NOAA ditches weather-predicting supercomputers for Google Cloud

Uncle Sam will no longer be hosting his own supercomputers to predict the weather. The U.S. National Oceanic and Atmospheric Administration has picked Google Cloud to provide the infrastructure for its weather forecasting operations. In an announcement, NOAA boasted that it will be the first national weather prediction center to run on the commercial cloud, though the UK's Met Office is also in the process of moving its own weather prediction system to Microsoft Azure in a hybrid setup. Weather operations are typically run on in-house or government-funded supercomputer systems, which helps drive the HPC (high performance computing) market. General Dynamics held the previous contract for managing NOAA’s weather predicting machines, which most recently were HPE Cray supercomputers running in data centers in Virginia and Arizona. Those machines – Dogwood and Cactus – could crank almost 14 PFlops of weather-predicting prognosis. The plan is to move NOAA’s Weather and Climate Operational Supercomputing System, run by the National Weather Service (NWS) division, over to the cloud by December 2027, along with the software that generates NWS weather data for analysis. Don’t say global warming The agency is hoping that the cloud will make model forecasting more nimble, resulting in earlier predictions and better warnings for all the extreme weather events that seem to keep occurring these days. It was the in-house systems that were holding things back, evidently. “Cloud-based high-performance computing will accelerate the transition of research into operations by eliminating traditional bottlenecks of on-premise systems,” said NOAA Administrator Neil Jacobs in a statement. Jacobs noted that the cloud’s flexibility for providing large amounts of compute is advantageous: the agency can ramp up cycles during tropical storm season, then wind them down during calmer periods. Under the contract, NOAA can also avail itself of Google’s DeepMind set of AI tools to help build out its first AI-driven weather forecasting system, the AI Global Forecast System, which promises to offer accurate weather forecasts using 99.7% fewer computer cycles and take minutes, rather than hours, to produce a forecast. NWS has already been upgrading the software downstream from GFS and GEFS to also work in the cloud. In March, it awarded contracts to Accenture and Booz Allen Hamilton to oversee the development of cloud-based software (HIVE and CIRRUS) for the field offices to analyze data and push out alerts, replacing the in-house software doing these tasks currently. For the job, Google plans to use Google Cloud H4D VMs, built on AMD Epyc processors. Google labels these instances as “virtual machines” because they run under a hypervisor that integrates Google’s networking and orchestration tools. As a result, they can be synchronized to run large jobs the same way supercomputers do. According to Google, customers can access H4Ds for as low as 3 cents per core-hour without long-term commitments. For supercomputing jobs, they can also use Cluster Toolkit to deploy clusters and Cluster Director to maintain them. Google Cloud’s Batch can handle the queuing, scheduling, and resource provisioning. ®