Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4107-2020
https://doi.org/10.5194/gmd-13-4107-2020
Development and technical paper
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08 Sep 2020
Development and technical paper | Highlight paper |  | 08 Sep 2020

Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2

Shin-ichiro Shima, Yousuke Sato, Akihiro Hashimoto, and Ryohei Misumi

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Cited articles

Abade, G. C., Grabowski, W. W., and Pawlowska, H.: Broadening of cloud droplet spectra through eddy hopping: Turbulent entraining parcel simulations, J. Atmos. Sci., 75, 3365–3379, https://doi.org/10.1175/JAS-D-18-0078.1, 2018. a, b, c
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Andrejczuk, M., Grabowski, W. W., Reisner, J., and Gadian, A.: Cloud-aerosol interactions for boundary layer stratocumulus in the Lagrangian Cloud Model, J. Geophys. Res.-Atmos., 115, D22214, https://doi.org/10.1029/2010JD014248, 2010. a, b, c
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Short summary
Using the super-droplet method, we constructed a detailed numerical model of mixed-phase clouds based on kinetic description and subsequently demonstrated that a large-eddy simulation of a cumulonimbus which predicts ice particle morphology without assuming ice categories or mass–dimension relationships is possible. Our results strongly support the particle-based modeling methodology’s efficacy for simulating mixed-phase clouds.