department of Atmospheric studies, Abu Dhabi:131–141

  • Wisner C, Orville HD, Myers C (1972) A numerical model of a hail-bearing cloud. J Atmos Sci 29:1160–1181

    Article  Google Scholar 

  • Xue L, Tessendorf SA, Nelson E, Rasmussen R, Breed D, Parkinson S, Holbrook P, Blestrud D (2013) Implementation of a silver iodide cloud-seeding parameterization in WRF. Part II: 3D simulations of actual seeding events and sensitivity test. J Appl Meteor Clim 52(6):1458–1476

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the Ministry of Education, Science and Technological Development of Serbia under Grant no. 176013.

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  1. Faculty of Physics, Institute of Meteorology, University of Belgrade, 16 Dobračina, 11000, Belgrade, Serbia

    Nemanja Kovačević

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  1. Nemanja Kovačević
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Correspondence to Nemanja Kovačević.

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Responsible Editor: Responsible Editor: S.-W. Kim.

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Kovačević, N. Hail suppression effectiveness for varying solubility of natural aerosols in water. Meteorol Atmos Phys 131, 585–599 (2019). https://doi.org/10.1007/s00703-018-0587-4

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