New AI-Powered Tsunami Warning System Developed by UCLA and Cardiff University

Tsunamis are powerful waves that can cause significant damage to coastal areas. Predicting them is challenging because they depend on the type of underwater earthquake that occurs. Researchers from the University of California, Los Angeles, and Cardiff University have created an early warning system using advanced acoustic technology and artificial intelligence to quickly assess earthquake types and potential tsunami risks.

Understanding Earthquake Types

Underwater earthquakes can lead to tsunamis if they displace a large amount of water. Bernabe Gomez, a co-author of the study, explains that earthquakes with a strong vertical slip are more likely to cause tsunamis than those with horizontal slips. Identifying the slip type early can reduce false alarms and improve warning system reliability.

Using Acoustic Technology

Traditional methods using ocean wave buoys often don't provide enough time for evacuation. Instead, the researchers suggest using acoustic radiation, or sound, produced by earthquakes. This sound travels faster than tsunami waves and can be recorded by underwater microphones called hydrophones. Usama Kadri, another co-author, notes that these sounds can be detected thousands of kilometers away, providing crucial information about the earthquake.

AI and Real-Time Analysis

The system uses AI to analyze data from hydrophones, determining the earthquake's slip type and magnitude. It calculates key properties like length, width, uplift speed, and duration, which help predict the tsunami's size. Tests with hydrophone data showed the model could quickly and accurately describe earthquake parameters with minimal computational effort.

Future Improvements

The researchers are working to enhance the model's accuracy by incorporating more data. Their efforts are part of a larger project to improve hazard warning systems, which could increase the safety of offshore platforms and ships.