A newly developed artificial intelligence system, trained on centuries of data, can predict the occurrence of dangerous 'rogue' waves in the ocean. This breakthrough insight could save many lives and protect valuable infrastructure like ships and oil rigs.
AI system predicting rogue wave formation
Rogue waves are notorious for their sudden appearance and potential to cause harm to ships and oil rigs. They're defined not necessarily by their size, but by standing at least twice as high as surrounding waves, forming due to unique interactions between currents and winds. Now, an artificial intelligence system trained on centuries of wave data can predict when these rogue waves will happen, offering valuable insights into how they form and potentially saving lives and valuable infrastructure.
The University of Copenhagen researchers fed a gigantic amount of wave data into the AI system to train it. This data was collected by buoys in 158 locations worldwide and covered over 700 years' worth of data and more than a billion waves. The extensive dataset allowed for a comprehensive understanding of wave patterns and behaviors, and subsequently, the ability to predict rogue waves.
Discovering rogue waves' true cause
The research team's analysis revealed a surprising fact: the most common cause of rogue waves isn't what scientists originally thought. Instead of being caused by seismic activity like tsunamis, rogue waves result from a phenomenon known as linear superposition. This happens when two separate wave systems intersect and briefly reinforce each other, leading to the formation of these potentially dangerous waves.
Applications of rogue wave prediction algorithm
The new algorithm developed by the research team provides a practical application for rogue wave prediction. It can analyze incoming data from ocean buoys and signal an alarm when the exact combination of risk factors for rogue waves presents itself in a specific ocean region. Shipping companies could use this information to plan alternate routes and avoid these potential hazards, increasing safety and efficiency.