Abstract
In the future, climate change will strongly influence our environment and living conditions. Weather and Climate simulations that predict possible changes produce big data sets. The combination of various variables of climate models with spatial data from different sources helps to identify correlations and to study key processes. In this paper, the results of the Weather Research and Forecasting model are visualized for two regions. For this purpose, a continuous workflow that leads from the integration of heterogeneous raw data to 3D visualizations that can be displayed on a desktop computer or in an interactive virtual reality environment is developed. These easy-to-understand visualizations of complex data are the basis for scientific communication and for the evaluation and verification of models as well as for interdisciplinary discussions of the research results.
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Acknowledgments
The first author would like to express her gratitude to the European Social Fund (ESF) as part of the program ”Europa fördert Sachsen” for the funding of the scholarship. We thank HIGRADE, the graduate school of UFZ (Bissinger and Kolditz 2008), and CompeTE+ the school for doctoral students at the HTWK. The authors gratefully acknowledge the data support of the Spatial Information and Planning System (RIPS) of the Regional Office for Environment, Measurement and Nature Protection of Baden-Württemberg. Thanks to Dr. Andreas Marx and the climate data support of CERA (Climate and Environmental Retrieving and Archiving) for providing the observation data. The presented work is part of the WESS project, WESS is supported by a grant from the Ministry of Science, Research and Arts of Baden-Württemberg (AZ Zu 33-721.3-2) and the Helmholtz Center for Environmental Research, Leipzig (UFZ). The satellite images were provided by the NERC Satellite Receiving Station, Dundee University, Scotland from http://www.sat.dundee.ac.uk.
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Helbig, C., Bauer, HS., Rink, K. et al. Concept and workflow for 3D visualization of atmospheric data in a virtual reality environment for analytical approaches. Environ Earth Sci 72, 3767–3780 (2014). https://doi.org/10.1007/s12665-014-3136-6
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DOI: https://doi.org/10.1007/s12665-014-3136-6