Preprints
https://doi.org/10.5194/egusphere-2022-1243
https://doi.org/10.5194/egusphere-2022-1243
 
22 Nov 2022
22 Nov 2022
Status: this preprint is open for discussion.

Breakups are Complicated: An Efficient Representation of Collisional Breakup in the Superdroplet Method

Emily de Jong1, John Ben Mackay2,3, Anna Jaruga2, and Sylwester Arabas4 Emily de Jong et al.
  • 1Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA, USA
  • 2Department of Environmental Science and Engineering, California Institute of Technology, Pasadena, CA, USA
  • 3Scripps Institution of Oceanography, San Diego, CA, USA
  • 4Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland

Abstract. A key constraint of particle-based methods for modeling cloud microphysics is the conservation of total particle number, which is required for computational tractability. The process of collisional breakup poses a particular challenge to this framework, as breakup events often produce many droplet fragments of varying sizes, which would require creating new particles in the system. This work introduces a representation of collisional breakup in the so-called "superdroplet" method which conserves the total number of superdroplets in the system. This representation extends an existing stochastic collisional-coalescence scheme and samples from a fragment-size distribution in an additional Monte Carlo step. This method is demonstrated in a set of idealized box model and single-column warm-rain simulations. We further discuss the effects of the breakup dynamic and fragment-size distribution on the particle size distribution, hydrometeor population, and microphysical process rates. This representation of collisional breakup is able to produce a stationary particle-size distribution, in which breakup and coalescence rates are approximately equal, and it recovers expected behavior such as precipitation suppression in the column model. Furthermore, representing breakup has potential benefits that extend beyond warm rain processes, such as the ability to capture mechanisms of secondary ice production in the superdroplet method. The breakup algorithm presented here contributes to an open-source pythonic implementation of the superdroplet method, `PySDM', which will facilitate future research using particle-based microphysics.

Emily de Jong et al.

Status: open (until 17 Jan 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'super-droplets make breakups easier', Axel Seifert, 28 Nov 2022 reply
    • AC1: 'Reply on CC1', Emily de Jong, 05 Dec 2022 reply

Emily de Jong et al.

Model code and software

PySDM Sylwester Arabas; Piotr Bartman; Emily de Jong; Clare Singer; Michael A. Olesik; Oleksii Bulenok; Ben Mackay; Sajjad Azimi; Kamil Górski; Anna Jaruga; Bartosz Piasecki; Codacy Badger https://zenodo.org/record/7306034#.Y3fwHuzMI-Q

PySDM-examples Sylwester Arabas; Clare Singer; Emily de Jong; Sajjad Azimi; Piotr Bartman; Oleksii Bulenok; imdula; Ben Mackay; Anna Jaruga; Wenhan Tang https://zenodo.org/record/7308668#.Y3fwHuzMI-Q

Emily de Jong et al.

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Short summary
In clouds, collisional breakup occurs when two colliding droplets splinter into new, smaller fragments. Particle-based modeling approaches often do not represent breakup because of the computational demands of creating new droplets. We present a particle-based breakup method that preserves the computational efficiency of these methods. In a series of simple demonstrations, we show that this representation alters cloud processes in reasonable and expected ways.