Real-Time Tsunami Forecasting Wins Top Supercomputing Prize

A team of researchers from The University of Texas at Austin (UT), Lawrence Livermore National Laboratory (LLNL), adn Scripps Institution of Oceanography at UC San Diego has won the 2025 Association for Computing Machinery (ACM) Gordon Bell Prize for its work on real-time tsunami forecasting.

The team created a real-time tsunami forecasting system using an advanced “digital twin” framework. This dramatically reduces supercomputing time – what normally takes 50 years now happens in under a second. This breakthrough could substantially improve early warning systems for coastal communities in earthquake and tsunami-prone areas.

Researchers applied the forecast to the Cascadia subduction zone, a seismically hazardous area spanning 700 miles from Northern California to British Columbia, Canada. The last major Cascadia earthquake occurred in 1700. Seismologists estimate a 37% probability of an earthquake with a magnitude of 8.0 or higher within the next 50 years.

“We developed new algorithms using seafloor sensors to forecast tsunami wave heights and their uncertainties in fractions of a second – 10 billion times faster than conventional algorithms,” said Scripps Oceanography seismologist and team member Alice Gabriel. “Our work demonstrates that physics-based models of earthquakes and tsunami generation are now fast enough to guide real-time response. This improves early warning for the Pacific Northwest and paves the way for global, physics-based earthquake and tsunami early-warning systems.”

The gordon Bell Prize, often called the Nobel Prize of supercomputing, recognizes innovation in high performance computing (HPC) applications in science, engineering, and large-scale data analytics. The award was presented at the annual Supercomputing Conference (SC25) on Nov. 20.

“It’s a tremendous honor for our team to receive this highest recognition in the