Not long ago, tsunamis triggered by powerful offshore earthquakes could strike with no warning. Walls of water would sweep across the Pacific, devastating coastal communities thousands of miles from the earthquakes’ sources — while residents had no idea what was coming.
That’s no longer the case.
Late Tuesday, a magnitude-8.8 event occurred off the east coast of Russia’s Kamchatka Peninsula — one of the most tsunami-genic regions on Earth. Within minutes, alerts rippled out across the Pacific: Hawaii, Alaska, Japan and the West Coast of the United States were all placed under a variety of warnings, watches or advisories. Fortunately, the tsunami the earthquake produced was relatively modest: The wave heights recorded in the United States topped out at 6 feet in Hawaii and 4 feet along the West Coast.
But the response wasn’t modest at all. It was a big win for modern science and engineering. And amid threats to funding for federal emergency management and response, the response was a crystal-clear illustration of why sustained federal investment in hazard monitoring and response saves lives.
The history of tsunami response in the United States is full of cases in which improvements were triggered by tragedies. On April 1, 1946, a powerful magnitude-8.6 earthquake in Alaska’s Aleutian Islands triggered a tsunami that raced southward and struck Hawaii without warning. It killed 159 people — including schoolchildren in Hilo, swept away by surging waves.
After that disaster, in 1949 the United States established the Pacific Tsunami Warning Center (PTWC), the first of its kind, to provide early warnings to populations around the Pacific. It was a visionary step, recognizing that natural hazards like tsunamis don’t respect borders — and that scientific knowledge could mitigate risk.
But the learning curve was steep. In 1952, another massive earthquake struck Kamchatka, eerily similar in both location and size to Tuesday night’s event. Once again, tsunami waves raced across the Pacific and struck Hawaii. Unlike this week, the wave heights weren’t modest: In some places, they exceeded 12 feet. Even with the PTWC in place, warning systems were rudimentary, and communication channels were slow. The gap between what communities needed to know and what scientists could observe remained dangerously wide.
This week’s success, however, masks a more troubling reality.
Today, though, that gap has narrowed considerably. When Tuesday’s quake hit, the tsunami warning centers in Hawaii and Alaska — operated by the National Oceanic and Atmospheric Administration — immediately sprang into action. The initial alerts, based on the quake’s magnitude and location, are similar to the data scientists could share when the PTWC was created. These early warnings, often issued within 5 to 10 minutes, do trigger public awareness, emergency coordination and follow-up analysis, but they can’t say how high a wave will be or which areas are safest.
What came next on Tuesday, however, was where the scientific transformation is most visible. In the hours following the quake, geophysicists generated a variety of estimates of the details of this earthquake. For example, the U.S. Geological Survey creates rapid “slip models” — estimates of how much the fault moves during the earthquake. These models are crucial, because the shape and magnitude of this motion determine how much water gets displaced. They feed into tsunami propagation models that simulate how waves travel across the ocean and affect distant coastlines.
It used to take days to generate these kinds of simulations. After the magnitude-9.2 Sumatra-Andaman earthquake in 2004, detailed modeling took a week or more. The catastrophic tsunami that followed killed over 230,000 people around the Indian Ocean. Less than a decade later, during the magnitude-9.1 Tōhoku earthquake off Japan in 2011, it took about a day to release reliable models.
Tuesday night? Scientists produced and shared slip models and many other estimates of the earthquake’s behavior within two hours of the event. That level of speed is the result of decades of research, data sharing, software development and international collaboration. And it directly improves the precision of wave forecasts, allowing emergency managers to calibrate their responses appropriately.
This week’s success, however, masks a more troubling reality. Both NOAA and the USGS play critical roles in hazard monitoring and warning, yet their core programs are under increasing strain. The USGS — responsible for seismic monitoring, real-time data delivery and public earthquake alerts — has dealt with flat or declining budgets for years, limiting its ability to modernize infrastructure or expand coverage. The NOAA’s Tsunami Program is in especially urgent trouble. Responsible for both operations and research, it has long been chronically underfunded. Key staff positions remain vacant. Promising research efforts to improve tsunami modeling, coastal inundation forecasts and risk communication have stalled or been abandoned. And just this year, additional budget cuts have been proposed that would jeopardize both the ability to issue timely warnings and the scientific foundation those warnings rely on. When the system works well, like it did Tuesday night, it’s easy to forget how rare that used to be. We’re at the edge of another leap forward in tsunami forecasts. New technologies like machine learning and AI are being tested to produce faster and more accurate slip models, integrate real-time seismic and ocean data and deliver more granular predictions — not just that a wave is coming, but how big, where exactly and when to expect it. These systems can learn from thousands of past events and simulations to improve both speed and accuracy. But this future requires investment in physical infrastructure — especially ocean-bottom networks that can detect seafloor motion and pressure changes directly at the source. Japan, for example, has invested billions in a dense network of cabled seafloor sensors, giving it unparalleled visibility into offshore earthquakes and tsunamis. In contrast, the United States still relies on a much sparser and more fragile network, leaving major offshore subduction zones — like Cascadia — under-monitored. This future will also take resources — not just for technologies, but also for people. Researchers, forecasters, modelers and emergency managers all need training and tools to integrate these new paradigms into real-world operations without compromising safety or transparency. We also need better public-facing communication systems — mobile alerts, smart signage and multilingual messaging — that reflect how people today receive and act on risk information. A tsunami warning system is a public good. It protects everyone — coastal families, fishers, tourists, ports and even those living far inland who rely on coastal infrastructure. It’s not something the private sector can step in to provide at scale. It requires shared investment, public trust and international coordination. And when the system works well, like it did Tuesday night, it’s easy to forget how rare that used to be. Warnings went out quickly. Agencies coordinated. Emergency managers and communities had time to make informed decisions. That’s the best-case scenario. That’s science doing what it’s supposed to do. It’s a dangerous paradox: The better the warning systems perform, the less visible their value becomes — until the systems fail. We can’t control where or when earthquakes strike. But we can choose to be prepared. Tsunami warning centers are one of the clearest examples of how science, when funded and supported, translates into public safety. This time, the Pacific stayed relatively calm. But we were ready. That’s the story. And we shouldn’t wait for a tragedy to realize how vital that readiness really is.
Diego Melgar
Diego Melgar is the director of the Cascadia Region Earthquake Science Center and Ann and Lew Williams Chair of Earth Sciences at the University of Oregon. 
