Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4107-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-13-4107-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| Highlight paper
| 
08 Sep 2020
Development and technical paper | Highlight paper |
| 08 Sep 2020
| 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
CORRESPONDING AUTHOR
Graduate School of Simulation Studies, University of Hyogo, Kobe, Japan
RIKEN Center for Computational Science, Kobe, Japan
Yousuke Sato
Faculty of Science, Hokkaido University, Sapporo, Japan
RIKEN Center for Computational Science, Kobe, Japan
Akihiro Hashimoto
Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan
Ryohei Misumi
National Research Institute for Earth Science and Disaster Resilience, Tsukuba, Japan
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25 citations as recorded by crossref.
- New developments in PySDM and PySDM-examples v2: collisional breakup, immersion freezing, dry aerosol initialization, and adaptive time-stepping E. de Jong et al. https://doi.org/10.21105/joss.04968
- Supersaturation, buoyancy, and deep convection dynamics W. Grabowski & H. Morrison https://doi.org/10.5194/acp-21-13997-2021
- Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1 P. Zmijewski et al. https://doi.org/10.5194/gmd-17-759-2024
- Persistent mixed‐phase states in adiabatic cloud parcels under idealised conditions G. Abade & D. Albuquerque https://doi.org/10.1002/qj.4775
- Between Broadening and Narrowing: How Mixing Affects the Width of the Droplet Size Distribution J. Lim & F. Hoffmann https://doi.org/10.1029/2022JD037900
- Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1 C. Yin et al. https://doi.org/10.5194/gmd-17-5167-2024
- An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n‐Moment Bulk Microphysics Scheme M. Bieli et al. https://doi.org/10.1029/2022MS002994
- Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign S. Park et al. https://doi.org/10.5194/gmd-17-7199-2024
- Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme T. Lüttmer et al. https://doi.org/10.5194/acp-25-4505-2025
- Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions Y. Liu et al. https://doi.org/10.1007/s00376-022-2077-3
- Super‐Droplet Method to Simulate Lagrangian Microphysics of Nuclear Fallout in a Homogeneous Cloud D. McGuffin et al. https://doi.org/10.1029/2022JD036599
- Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0 R. Zhang et al. https://doi.org/10.5194/gmd-17-6761-2024
- snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation D. Ori et al. https://doi.org/10.5194/gmd-14-1511-2021
- Pathways from nucleation to raindrops F. Poydenot & B. Andreotti https://doi.org/10.1103/PhysRevFluids.9.123602
- Breakups are complicated: an efficient representation of collisional breakup in the superdroplet method E. de Jong et al. https://doi.org/10.5194/gmd-16-4193-2023
- Resolving Entrainment–Mixing in Marine Stratocumulus: The Role of LES Grid Resolution and Super-Droplet Number C. Yin et al. https://doi.org/10.1007/s00376-025-5043-z
- Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets Y. Sun et al. https://doi.org/10.5194/gmd-19-1581-2026
- The Relationship of Aerosol Properties and Ice‐Nucleating Particle Concentrations in Beijing Y. Ren et al. https://doi.org/10.1029/2022JD037383
- Comparison of Lagrangian Superdroplet and Eulerian Double-Moment Spectral Microphysics Schemes in Large-Eddy Simulations of an Isolated Cumulus Congestus Cloud K. Chandrakar et al. https://doi.org/10.1175/JAS-D-21-0138.1
- A Lagrangian particle-based numerical model for surfactant-laden droplets at macroscales M. Denys et al. https://doi.org/10.1063/5.0101930
- Semianalytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models J. Harrington et al. https://doi.org/10.1175/JAS-D-20-0307.1
- Collision Fluctuations of Lucky Droplets with Superdroplets X. Li et al. https://doi.org/10.1175/JAS-D-20-0371.1
- Collisional growth in a particle-based cloud microphysical model: insights from column model simulations using LCM1D (v1.0) S. Unterstrasser et al. https://doi.org/10.5194/gmd-13-5119-2020
- Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method T. Matsushima et al. https://doi.org/10.5194/gmd-16-6211-2023
- Opinion: Tropical cirrus – from micro-scale processes to climate-scale impacts B. Gasparini et al. https://doi.org/10.5194/acp-23-15413-2023
25 citations as recorded by crossref.
- New developments in PySDM and PySDM-examples v2: collisional breakup, immersion freezing, dry aerosol initialization, and adaptive time-stepping E. de Jong et al. https://doi.org/10.21105/joss.04968
- Supersaturation, buoyancy, and deep convection dynamics W. Grabowski & H. Morrison https://doi.org/10.5194/acp-21-13997-2021
- Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1 P. Zmijewski et al. https://doi.org/10.5194/gmd-17-759-2024
- Persistent mixed‐phase states in adiabatic cloud parcels under idealised conditions G. Abade & D. Albuquerque https://doi.org/10.1002/qj.4775
- Between Broadening and Narrowing: How Mixing Affects the Width of the Droplet Size Distribution J. Lim & F. Hoffmann https://doi.org/10.1029/2022JD037900
- Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1 C. Yin et al. https://doi.org/10.5194/gmd-17-5167-2024
- An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n‐Moment Bulk Microphysics Scheme M. Bieli et al. https://doi.org/10.1029/2022MS002994
- Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign S. Park et al. https://doi.org/10.5194/gmd-17-7199-2024
- Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme T. Lüttmer et al. https://doi.org/10.5194/acp-25-4505-2025
- Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions Y. Liu et al. https://doi.org/10.1007/s00376-022-2077-3
- Super‐Droplet Method to Simulate Lagrangian Microphysics of Nuclear Fallout in a Homogeneous Cloud D. McGuffin et al. https://doi.org/10.1029/2022JD036599
- Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0 R. Zhang et al. https://doi.org/10.5194/gmd-17-6761-2024
- snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation D. Ori et al. https://doi.org/10.5194/gmd-14-1511-2021
- Pathways from nucleation to raindrops F. Poydenot & B. Andreotti https://doi.org/10.1103/PhysRevFluids.9.123602
- Breakups are complicated: an efficient representation of collisional breakup in the superdroplet method E. de Jong et al. https://doi.org/10.5194/gmd-16-4193-2023
- Resolving Entrainment–Mixing in Marine Stratocumulus: The Role of LES Grid Resolution and Super-Droplet Number C. Yin et al. https://doi.org/10.1007/s00376-025-5043-z
- Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets Y. Sun et al. https://doi.org/10.5194/gmd-19-1581-2026
- The Relationship of Aerosol Properties and Ice‐Nucleating Particle Concentrations in Beijing Y. Ren et al. https://doi.org/10.1029/2022JD037383
- Comparison of Lagrangian Superdroplet and Eulerian Double-Moment Spectral Microphysics Schemes in Large-Eddy Simulations of an Isolated Cumulus Congestus Cloud K. Chandrakar et al. https://doi.org/10.1175/JAS-D-21-0138.1
- A Lagrangian particle-based numerical model for surfactant-laden droplets at macroscales M. Denys et al. https://doi.org/10.1063/5.0101930
- Semianalytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models J. Harrington et al. https://doi.org/10.1175/JAS-D-20-0307.1
- Collision Fluctuations of Lucky Droplets with Superdroplets X. Li et al. https://doi.org/10.1175/JAS-D-20-0371.1
- Collisional growth in a particle-based cloud microphysical model: insights from column model simulations using LCM1D (v1.0) S. Unterstrasser et al. https://doi.org/10.5194/gmd-13-5119-2020
- Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method T. Matsushima et al. https://doi.org/10.5194/gmd-16-6211-2023
- Opinion: Tropical cirrus – from micro-scale processes to climate-scale impacts B. Gasparini et al. https://doi.org/10.5194/acp-23-15413-2023
Saved (final revised paper)
Latest update: 11 Jun 2026
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.
Using the super-droplet method, we constructed a detailed numerical model of mixed-phase clouds...
