13 July 2026—Tsunamis in the deep ocean travel as fast as a high-speed train or even an airplane in some cases. “It’s quick, but not so quick,” says Yuchen Wang. “We have enough time between the tsunami generation and the tsunami arrival at the coast, and this time is very precious for us to issue a tsunami warning.”
Wang, a researcher at the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) is focused on that precious time and how to make the most of it. He studies different ways to estimate tsunami hazards and develop early warning systems. He is also interested in solving an understudied problem in the field—how do you know when it’s time to cancel a tsunami warning?
There are generally two types of tsunami warning methods, Wang says. The first method applies seismic data from the triggering earthquake event to a model that simulates the initial sea surface displacement, which in turn informs numerical simulations that combine with hydrological equations to characterize the coastal tsunami.
“The second method, which I’m working on, is called data assimilation,” Wang explains. Tsunami data collected by sea bottom pressure gauges and high-frequency radar are used “directly to reconstruct the tsunami wave field, and then similarly, the numerical model from the tsunami wave field is applied to coastal tsunami, and we can then make the early warning. In this case, we don’t use the initial sea surface displacement.”
There are pros and cons to each approach, he notes. The seismic method can be very quick, relying mostly on speedy source estimates provided by the U.S. Geological Survey, the Japan Meteorological Agency (JMA) and other seismic agencies around the world.
“But for the data assimilation method, it also has its advantages. It’s more accurate in some cases, because it uses offshore tsunami data to predict coastal tsunami, instead of using seismic data to predict tsunami,” Wang says. “And also, it is applicable to all types of tsunamis, like the tsunami generated by a landslide or a volcano. For example, the 2022 Tonga volcanic eruption was generated by atmospheric disturbance, and there was no seismic source for the tsunami.”
Wang and his colleagues recently had a chance to test the method after the Pacific-wide 2025 Kamchatka tsunami, using data collected by the submarine pressure gauges that are part of S-Net, Japan’s 150-station ocean floor observatory system.
In their paper, they show how the method can be used to support a tsunami warning. But Wang and colleagues also added a nonlinear propagation model to help determine when the warning could be lifted safely. Features like bottom friction and advection produce nonlinear effects on tsunamis that impact the formation of following waves and the eventual decay of the waves. (Wang will be speaking about the study at the 2026 Asia Oceania Geosciences Society meeting next month.)
“We want to know when to cancel the warning and let people go back to their homes, and for the warning cancellation, the focus on tsunami following waves is very important,” Wang explains. “That’s why I’m working on nonlinear effects.”
Wang first presented this research at the 2025 SSA Annual Meeting, after receiving an early-career travel grant to attend. Conferences like the SSA meeting help him keep in touch with tsunami researchers around the world, he says.
He also thinks it’s important for tsunami researchers like him to talk more with operational agencies like JMA or NOAA, to share their findings and learn more about what they need for effective tsunami early warning.
Wang had been studying physics as an undergraduate student in Peking University, China before coming across an internship opportunity at the University of Tokyo. “I applied because I like Japan, and I wanted to experience the Japanese culture and get some training.”
The seven-week internship included a visit to Fukushima Prefecture and the site of the 2011 magnitude 9.0 Tohoku earthquake and tsunami. He was tutored by the famous seismologist Kenji Satake. “I found out that seismology is very interesting and meaningful, and especially when we combine field surveys and numerical simulations it can be very important for disaster mitigation,” Wang recalls. “That’s when I decided I would like to go into the Earth science field for graduate study.”
His dream project is to see more instrumentation such as ocean bottom pressure gauges and high-speed radar stations placed around the Pacific. “Here in Japan, we have plenty of stations like S-Net, but in many countries around the Pacific Ocean, they still lack enough observations,” he says. “When we have enough observations, we can make tsunami early warning quicker and more accurate.”
SSA At Work is a monthly column that follows the careers of SSA members. For the full list of issues, head to our At Work page.