Immersive Analytics for Climate Change

Visualizing complex climate models is difficult and the results are often challenging to interpret. We created a immersive analytics tool for exploring the output of a Dynamic Integrated Climate-Economy (DICE) model to demonstrate the potential of immersive virtual reality (iVR) for exploring climate models in a more intuitive way. Immersive abstract 3D visualizations and realistic environmental models are integrated into the same experience. DICE models and other Integrated Assessment Models (IAMs) are critical for informing environmental decision making and policy analysis. They often produce complex and multi-layered output, but need to be understood by decision makers who are not experts. iVR on the other hand enables representations that are both compelling and intuitive.


Mark Simpson
Jan Oliver Wallgrün
Alexander Klippel
Liping Yang
Department of Geography

Gregory Garner
Klaus Keller
Earth and Environmental Systems Institute

Danielle Oprean
Stuckeman Center for Design Computing

Saurabh Bansal
Smeal College of Business


Simpson, M., Wallgrün, J.O., Klippel, A., Yang, L., Garner, G., Keller, K., Oprean, D., and Bansal, S. Immersive Analytics for Multi-objective Dynamic Integrated Climate-Economy (DICE) Models. In Proceedings of the 2016 ACM Companion on Interactive Surfaces and Spaces (ACM-ISS 2016). DOI: 10.1145/3009939.3009955 
Simpson, M., Garner, G., Wallgrün, J.O., Keller, K., Oprean, D., Bansal, S., and Klippel, A. Immersive Analytics for Integrated Assessment Models of Climate Change.  In Proceedings of the SpatialVA 2016 Workshop at GIScience 2016.


This work was partially supported by the National Science Foundation (NSF) cooperative agreement GEO-1240507 and the Penn State Center for Climate Risk Management and this work was supported by the NSF under IGERT Award #DGE-1144860, Big Data Social Science, and Pennsylvania State University. Funding has also been received through Pennsylvania State University’s Institute for Cyber Science. Any conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies.