Visualization of Clouds and Atmospheric Processes

The output generated by climate simulations is increasing in size, as well as complexity. Both aspects pose equal challenges for the visualization and interactive analysis of the data. The increase in complexity is due to maturing models that are able to better describe the intricacies of the climate system, while the gain in data size is a direct result of an increased spatial and temporal resolution used by modern climate models.The benefit of these high resolution models is not only that they are able to simulate the Earth's past, current and future climate with a higher accuracy, these models also allow us to gain more insight in the complexity of the weather and climate system itself. Until very recently, clouds and precipitation processes were only approximated within climate models and not fully resolved. Now, with maturing models and increasing computational capacities, we are not only able to really simulate clouds and precipitation processes in global models, but also small scale features from the formation of clouds, ice and rain. The data generated, however, is huge and requires special methods for the analysis and visualization of very large data sets.

A first impression of this complexity can be seen from the animation below, which was created using ParaView 4.3 and shows liquid cloud water content as volume rendering, as well as rain content (blue iso-surface) and cloud ice (purple iso-surface).

Visualization of liquid cloud water, cloud ice and rain for the entire day of April 26, 2013. 

The visualization and analysis assignments for the 2017 IEEE SciVis Contest cover a large variety of different tasks with varying level of difficulty. Especially those associated with cloud detection and tracking, or the analysis and comparison of different resolutions, are very important to us, and maybe your solutions and answers will help us to gain more and faster insight into our data, and finally enable us to improve our research through better visualization. 

Dates and Deadlines

• October 26, 2016 - Official announcement of the 2017 IEEE SciVis Contest
• July 31, 2017 - Deadline for Contest entry submissions
• August 31, 2017 - Team notification
October 4, 2017 - Official announcement of the end results at IEEE Vis 2017

Received Submissions

• Winning Entry ETH Zürich (Rimensberger, Gross and Günther "Visualization of Clouds and Atmospheric Air Flows")
• Honourable Mention German Aerospace DLR (Schneegans, Neary, Flatken and Gerndt "STRIELAD - A Scalable Toolkit for Real-time Interactive Exploration of Large Atmospheric Datasets")
• University of Zürich (Amiraghdam, Thöny and Pajarola "SciVis Contest 2017: Visualization of a Large Climate Dataset")
• Tecplot (Simpson, Lee, Mackey and Idso "Visualization of Weather SimulationData Using Tecplot 360")