AI model could ‘revolutionise’ marine operational decision-making

A new artificial intelligence (AI) model shows potential to forecast ocean currents in the Gulf of Mexico from just a laptop, according to new research.

The AI-based model, developed by researchers at the Met Office and the University of Exeter, is already helping to redefine how new technologies can support marine operational decision-making, with the work recently recognised by the American Society of Civil Engineers (ASCE) Offshore Technology Conference (OTC) Best Paper Award 2025. 

The latest paper extends the previous work of the team to show how their Machine Learning for Low-Cost Offshore Modelling (MaLCOM) framework – originally designed for the regional prediction of ocean waves in UK coastal waters – can be successfully adapted and applied to forecasting the currents in the Gulf of Mexico. 

What makes this framework particularly exciting is its flexibility and efficiency, having been developed to directly leverage hyper-sparse observational measurements for the basis of its predictions, as well as its ability to be trained and run using a laptop or desktop computer. 

In addition, the architecture of the model allows for easy interrogation of its temporal and spatial behaviour, which allows its characteristics to be better unpicked and explained – building trust in its outputs and providing a path to inform future improvements. 

Met Office IT Fellow for Data Science, and the paper’s lead author, Dr Edward Steele, said: “AI-based forecasting could revolutionise ocean prediction in a number of ways. Our research shows the exciting potential of very low-cost, observations-driven, AI-based models in delivering promising results, even when constrained by the scope of the available data.”

“Although still at an early stage of refinement – with further development needed to fully realise the anticipated benefits – we show how AI could quickly and reliably support the forecasting of ocean processes, with the work poised to support a range of possible use cases with key offshore energy, marine search and rescue, and defence applications (among others).” 

University of Exeter Senior Lecturer and Royal Academy of Engineering Research Fellow, Dr Ajit Pillai, said: “This is an exciting application of the MaLCOM framework to new parameters and new geographical regions, demonstrating the versatility of AI-based approaches, and providing new decision-making capability to help offshore safety and workability.”

A pioneering partnership 

This study is a milestone in the team’s continuing work linked with helping ensure safe, efficient and successful operations for those working at sea through more accessible, accurate and faster forecasts. 

Further upgrades of the model are planned to further tailor the MaLCOM framework for ocean current forecasting, complementing the major focus of the team’s research on regional wave prediction. 

This initial concept of what would later evolve into the MaLCOM framework originally began almost 5 years ago as an experimental research project led by the University of Exeter, in which the Met Office were supporting participants.  

Together, the team worked to develop the approach and benchmark the AI-based model results, achieving parity of performance with the operational Met Office physics-based wave model under typical (non-extreme) conditions at short-range forecast horizons out to 12 hours ahead, prior to testing new approaches, use cases, regional domains and ocean variables. Throughout, they have worked directly with industry operators to make sure developments complement their decision-making and workflow. 

Dr Steele continued: “This is an example of the benefits of academic, government and industry organisations working together to develop new approaches and capabilities that are useful, usable and used. As well as the collaboration being scientifically stimulating and enjoyable, in rapidly-evolving fields such as machine learning, partnerships are particularly essential to realising the ambition and vision for the use of AI in weather and climate science and services.” 

Dr Pillai commented: “It is always exciting for research to deliver real impact, and the recognition of the team’s work through the ASCE OTC Best Paper Award 2025 is reflection of some of our progress to date – these are exciting times ahead.”