This week marks a major milestone in oceanic studies and maritime safety after a team of engineers published a study demonstrating how AI neural networks could help to forecast and warn about rogue waves. Notably, these massive events were once seen as unpredictable and have led to major losses for centuries. Here’s what you need to know.
Rogue Waves
Rogue waves go by many names including killer, monster, and extreme waves. These waves possess a height that is double the normal oceanic conditions and may appear out of nowhere, placing those in its way in great danger. Throughout history, rogue waves have been the folklore of sea travelers, who undoubtedly heard legends of these massive waves carrying their fellow seaman to the depths. Today, these waves still pose a major threat.
Notably, these rare oceanic events are similar to tsunamis in their size and destructive power. However, unlike their well-understood counterparts, Rogue waves can appear without any major noticeable event, such as an earthquake. As such, these large and unpredictable waves pose great danger to offshore infrastructure, travelers, and other equipment.
How Rogue Waves Form
Until recently, there wasn’t enough data and computational power to create reliable rogue wave formation mechanisms. As such, the majority of science regarding the formation of these elusive events was based on observational data collection following events. This info has led researchers to determine the three most prominent ways that rogue waves form.
Slowly Build-up
Interestingly, a rogue wave can begin to form and build up without the need to combine with other waves. Strong currents like the Gulf Stream can resonate and expand to create a massive sea anomaly. Scientists studying this phenomenon often employ a method called Benjamin-Feir instability to explain the single-wave train’s expansion. This is one of the rarest forms of rogue waves captured by researchers.
Multiple Waves
The most widely understood formation of rogue waves occurs due to multiple wave interference meeting at the perfect time to amplify the magnitude. When waves build up and resonate, they can magnify and intensify the current and ferocity of the wave. You can think of this like a snowball effect in that each wave becomes absorbed into the greater momentum creating a massive wall ready to destroy anything in its path.
Current Methods of Determining Rogue Waves
There are no reliable rogue wave forecast systems in place globally, even though these events have the potential to wreak billions in damage yearly. The most common methods used to determine these events rely on real-time ocean data that can only be predicted as the event occurs, notifying scientists of the increase in sea level. This strategy leaves much to be desired in terms of early warning and safety precautions.
Rogue Waves Study
The “Prediction of freak waves from buoy measurements” study seeks to shed light on these unique ocean events. The researchers set out to create an AI neural network capable of predicting the chances of a rogue wave occurring based on the current ocean state. As part of this approach, researchers sought to determine what pre-factors occurred before the formation of rogue waves.
This approach was meant to demonstrate the functional relationship between the previous waves and the final rogue event using field measurement devices and advanced neural networks. More importantly, the team wanted to capture and document the phases of synchronization between the individual waves needed to create rogue waves.
Testing Phase
The testing began with the creation of a neural network. The team decided to use a long short-term memory network (LSTM) AI algorithm. These AI systems were created to streamline the functional relationship between input data and output data. As such, they are ideal for creating data-driven forecasts of complex systems.
Ocean Buoys
The researchers gathered data from 172 buoys located off the east coast of the US and Pacific islands with depths ranging from 20 meters to +4000m. Two types of buoys were used in the test. The Datawell directional wave rider MkIII with a 1.28 Hz sampling rate and Datawell directional wave rider MkIII with a 2.56 Hz rate. These units are well-tested and offer reliable data, including accelerators that monitor vertical displacement.
Source – MATLAB
Dataset
The neural network was programmed using a sample size equivalent to 880 years of consecutive data regarding pre-rogue wave conditions. In particular, 14 million 30-minute sea surface elevation measurements were combined with 40,000 sea surface elevation measurements from the same buoys. This data was then scanned to check for abnormalities. The data was then fed back into the algorithm to better train it how to spot these factors.
Relevant to Ocean Conditions
The researchers were keen to try to make the rogue wave samples few and far between in the testing phase to ensure that data was closer to real-world scenarios. The samples were then broken into the non-rogue wave and rogue wave categories that were reinforced. Notably, the initial data was obtained via the Coastal Data Information Program (CDIP) in conjunction with Scripps Institution of Oceanography.
Scanned for Rogue Waves
The researchers scanned the wave sample data using the University of Maryland supercomputing resources. This access enabled them to leverage an NVIDIA A100 GPU in conjunction with a local NVIDIA Quadro P1000 GPU to enhance their AI performance, training times, and accuracy.
Results
The results of this study could have a resounding effect on the way engineers and researchers view rogue waves moving forward. These once nearly impossible-to-determine events were able to be singled out with 75% accuracy using the AI systems. Specifically, 75% of rogue waves were predicted within 1 minute of their appearance. The rate only dropped to 73% when the time was expanded to 5 minutes of warning.
