The federal government’s core weather forecast supercomputing operation is moving to the commercial cloud.
The National Oceanic and Atmospheric Administration selected Google Cloud on Monday as the primary provider for NOAA’s Weather and Climate Operational Supercomputing System, becoming one of the first forecasting infrastructures to drift to the public cloud.
Google Cloud offers a complete suite of artificial intelligence services and infrastructure with tools for building, deploying and scaling machine learning models and generative AI apps.
This transition will reshape how the U.S. forecasts hurricanes, tornadoes and other severe weather, resulting in a more flexible modeling system, according to the agency.
“Cloud-based high-performance computing will accelerate the transition of research into operations by eliminating traditional bottlenecks of on-premise systems,” NOAA Administrator Neil Jacobs said in a statement. “Not only will this new approach provide access to the latest chips, it will advance weather forecasting by aligning operational and research compute and provide capabilities for elastic on-demand model development.”
Transferring NOAA supercomputers to cloud infrastructure will enable rapid updates and adaptations, make the system more resilient and prone to fewer and shorter periods of downtime, and increase computing power, the agency said.
Ken Graham, the director of NOAA’s National Weather Service, said the agency is now “charting a course to global leadership in cloud-based numerical weather prediction.
“This is a significant achievement for NOAA, one that will ensure our critical modeling operations can seamlessly adapt to emerging science and strengthen our mission to protect life and property.”
The transition to the cloud is scheduled to be completed by December 2027.
NOAA and Google’s partnership goes back over a decade, involving other AI applications.
Most recently, NOAA began using Google DeepMind as the framework for its AI-driven global weather prediction models, the agency’s first set of weather forecast models powered by machine learning.
