Satellite view of Kamchatka tsunami challenges wave models
SWOT observations of a Pacific tsunami suggest standard models missed wave complexity and point to a longer earthquake rupture.
By Tom Brennan · Health & Medicine Correspondent
3 min read
A NASA-led satellite mission recorded a major Pacific tsunami in unusual detail after a magnitude 8.8 earthquake struck off Russia’s Kamchatka Peninsula, giving scientists a new look at how the wave moved across the ocean. Researchers say the data could change parts of tsunami modeling and improve estimates of risk for coastal communities.
The findings, reported by the Seismological Society of America and published in The Seismic Record, center on the July 29 earthquake in the Kuril-Kamchatka subduction zone. The quake ranks as the sixth-largest recorded globally since 1900, according to the society.
The Surface Water Ocean Topography satellite, known as SWOT, passed over the tsunami as it spread through the Pacific. The study’s authors said the mission produced the first broad, high-resolution satellite view of a major tsunami caused by a subduction-zone earthquake.
SWOT saw more than a single wave
Researchers combined SWOT measurements with readings from DART, the Deep-ocean Assessment and Reporting of Tsunamis buoy network. DART stations measure small changes in sea level at fixed points and are used in tsunami warning systems.
Angel Ruiz-Angulo of the University of Iceland, the study’s lead author, said SWOT gave scientists a wider view than earlier tools. He described the satellite data as “a new pair of glasses,” because DART buoys show conditions at specific locations while SWOT can scan a swath of ocean about 120 kilometers wide.
That wider view showed a more complex tsunami than standard assumptions would suggest, according to the study. Instead of a wave maintaining a relatively simple form as it crossed deep water, the observations showed waves spreading, scattering and interacting over long distances.
The study focused on dispersion, a process in which parts of a wave travel at slightly different speeds. Large tsunamis are often treated as largely non-dispersive because their wavelengths greatly exceed ocean depth, but Ruiz-Angulo said the SWOT data challenged that view for this event.
Computer models that included dispersion fit the satellite observations better than more traditional tsunami models, according to the researchers. Ruiz-Angulo said modelers may be leaving out variability that could affect how a main wave is shaped by trailing waves as it nears some coasts.
Wave data pointed back to the quake
The tsunami measurements also helped the team reassess the earthquake rupture. Earlier models based on seismic records and land deformation did not match all buoy readings, with one DART station detecting the tsunami earlier than expected and another later than predicted.
Using an inversion method, the researchers worked backward from the tsunami observations to estimate the earthquake source. Their model indicated the rupture extended about 400 kilometers, farther south than previous studies had found and longer than the roughly 300 kilometers estimated in earlier models.
Co-author Diego Melgar said tsunami data have become more important for studying shallow slip near the seafloor since Japan’s magnitude 9.0 Tohoku-oki earthquake in 2011. He said combining DART data with seismic and geodetic observations remains difficult because ocean-wave models differ from models of seismic waves inside Earth, but the Kamchatka analysis shows the value of using multiple data types.
SWOT launched in December 2022 as a joint mission of NASA and France’s Centre National d’Etudes Spatiales. Its main job is to map Earth’s surface water, including rivers, lakes and ocean features.
The Seismological Society of America said the Kuril-Kamchatka zone has generated some of the Pacific’s largest tsunamis, including a 1952 event after a magnitude 9.0 earthquake that helped spur creation of the international tsunami warning system. Researchers hope future satellite observations like SWOT’s can support faster and more accurate tsunami forecasts.
This story draws on original reporting from ScienceDaily.