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Preprints
https://doi.org/10.5194/egusphere-2023-2700
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2023-2700
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Preprints
17 Nov 2023
 | 17 Nov 2023
Status: this preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).

Meeting Summary: Exploring Cloud Dynamics with Cloud Model 1 and 3D Visualization – insights from a University Modeling Workshop

Lisa Schielicke, Yidan Li, Jerome Schyns, Aaron Sperschneider, Jose Pablo Solano Marchini, and Christoph Peter Gatzen

Abstract. We introduce an innovative two-week educational block course held at the University of Bonn during the 2023 winter semester, focusing on Cloud Model 1 (CM1) and its convection-permitting capabilities. During the course, students gained essential skills in setting up and customizing CM1 simulations on high-performance computing clusters, while delving into deep moist convection dynamics. An additional introduction to three-dimensional visualization software allowed the participants to transform numerical data into compelling visualizations, deepening their insights into cloud dynamics. Students applied their gained knowledge in research projects of their own choice that will be presented here and in the supplementary material.

How to cite. Schielicke, L., Li, Y., Schyns, J., Sperschneider, A., Solano Marchini, J. P., and Gatzen, C. P.: Meeting Summary: Exploring Cloud Dynamics with Cloud Model 1 and 3D Visualization – insights from a University Modeling Workshop, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2700, 2023.
Received: 15 Nov 2023 – Discussion started: 17 Nov 2023

Lisa Schielicke et al.

Status: open (until 29 Dec 2023)

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Lisa Schielicke et al.

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Short summary
We present course contents and results of a two-week educational block course with focus on Cloud Model 1 (CM1) and 3D visualization. Through hands-on experience, students gained skills in setting up and customizing the model and visualizing its output in 3D. The research aimed to bridge the gap between classroom learning and practical applications, fostering a deeper understanding of convective processes and preparing students for future careers in the field.
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