In total, the AI successfully predicted close to 3k rogue waves accurately. Only 855 events managed to slip past the AI detection, leaving the system with a 23% accuracy rating. Considering many researchers believed it was impossible to determine these events, these results opened the door for new and more effective prediction systems to be introduced.
Benefits
This study could bring many benefits to the market. For one, it’s the first reliable rogue wave forecast system concept. It takes the idea of these events being too complex to predict and instead, introduces a very reliable and cost-effective solution that could provide valuable advanced warning to ships and offshore platforms when needed.
Uses Current Buoy Data
Another major benefit of this approach to determining the probability of rogue waves is that there is no need to install new sensors or systems. Buoys have already been deployed and tested for decades. As such, they provide a reliable and proven data source that has a trackable history. This AI prediction upgrade is software. As such, it can leverage the millions of hours of data provided by these devices to improve and enhance future performance.
Universal Application
One of the most interesting aspects of their AI training is that the model was able to be applied to locations outside the original buoy data set with success. The team was able to predict with high probability the rogue wave risk for two off-site buoys. They tested their theory on Buoy 132, located near Jacksonville, Florida, and Buoy 067 near San Nicolas Island off the coast of Los Angeles. The results showed that the algorithm could be applied to other locations with success.
Self Improving
One of the biggest benefits of this style of AI algorithm is that it can continually improve its data set, reinforcing its understanding and improving performance. These systems will improve as the data gets refined. As such, this method provides a low-cost and efficient way to enhance operations.
Researchers
Thomas Breunung and Balakumar Balachandran were the lead researchers in the study. They achieved their goal of demonstrating a way to determine rogue waves with high accuracy globally. Notably, The University of Maryland provided supercomputing resources and support for the team, which now seeks to improve its results by introducing more data to its model including wind speed, location, and depth. All of these factors could help to improve detection times and even provide a way to determine the height of the event.
Companies that Can Integrate This Tech Today
Many firms could gain immediate benefits from this study. There are currently billions in offshore infrastructure and shipping vessels traversing the ocean. These firms are sure to invest in any technology that can help prevent catastrophic losses and death.
1. Diamond Offshore Drilling Inc. 
Diamond Offshore Drilling Inc. is a major oil and gas drilling firm located in Katy, Texas. The company entered the market in 1987 as a Diamond M Drilling company before undergoing multiple rebrandings. Currently, they have 44 offshore drilling rigs including 32 semi-submersible platforms and 5 drillships.
Diamond Offshore Drilling Inc. has contracts with many of the largest oil and gas companies in the world, including Hess Corporation, Petrobras, BP, and Occidental Petroleum. Its positioning and the demand for fossil fuels make this stock a strong “hold.” Notably, it has experienced some downsides due to an influx of green energies into the market, but analysts predict future gains as conflict and other factors drive gas prices higher.
2. Sable Offshore Corp 
Sable Offshore Corp is another drilling firm that could leverage a rogue wave prediction system to protect its fleet of offshore rigs and drilling stations. The company was founded in 2020 as Flame Acquisition Corp before changing its name to Sable. Sable has offshore operations located off the coast of California in federal waters. It also holds 76K acres of subsea leases that enable it to pipe crude oil and natural gas.
The firm has many strategic partnerships with industry leaders including ExxonMobil, Canada Ltd, Imperial Oil Resources Limited, and Pengrowth Energy Corporation, to name a few. The company’s stock has suffered recently due to fluctuations in the market. However, California has a growing demand for these services, positioning Sable Offshore Corp as a premier local energy provider.
Future of Rogue Wave Prediction
This study sheds light on the elusive world of rogue waves. These events are no longer sailor tales but are now predictable events. In the future, these systems will be integrated across the maritime economy to mitigate risk and improve efficiency. Notably, these systems will get much better and more accurate as they obtain additional reinforced data.
You can expect to see this style of prediction coupled with systems such as blockchain networks that provide real-time monitoring of massive data across the globe soon. This improvement would enable these systems to record and track real-time occurrences across the ocean in an immutable manner. This data could then be used to improve scientists understanding of these elusive occurrences.
Rogue Waves are a Problem that Detection Can Solve
There’s no way to stop rogue waves from forming as of yet. However, the first step to preventing major losses is determining when and what makes these events occur. These engineers have taken the first steps and laid the groundwork for future research that could save lives. For now, their efforts are making “waves” across multiple industries.
Learn about other cool AI projects now.