High Performance Visualization using the NOAA Earth Information System (NEIS)

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Thursday, 8 January 2015: 3:45 PM
130 (Phoenix Convention Center - West and North Buildings)
Jebb Q. Stewart, NOAA, Boulder, CO; and E. Hackathorn, J. S. Smith, and J. Joyce

Within our community data volume is rapidly expanding for both observations as well as weather prediction models. These data have limited value if you cannot interact or visualize the data in a timely manner. The scientific community needs the ability to dynamically visualize, analyze, and interact with these data along with other environmental data in real-time regardless of the physical location or data format.

Within the National Oceanic Atmospheric Administration's (NOAA's), the Earth System Research Laboratory (ESRL) is actively developing the NOAA Earth Information System (NEIS). Previously, the NEIS team investigated methods of data discovery and interoperability. The recent focus has shifted to high performance real-time visualization allowing NEIS to bring massive amounts of 4-D data, including output from multiple weather forecast models as well as different data from different observations (surface obs, upper air, maritime obs) in one place.

Our server side architecture provides a real-time stream processing system which utilizes server based NVIDIA Graphical Processing Units (GPU's) for data processing, wavelet based compression, and other preparation techniques for visualization, allows NEIS to minimize the bandwidth and latency for data delivery to end-users.

Client side, users interact with NEIS services through the visualization application developed at ESRL called TerraViz. Terraviz is developed using the Unity game engine and takes advantage of the GPU's allowing a user to interact with large data sets in real time that might not have been possible before.

Through these technologies, the NEIS team has improved accessibility to ‘Big Data' along with providing tools allowing novel visualization and seamless integration of data across time and space regardless of data size, physical location, or data format. These capabilities provide the ability to see the global interactions and their importance for weather prediction. Additionally, they allow greater access than currently exists helping to foster scientific collaboration and new ideas.

This presentation will provide an update of the recent enhancements of the NEIS architecture and visualization capabilities, challenges faced, as well as ongoing research activities related to this project.