This year's AGU Fall Meeting will have a session focused on science results from Yellowstone and other petascale systems, and we would like to encourage Yellowstone users to submit an abstract about results you may have from your allocations on the system. Session conveners are Jim Hurrell, Director of the National Center for Atmospheric Research (NCAR); Jim Kinter, Director of the Center for Ocean-Land-Atmosphere Studies (COLA); Doug Nychka, Director of the Institute for Mathematics Applied to Geosciences (IMAGe) at NCAR; and Marijke Unger, External Relations Specialist at NCAR.
Early submission deadline for abstracts is July 27 and abstract submissions close on August 3. To submit an abstract, please see http://fallmeeting.agu.org/2016/. The session information is included below.
If you have any questions, please contact Marijke Unger (email@example.com).
Session ID: 13305
Session Title: IN041. Supercomputing for Geoscience: Success Stories from Yellowstone and Other Petascale Systems
Section/Focus Group: Earth and Space Science Informatics
Supercomputing for Geoscience: Success Stories from Yellowstone and Other Petascale Systems
Geoscience has advanced dramatically in the past 50 years by exploiting supercomputers. For example, the Yellowstone supercomputer has been exclusively dedicated to the geosciences, and has contributed two billion core hours to help scientists answer questions about the solar dynamo and photosphere, learn about climate predictability and make predictions of future climate, understand turbulence, and study space and global weather. Yellowstone is operated by the National Center for Atmospheric Research with funding from the National Science Foundation, and has served a global community of 2,500 space physicists, climate dynamics researchers, mesoscale meteorologists, and geologists. This session illustrates the value of high performance computing resources dedicated to geoscience, showcasing computational advances in understanding anthropogenic climate change and associated impacts, in modeling the Sun and predicting coronal mass ejections, in improving severe weather forecasts, and in finding new sources of energy, and looks at how future supercomputers might inform scientific discovery.