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Green Image
Issue No. 06 - November/December (2008 vol. 14)
ISSN: 1077-2626
pp: 1579-1586
Johannes Kehrer , Department of Informatics, University of Bergen, Norway
Florian Ladstädter , Wegener Center for Climate and Global Change (WegCenter) and Institute for Geophysics, Astrophysics, and Meteorology (IGAM), University of Graz, Austria
Philipp Muigg , VRVis Research Center and SimVis GmbH, Vienna, Austria
Helmut Doleisch , VRVis Research Center and SimVis GmbH, Vienna, Austria
Andrea Steiner , Wegener Center for Climate and Global Change (WegCenter) and Institute for Geophysics, Astrophysics, and Meteorology (IGAM), University of Graz, Austria
Helwig Hauser , Department of Informatics, University of Bergen, Norway
ABSTRACT
One of the most prominent topics in climate research is the investigation, detection, and allocation of climate change. In this paper, we aim at identifying regions in the atmosphere (e.g., certain height layers) which can act as sensitive and robust indicators for climate change. We demonstrate how interactive visual data exploration of large amounts of multi-variate and time-dependent climate data enables the steered generation of promising hypotheses for subsequent statistical evaluation. The use of new visualization and interaction technology—in the context of a coordinated multiple views framework—allows not only to identify these promising hypotheses, but also to efficiently narrow down parameters that are required in the process of computational data analysis. Two datasets, namely an ECHAM5 climate model run and the ERA-40 reanalysis incorporating observational data, are investigated. Higher-order information such as linear trends or signal-to-noise ratio is derived and interactively explored in order to detect and explore those regions which react most sensitively to climate change. As one conclusion from this study, we identify an excellent potential for usefully generalizing our approach to other, similar application cases, as well.
INDEX TERMS
Index Terms—interactive visual hypothesis generation, interactive visual exploration and analysis, visualization for climate research.
CITATION

A. Steiner, H. Hauser, J. Kehrer, H. Doleisch, F. Ladstädter and P. Muigg, "Hypothesis Generation in Climate Research with Interactive Visual Data Exploration," in IEEE Transactions on Visualization & Computer Graphics, vol. 14, no. , pp. 1579-1586, 2008.
doi:10.1109/TVCG.2008.139
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