Abstract
Recent advances in high-performance computing technologies, applied in climate science, are allowing increases in model complexity, model resolution, and the number of simulations run. The interactive exploration and analysis of these complex, multi-field climate data sets have been identified as one of the major current challenges in scientific visualization. For example, without direct 3D multi-field visualization, it is difficult to recognize the important correlative effects between vertical wind velocities and transport of the volumetric atmosphere. As such data have complicated 3D structures and are highly time-dependent, a visualization approach must handle these dynamic data in a highly interactive way. In this paper, an efficient multi-field visualization framework is proposed for Earth climate simulation data. A novel visualization pipeline is presented for on-demand data processing, enabling scalable handling of large-scale climate data sets. The hardware-accelerated multi-field visualization method used in the framework allows interactive and accurate visualization of multiple intersecting climate phenomena. An information-theoretic-based wind-field analysis method is also implemented within the visualization framework to help scientists gain a deeper understanding of the underlying multi-field climate data.
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Acknowledgments
This work was supported by the Key Program of Science and Technology Funds of China Academy of Engineering Physics (CAEP) under Grant No. 2014A0403019, Science and Technology Founds of CAEP under Grant No. 2015B0403093, and the National Natural Science Foundation of China (No. 61232012).
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Cao, Y., Mo, Z., Ai, Z. et al. An efficient and visually accurate multi-field visualization framework for high-resolution climate data. J Vis 19, 447–460 (2016). https://doi.org/10.1007/s12650-015-0335-5
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DOI: https://doi.org/10.1007/s12650-015-0335-5