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Peter J. Marinescu, Susan C. van den Heever, Max Heikenfeld, Andrew I. Barrett, Christian Barthlott, Corinna Hoose, Jiwen Fan, Ann M. Fridlind, Toshi Matsui, Annette K. Miltenberger, Philip Stier, Benoit Vie, Bethan A. White, and Yuwei Zhang

; Fan et al. 2009 ; Lebo and Seinfeld 2011 ; Barthlott and Hoose 2018 ), contradictory to the invigoration concepts described above. Even for one of the most established concepts on the interactions of aerosol particles with deep convective clouds, the results appear to be muddled due to the complex kinematic and microphysics processes and feedbacks in deep convection. These seemingly conflicting results have been attributed to the many differences between the various studies. For example, the

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Wojciech W. Grabowski

describing aerosol, cloud, and precipitation particles) in a single cloud-field simulation. The first set is coupled to the dynamics and drives the simulation (set D, as in “driving”), and the second set piggybacks the simulated flow and does not affect it (set P, as in “piggybacking”). From the point of view of the P set of thermodynamic variables, the piggybacking is similar to the kinematic model approach, that is, using thermodynamic variables within a prescribed flow (e.g., Szumowski et al. 1998

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Wojciech W. Grabowski and Hugh Morrison

deposition and the other including that grown by riming. The third prognostic ice variable is the number mixing ratio of ice particles. This approach allows for representing the gradual transition from small to large ice particles due to growth by water vapor deposition and aggregation, and from unrimed crystals to rimed ice particles and eventually to graupel due to riming. The scheme was used in Slawinska et al. (2009) in kinematic model simulations of deep organized convection, in Grabowski and

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Eyal Ilotoviz, Alexander P. Khain, Nir Benmoshe, Vaughan T. J. Phillips, and Alexander V. Ryzhkov

hail growth was noted by Nelson (1983) as well. This researcher analyzed multiple-Doppler data and used a simple particle growth model in which a hail embryo grows within a given field of vertical velocity and cloud water content. Tessendorf et al. (2005) analyzed the kinematics and microphysics of the 29 June supercell storm observed during the Severe Thunderstorm Electrification and Precipitation Study (STEPS) field campaign using polarimetric and Doppler radar data. They found that most of

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Tianmeng Chen, Jianping Guo, Zhanqing Li, Chuanfeng Zhao, Huan Liu, Maureen Cribb, Fu Wang, and Jing He

. Atmos. Phys. , 119 , 17 – 29 , doi: 10.1007/s00703-012-0221-9 . Yuan , T. , Z. Li , R. Zhang , and J. Fan , 2008 : Increase of cloud droplet size with aerosol optical depth: An observation and modeling study . J. Geophys. Res. , 113 , D04201 , doi: 10.1029/2007JD008632 . Yuter , S. E. , and R. A. Houze Jr. , 1995 : Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and

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