Articles | Volume 12, issue 1
https://doi.org/10.5194/gmd-12-233-2019
https://doi.org/10.5194/gmd-12-233-2019
Model description paper
 | 
16 Jan 2019
Model description paper |  | 16 Jan 2019

Toward modular in situ visualization in Earth system models: the regional modeling system RegESM 1.1

Ufuk Utku Turuncoglu

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Cited articles

Ahern, S.: High Performance Visualization: Enabling Extreme – Scale Scientific Insight, The Path to Exascale, CRC Press/Francis–Taylor Group, 331–353, 2012. a
Ahrens, J.: Increasing scientific data insights about exascale class simulations under power and storage constraints, IEEE Comput. Graph., 35, 8–11, 2015. a
Ahrens, J., Geveci, B., and Law, C.: ParaView: An End-User Tool for Large Data Visualization, Visualization Handbook, Elsevier, 2005. a
Ahrens, J., Jourdain, S., O'Leary, P., Patchett, J., Rogers, D. H., Fasel, P., Bauer, A., Petersen, M., and Samsel, F.: In Situ MPAS-Ocean Image-Based Visualization. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis SC14, 16–21 November 2014, New Orleans, LA, USA, 2014. a, b, c
Alexander, K. and Easterbrook, S. M.: The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations, Geosci. Model Dev., 8, 1221–1232, https://doi.org/10.5194/gmd-8-1221-2015, 2015. a
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Short summary
This study aims to present a novel application of the recently developed state-of-the-art modeling framework to integrate in situ visualization and a data analysis approach with a model coupling framework. The modeling framework utilizes ParaView/Catalyst to gain more insight about the vast amount of data through in situ visualizations, enabling analysis of fast-moving processes and their evolution in both time and space to support better understanding of underplaying physical mechanisms.