Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 21
Articles | Volume 16, issue 21
https://doi.org/10.5194/gmd-16-6211-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-16-6211-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 21
Development and technical paper
 | 
02 Nov 2023
Development and technical paper |  | 02 Nov 2023

Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method

Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima

Supplement

https://doi.org/10.5194/gmd-16-6211-2023-supplement

Data sets

Supplement to the manuscript "Overcoming computational challenges to realize meter-to-submeter-scale resolution in cloud simulations using super-droplet method" (Matsushima et al., 2023) Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima https://doi.org/10.5281/zenodo.8103378

Model code and software

SCALE-SDM source code and configuration files for meter-to-submeter-scale resolution in cloud simulations Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima https://doi.org/10.5281/zenodo.8103369

Download
Short summary
A particle-based cloud model was developed for meter- to submeter-scale resolution in cloud simulations. Our new cloud model's computational performance is superior to a bin method and comparable to a two-moment bulk method. A highlight of this study is the 2 m resolution shallow cloud simulations over an area covering ∼10 km2. This model allows for studying turbulence and cloud physics at spatial scales that overlap with those covered by direct numerical simulations and field studies.
Read more
Special issue
Particle-based methods for simulating atmospheric aerosol...