Instead of a clean, cohesive wavefront, the satellite detected a braided, fragmented energy pattern that extended across hundreds of miles. This level of detail\u2014impossible to capture with traditional sensors\u2014revealed how large tsunamis may behave in complex and previously misunderstood ways.<\/p>\n
The findings, published in The Seismic Record<\/a>, could fundamentally alter how scientists model tsunamis, issue early warnings, and prepare coastal communities for impact.<\/p>\n Satellite Imaging Challenges Old Tsunami Models<\/p>\n Launched in December 2022<\/a>, SWOT was never built for disaster response. It was created to map global rivers, lakes, and ocean topography using Ka-band radar interferometry\u2014scanning 120-kilometer-wide swaths of sea surface with sub-centimeter precision. But this mission accidentally became the first to capture a full satellite view of a tsunami in open ocean.<\/p>\n Until now, the NOAA-operated DART system<\/a> has been the gold standard for tsunami detection. These buoys provide highly sensitive sea-level data, but only at specific points across the ocean. SWOT, by contrast, delivered a continuous two-dimensional view, capturing how the tsunami evolved spatially and temporally.<\/p>\n \u201cWe could only see the tsunami at specific points in the vastness of the ocean,\u201d said Angel Ruiz-Angulo, lead author of the study and a researcher at the University of Iceland. \u201cNow, with SWOT, we can capture a swath up to about 120 kilometers wide, with unprecedented high-resolution data of the sea surface.\u201d<\/p>\n The satellite imagery showed the tsunami wave field breaking apart and recombining mid-ocean\u2014clear signs of wave dispersion. When the research team ran numerical simulations including dispersion physics, the results closely mirrored the satellite\u2019s observation<\/a>. Models that ignored dispersion failed to match what actually happened.<\/p>\n Understanding Tsunami Dispersion and Wave Behavior<\/p>\n For years, most tsunami models have treated large waves as non-dispersive shallow-water waves, where the wave energy travels uniformly. This simplification allowed for faster predictions and easier risk calculations\u2014but SWOT has exposed its limitations.<\/p>\n In this event, dispersion mattered. The wave energy didn\u2019t stay in a tight packet\u2014it split, scattered, and re-formed over time and space. That matters for coastlines, where delayed or trailing waves can influence run-up height, arrival time, and force of impact.<\/p>\n \u201cThis extra variability could represent that the main wave could be modulated by the trailing waves as it approaches some coast,\u201d Ruiz-Angulo explained. \u201cWe would need to quantify this excess of dispersive energy and evaluate if it has an impact that was not considered before.\u201d<\/p>\n This isn\u2019t just a matter of refining models. It\u2019s about improving real-world tsunami risk assessments. If coastal warnings are based on oversimplified assumptions, they may underestimate danger in critical areas, especially near harbors or complex shorelines where timing and wave interference matter most.<\/p>\n Combining Satellites, Buoys, and Seismic Data<\/p>\n![\"Propagation](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2025\/12\/propagation-of-the-2025-tsunami-across-the-pacific-basin-with-arrival-times-in-minutes-at-dart-buoys.jpeg\"\/)
Propagation of the 2025 tsunami across the Pacific Basin with arrival times (in minutes) at DART buoys and the SWOT satellite\u2019s overpass path. Credit: The Seismic Record<\/p>\n![\"Synthetic](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2025\/12\/synthetic-tide-gauge-data-simulated-along-the-swot-nadir-track-953x800.png\"\/)
Synthetic tide gauge data simulated along the SWOT nadir track, showing the complexity and modulation of wave heights over time and space. Credit: The Seismic Record<\/p>\n
![\"Comparison](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2025\/12\/comparison-of-vertical-deformation-and-slip-models-derived-from-usgs-dart-inversion-and-blended-data.png\"\/)
Comparison of vertical deformation and slip models derived from USGS, DART inversion, and blended datasets. The final blended model extends farther south than initial estimates. Credit: The Seismic Record<\/p>\n![\"Comparative](\"https:\/\/www.newsbeep.com\/il\/wp-content\/uploads\/2025\/12\/comparative-tsunami-energy-release-from-the-2025-m88-and-1952-m90-kamchatka-earthquakes.png\"\/)
Comparative Tsunami Energy Release From The 2025 M8.8 And 1952 M9.0 Kamchatka Earthquakes. Credit: The Seismic Record<\/p>\n