In September 2023, an unusual seismic signal reverberated around the globe every 90 seconds for nine consecutive days and was then repeated a month later. Scientists were initially unable to identify the source. Almost a year later, two scientific studies proposed that the cause of these seismic anomalies were two mega tsunamis which were triggered in a remote East Greenland fjord by two major landslides which occurred due to warming of an unnamed glacier. These events were believed to have unleashed mega-tsunamis, which then became trapped as seiches—standing waves that sloshed back and forth in the fjord, shaking the planet’s crust. Up to now no observations of these seiches existed to confirm this theory. In a new study, scientists have made the first direct observations by using novel analysis techniques to interpret satellite altimetry data.

Using the SWOT

According to the new research, the breakthrough came from the Surface Water and Ocean Topography (SWOT) satellite. Traditional satellite altimeters failed to detect the waves due to their sparse and linear data coverage. In contrast, SWOT’s Ka-band Radar Interferometer (KaRIn) offers unprecedented spatial resolution and measures surface water heights with 2.5-meter accuracy over 50-kilometer-wide swaths.

Researchers analyzed SWOT data to generate elevation maps of the fjord during and after the events. These maps revealed distinct cross-channel slopes that moved in opposing directions, providing definitive evidence of seiches. Although a Danish military vessel in the fjord during the event observed no disturbances, SWOT’s wide-swath imaging captured what human eyes and older instruments could not.

Climate-Driven Extremes

By linking these observations to seismic signals and ruling out other causes like wind or tides, the researchers confirmed that the seiches caused the nine-day-long seismic event.

“Climate change is giving rise to new, unseen extremes,” said lead author Thomas Monahan. “This study shows how satellite Earth observation can help us study them.” Co-author Professor Thomas Adcock added, “SWOT is a game changer. To fully utilize its data, we must integrate machine learning and ocean physics.”