Out at sea, sailors are faced with harsh conditions that are often unpredictable. Ship-engulfing rogue waves can suddenly tower from nothing, measuring eight times higher than surrounding seas. 

These conditions pose a real danger for sailors, as these incoming rogue waves appear without warning.

MIT engineers may have found a way to provide a much-needed warning to sailors. They developed an algorithm capable of measuring data from surrounding waves in order to predict which clusters of waves may grow into rogue waves.

The prediction tool can offer sailors a two-to-three minute warning, giving them the opportunity to shut down ship operations or offshore platforms. Based on probability principles, the algorithm records the length and height or wave groups to predict which group is most likely to turn into a rogue wave.

This video shows how MIT engineers developed their rogue wave prediction:

“It’s precise in the sense that it’s telling us very accurately the location and the time that this rare event will happen,” said Themis Sapsis, the American Bureau of Shipping career development assistant professor of mechanical engineering at MIT. “We have a range of possibilities, and we can say that this will be a dangerous wave, and you’d better do something. That’s really all you need.”

Ocean Complexities Challenge Algorithm

The ocean is a complex system, and predicting rogue waves requires an approach that records as much information as possible. Researchers have tried simulating each individual wave in a given body of water to create high-resolution pictures of the sea state, including rogue-like activity. 

Unfortunately, the detailed data is computationally costly, since several computers are needed to solve equations not only for each wave, but also for all their interactions with other waves.

“It’s accurate, but it’s extremely slow — you cannot run these computations on your laptop,” Sapsis said. “There’s no way to predict rogue waves practically. That’s the gap we’re trying to address.”

Determined to simplify and speed up the computational process, Sapsis and former post-doc Will Cousins, along with their team, observed that some waves cluster together in a single wave group and roll through the ocean together. These waves seem to exchange energy which builds up into the rogue wave.

“These waves really talk to each other,” Sapsis said. “They interact and exchange energy. It’s not just bad luck. It’s the dynamics that create this phenomenon.”

The Practical Approach

The key to creating the simplified and faster algorithm was based on finding patterns in wave groups that transformed into rogue waves. From ocean buoy measurements, the researchers used nonlinear analysis of the water wave equations.

Statistical data quantified wave possibilities, and then the nonlinear dynamics of the system were analyzed to predict the groups which would turn into rogue waves. Two parameters essential for these predictions were a wave group’s length and height. 

Deriving a simple algorithm from a combination of statistics and dynamics, the researchers tracked the energy of the surrounding wave field over this length-scale and could immediately predict the probability of rogue wave formation a few minutes in advance.

The algorithm speed and independence of computations increases the odds for practical applications. However, reliability has yet to be tested. Ships and offshore platforms will require high-resolution scanning technologies such as radar and LIDAR, a surveying technology which uses laser light, to take the necessary wave measurements.

“If we know the wave field, we can identify immediately what would be the critical length scale that one has to observe, and then identify spatial regions with high probability for a rare event,” Sapsis said. “If you are performing operations on an aircraft carrier or offshore platform, this is extremely important.”