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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.”

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SpaceX to Fly Italian Science Experiments to Mars on Starship in 2026

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August 11, 2025

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SpaceX to Fly Italian Science Experiments to Mars on Starship in 2026

SpaceX has signed a first-of-its-kind deal with the Italian Space Agency (ASI) to fly Italian science experiments to Mars aboard its Starship rocket. ASI President Teodoro Valente announced that ASI will send its experiments on SpaceX’s first commercial Mars flights. The payloads will include a plant-growth module, a meteorology station and a radiation detector, which will collect data during the roughly six-month journey and on the Martian surface. This landmark agreement represents a new milestone in Mars exploration.

Italian Scientific Experiments on Starship

According to the ASI officials, the payloads include “a plant growth experiment, a meteorological monitoring station and a radiation sensor”. The plant experiment is designed to test how plants grow during the months-long trip and under Mars-like conditions, which will inform future life-support systems. The meteorological module will record Martian weather (temperature, pressure, etc.) to improve understanding of Mars’s climate. The radiation sensor will measure cosmic rays and solar particles during the flight and on Mars’ surface, providing data essential for assessing astronaut safety.

Mission Timeline and Commercial Partnership Implications

Starship has completed only suborbital test flights (nine as of mid-2025) and has not yet reached orbit. SpaceX is targeting the Nov–Dec 2026 Mars launch window, but CEO Elon Musk cautions that “a lot needs to go right” and success is far from guaranteed. Starship itself is a massive two-stage fully reusable rocket built specifically for Mars missions. Meeting these targets depends on completing Starship’s development and test flights.

For SpaceX, the contract turns Starship into a Mars transportation service. The deal lets Italy send experiments to Mars without developing its own rocket. More broadly, it exemplifies a new era in which countries and organizations can purchase payload flights on commercial rockets, benefiting future Mars research.

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SWOT Satellite Captures Tsunami Wave After Kamchatka Quake

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August 11, 2025

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SWOT Satellite Captures Tsunami Wave After Kamchatka Quake

The U.S.-French SWOT (Surface Water and Ocean Topography) satellite captured the leading edge of a tsunami wave that rolled through the Pacific Ocean on July 30, 2025 (11:25 a.m. local time), in the wake of a magnitude 8.8 earthquake that struck Russia’s Kamchatka Peninsula. The satellite captured the data about 70 minutes after the earthquake struck. SWOT is a designed to map oceans and freshwater on Earth. The satellite recorded data from the tsunami as it passed through the deep ocean.

About SWOT

According to NASA, The SWOT satellite was jointly developed by NASA and the French space agency CNES (Centre National d’Études Spatiales). NASA provided the Ka-band radar interferometer (KaRIn) instrument, a GPS science receiver, a laser retroreflector, a two-beam microwave radiometer, and NASA instrument operations. The Doppler Orbitography and Radioposition Integrated by Satellite system, the dual frequency Poseidon altimeter, the KaRIn radio-frequency subsystem, the satellite platform, and ground operations were provided by CNES.

These advanced technology and specialized radar helps SWOT to map the height of the ocean surface. In this case, SWOT’s measurement of the tsunami wave’s height and shape in open water showed that the leading edge of the wave was about 1.5 feet (45 centimeters) high. It also captured the wave’s profile and direction as it traveled toward coastal areas. Such detailed measurements of a tsunami at sea are unprecedented.

Better disaster forecast

The NOAA Center for Tsunami Research tested its forecast models using the new satellite data and found that including SWOT’s measurements could significantly improve forecast accuracy. NASA oceanographer Ben Hamlington noted that even a 1.5-foot tsunami in the deep ocean can amplify into a 30-foot wave at the shore and it is important to detect it early. Vasily Titov, chief scientist at NOAA’s Center for Tsunami Research, added that these observations suggest SWOT could significantly enhance operational tsunami forecasting – a capability long sought since the 2004 Sumatra disaster.

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SpaceX to Fly Italian Science Experiments to Mars on Starship in 2026



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Aeneas AI Model Helps Decode and Restore Ancient Roman Inscriptions

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August 10, 2025

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Aeneas AI Model Helps Decode and Restore Ancient Roman Inscriptions

Ancient Roman Inscriptions help us understand laws, traditions, economy, and even the emotional perspective of ancient people. Their lives and histories, however, have been rendered difficult to understand because, over time, the inscriptions have been damaged. Every year, there are 1500 Roman inscriptions discovered, albeit many of them are incomplete. Fortunately, advancements in technology like the new Aeneas tool, is helping in the future understanding of the Roman inscriptions. It serves as a large language model specializing in reading, interpreting, and giving context to Roman inscriptions.

Decode Ancient Roman Inscriptions

As Per Report,Drawing its name from a hero in Roman history, Aeneas, the model has been trained on nearly 200,000 latian inscriptions, which span from the 7th century to the 8th century covering regions from Portugal to Iraq.Aneas has the capability to analyze images of damaged inscriptions and predict or even fill in missing letters or words. In addition to that, it is able to determine a time frame and location for the inscription, as well as cross-reference it with other inscriptions containing similar phrases or purposes.

Making History Clearer Through Technology

Since Aeneas is trained exclusively on Latin inscriptions, specialists believe that he is less prone to random or false errors when compared to general AI approaches. University of Sydney historian Anne Rogerson remarked that Aeneas’s proposals, as informed guesses, still involve real historical data as opposed to baseless conjectures.

Despite the model’s open availability,Made public alongside the model’s code and data, Aeneas’s creator, Google DeepMind, offered the model without restrictions.

Most impressively, Aeneas can be accessed for free, enabling students and researchers to shift through and reinterpret previously concealed fragments of Roman history to understand them on a deeper level.

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