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2016 IEEE Pacific Visualization Symposium (PacificVis) (2016)
Taipei, Taiwan
April 19, 2016 to April 22, 2016
ISSN: 2165-8773
ISBN: 978-1-5090-1451-4
pp: 56-63
Qingya Shu , Key Laboratory of Machine Perception (Ministry of Education), and School of EECS, Peking University, Beijing, P.R. China
Hanqi Guo , Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA
Jie Liang , Key Laboratory of Machine Perception (Ministry of Education), and School of EECS, Peking University, Beijing, P.R. China
Limei Che , Key Laboratory of Machine Perception (Ministry of Education), and School of EECS, Peking University, Beijing, P.R. China
Junfeng Liu , College of Urban and Environmental Sciences, Peking University, Beijing, P.R. China
Xiaoru Yuan , Key Laboratory of Machine Perception (Ministry of Education), and School of EECS, Peking University, Beijing, P.R. China
ABSTRACT
This paper presents a novel visual analysis tool, EnsembleGraph, which aims at helping scientists understand spatiotemporal similarities across runs in time-varying ensemble simulation data. We abstract the input data into a graph, where each node represents a region with similar behaviors across runs and nodes in adjacent time frames are linked if their regions overlap spatially. The visualization of this graph, combined with multiple-linked views showing details, enables users to explore, select, and compare the extracted regions that have similar behaviors. The driving application of this paper is the study of regional emission influences over tropospheric ozone, based on the ensemble simulations conducted with different anthropogenic emission absences using MOZART-4. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations.
INDEX TERMS
graph visualization, ensemble simulation
CITATION
Qingya Shu, Hanqi Guo, Jie Liang, Limei Che, Junfeng Liu, Xiaoru Yuan, "EnsembleGraph: Interactive visual analysis of spatiotemporal behaviors in ensemble simulation data", 2016 IEEE Pacific Visualization Symposium (PacificVis), vol. 00, no. , pp. 56-63, 2016, doi:10.1109/PACIFICVIS.2016.7465251
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