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Optimization of DNS code and visualization of entrainment and mixing phenomena at cloud edges

Kumar, B and Rehme, M and Suresh, N and Cherukuru, N and Jaroszynski, S and Li, S and Pearse, S and Scheitlin, T and Rao, SA and Nanjundiah, RS (2021) Optimization of DNS code and visualization of entrainment and mixing phenomena at cloud edges. In: Parallel Computing, 107 .

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Official URL: https://doi.org/10.1016/j.parco.2021.102811


Entrainment and mixing processes occur during the entire life of a cloud. These processes change the droplet size distribution, which determines rain formation and radiative properties. Since it is a microphysical process, it cannot be resolved in large scale weather forecasting models. Small scale simulations such as Direct Numerical Simulations (DNS) are required to resolve the most minute scale of these processes. The DNS of cloud dynamics are performed by integrating two mathematical models, Eulerian and Lagrangian, in a coupled way. Running DNS is a tedious task as it requires a huge amount of computational resources. In this work, we provide a projection of the required resources for running DNS in different size domains. Visualizing these large simulations presents an added challenge, as they generate petabytes of data. Visualization plays a vital role in analyzing and understanding these huge data outputs. Here, we experimented with multiple tools to conduct a visual analysis of this data. Two of these tools are well established and tested technologies: ParaView and VAPOR. The others are emergent technologies in the development phase. This data simulation and visualization, in addition to exploring DNS as mentioned above, provided an opportunity to test and improve development of several tools and methods. © 2021 Elsevier B.V.

Item Type: Journal Article
Publication: Parallel Computing
Publisher: Elsevier B.V.
Additional Information: The copyright for this article belongs to Elsevier B.V.
Keywords: Mixing; Visualization; Weather forecasting, Computational resources; Development phase; Droplet size distributions; Emergent technologies; Microphysical process; Radiative properties; Tools and methods; Weather forecasting model, Data visualization
Department/Centre: Division of Mechanical Sciences > Centre for Atmospheric & Oceanic Sciences
Date Deposited: 21 Sep 2021 09:31
Last Modified: 21 Sep 2021 09:31
URI: http://eprints.iisc.ac.in/id/eprint/69761

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