To extend its weather modeling capabilities, the U.S. Air Force has joined the computing experts at the U.S. Department of Energy’s Oak Ridge National Laboratory in a strategic collaboration that includes procurement and operation of a new high-performance weather modeling computer system. Key members of the Air Force and ORNL teams gathered on July 10, 2018, to kick off the project and tour the facilities supporting the new system. (Photo courtesy ORNL)
For the U.S. military, accurate weather prediction is vital to both the planning and execution of worldwide missions. To extend its weather modeling capabilities, the U.S. Air Force has joined the computing experts at the U.S. Department of Energy’s Oak Ridge National Laboratory in a strategic collaboration that includes procurement and operation of a new high-performance weather modeling computer system. Key members of the Air Force and ORNL teams, including computing and global security team members, gathered on July 10 to kick off this project and tour the facilities supporting the new system, according to a story posted by ORNL.
The Air Force 557th Weather Wing provides the Air Force and Army with global- and regional-level numerical weather model forecasts. With the increasing scale of the requirements for the new system, the Air Force and ORNL identified an opportunity to take advantage of the capabilities of ORNL’s National Center for Computational Sciences—including expertise in high-performance computing facilities and infrastructure, systems administration, computing procurement and acquisition, and system operations, the story said.
“We learned about the Air Force’s needs, and it was immediately clear that ORNL could help them solve their problems,†said Jim Rogers, NCCS director of computing and facilities. “We can integrate the Air Force weather team’s needs into our facilities in a cost-effective way, leveraging our capabilities to deliver exceedingly high availability to support their mission.â€
As part of the collaboration, ORNL and Air Force Weather are exploring improvements to the numerical weather model, including the potential use of hardware accelerators, improved physical processes within the model, and existing capability gaps, including hydrological impacts. The partitioned system will run the forecast models as well as research and development codes that can dramatically advance the Air Force’s scientific capabilities for weather prediction.
“ORNL’s high-performance computing facilities and expertise across the computing spectrum will be a valuable partner as the Air Force looks to advance its weather modeling capabilities,†said ORNL’s Jeff Nichols, associate laboratory director of computing and computational sciences. “Conversely, this new system will enable ORNL researchers to push the state of the art in next-generation computing technologies and evolve and refine the state of the art in weather research and prediction.â€
The Air Force strives to maintain the most modern approach toward weather and Earth system modeling, a goal that requires harnessing the power of next-generation computing platforms such as those operated by the NCCS, ORNL said.
“The strategic partnership between the Air Force and ORNL provides the opportunity to leverage Oak Ridge’s world-class expertise to support our numerical weather forecast capabilities,†said U.S. Air Force Director of Weather Ralph Stoffler.
In addition to the hardware deployment, ORNL researchers will apply their expertise in computational science and Earth system modeling to improve performance of the target Air Force model on the new computing resources and demonstrate novel science capabilities, the story said.
“Our group lives at the nexus of computing, climate, earth science, and weather,†said Kate Evans, group leader for the Computational Earth Sciences Group in the Computing and Computational Sciences Directorate. Through the research and development portion of the collaboration, Evans and her colleagues will use their expertise in computational performance research across multiple Earth system models to accelerate the GALWEM (Global Air-Land Weather Exploitation Model).
“We will use a combination of approaches to improve the model, some of which overlap with DOE strategies, creating a symbiotic collaboration with the Air Force and DOE,†Evans said.
To extend its weather modeling capabilities, the U.S. Air Force has joined the computing experts at the U.S. Department of Energy’s Oak Ridge National Laboratory in a strategic collaboration that includes procurement and operation of a new high-performance weather modeling computer system. Key members of the Air Force and ORNL teams gathered on July 10, 2018, to kick off the project and tour the facilities supporting the new system. (Photo courtesy ORNL)
The collaboration also allows the ORNL team to perform research to enable a predictive hydrology capability with a robust multimodel workflow, the lab said. This workflow couples multiscale and multiphysics models for precipitation, runoff, streamflow, flooding, and impacts of flooding events. Along with weather forecasts, flood and drought prediction is of interest to a number of modeling and prediction centers, including the Air Force. Beyond model development, the multimodel workflow will utilize the evaluation, data processing, and model coupling expertise at ORNL.
The Air Force wants to later explore how advances in machine learning, combined with more traditional physics-based models, can advance its weather prediction capabilities.
More information will be added as it becomes available.
See the original ORNL story here.
Most news stories on Oak Ridge Today are free, brought to you by Oak Ridge Today with help from our advertisers, contributors, and subscribers. This is a free story. Thank you to our advertisers, contributors, and subscribers. You can see what we cover here.
Do you appreciate this story or our work in general? If so, please consider a monthly subscription to Oak Ridge Today. See our Subscribe page here. Thank you for reading Oak Ridge Today.
Copyright 2018 Oak Ridge Today. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
Leave a Reply