PML awarded funding to develop state-of-the-art digital twin for harmful algal bloom monitoring

18 January 2024

The project, named Synchronising Earth Observation and Modelling Frameworks Towards a Digital Twin Ocean (SyncED-Ocean), will deliver a digital twin demonstrator, combining data from satellite Earth Observation and marine autonomous robots with marine system models to create an optimised virtual coastal ocean ecosystem.

What is a digital twin?

 A digital twin is a dynamic virtual copy of a physical asset, process, system or environment that looks like and behaves in real time identically to its real-world partner. Actions and events can be modelled with unprecedented accuracy, offering the ability to experiment in a non-live environment of the real world. 

The TWINE digital twin pilot projects will demonstrate how research using Earth Observation data and emerging digital twinning technologies can transform environmental science across priority areas including climate change, biodiversity and ecosystems, and natural hazards.

The first SyncED-Ocean digital twin will focus on HABs and their subsequent impacts on ocean oxygen concentration in UK coastal areas, both of which present serious risk to ocean health, biodiversity and productivity.
 
The demonstrator utilises AI techniques to couple real and virtual systems, creating an agile, adaptive digital twin framework that can be used to support future research, policy and commercial applications that seek to improve understanding and management of our natural environment.
 
Professor Matthew Palmer, Head of Science for PML's Digital Innovation & Marine Autonomy group, said: 

"We are really excited that this project was successfully funded under the TWINE programme. SyncED-Ocean brings together a number of PML's scientific and digital technology areas of expertise to develop a ‘Digital Twin Ocean’ aimed at improving our ability to predict how coastal marine ecosystems function. The framework that SyncED-Ocean delivers is urgently required to underpin decision support tools for marine researchers, policymakers, managers and industry."
 
“For this demonstrator, we will target two key indicators of ocean health: harmful algal blooms (HABs) and coastal deoxygenation. Both present significant risk to marine systems and have potential to cause public health risks and economic loss in commercial fisheries and aquaculture. This 'Digital Twin' approach aims to produce a virtual replica of a marine ecosystem in the Western English Channel that is directly linked to its real-world equivalent via satellite Earth observations and autonomous marine robots that are controlled by satellites. Those robots will adapt continuously to the changing requirements of the virtual ecosystem (represented by a marine system model) to help optimise the virtual representation of the real-world ecosystem and present the best possible predictions of HABs and reducing oxygen levels." 
 
"The complex processing of the massive amounts of data used in this study will be assisted by a series of AI decision-making tools, developed in partnership with Exeter University co-investigators, that will condense observations and model outputs to optimise the near future requirements of the marine robotic missions, which will then be communicated back to the fleet of robots at regular intervals. The SyncED-Ocean framework will be designed around Digital Twin community best practices to ensure it can be further developed to address a range of marine and other environmental challenges". 


The SyncED-Ocean project is one of five projects that received part of the TWINE programme's £2.8m fund, being delivered by the Natural Environment Research Council in partnership with the Uk Met Office.

The TWINE programme is part of a £200 million portfolio of 17 Earth Observation Investment Package (EOIP) projects, which were announced in November 2022. The aims of the TWINE programme and the successful projects collectively are to:

• harness the UK’s leading position at the nexus of environmental, observational and computational sciences, and bring together multidisciplinary teams to realise the value of digital twinning technology to address environmental challenges
• improve the understanding, modelling and prediction of events, inform future decision-making, and test the impacts of different scenarios and interventions to help make better decisions on improving our environment
• build the foundations of a coherent and lasting landscape of digital twins for environmental science, with a high level of cross-fertilisation of learning and a focus on design for interoperability with current and future activities

Professor Peter Liss, Interim Executive Chair of NERC said:

“Developing digital twins for environmental science is important to improve our ability to anticipate and respond to crises including in climate change, biodiversity and future weather events."

“These five projects will bring together multidisciplinary teams to realise the value of digital twinning technology. It is excellent to form a partnership with the Met Office to address this research challenge and ensure that the UK reaches it’s potential in this area”.

The five funded TWINE project are:

Synchronising Earth Observation and Modelling Frameworks Towards a Digital Twin Ocean (SyncED-Ocean)
Plymouth Marine Laboratory

This project will deliver a digital twin pilot demonstrator that combines harmful algal bloom data from satellite Earth Observations and marine autonomous robots for assimilation to marine system models to provide an optimised virtual coastal ocean ecosystem.

MAS-DT
National Oceanography Centre

This project will develop a digital twin to optimise ocean glider observations to maximise their impact on ocean models.
 
Virtual Integration of Satellite and In-Situ Observation Networks (VISION)
National Centre for Atmospheric Science and University of Cambridge

This project will deliver a toolkit and novel visualisations that will allow for better integration of models and observations to enhance our confidence in future climate projections and will develop a digital twin to improve the operational flights of the FAAM Airborne Laboratory atmospheric research aircraft.

 FLOODTWIN
University of Hull

This project will build a digital twin for water-related hazard forecasting and decision-making for Hull and the East Riding of Yorkshire, a region heavily impacted by hydrometeorological hazards such as flooding.

 SPLASH: digital approaches to predict wave hazards
University of Plymouth

This project will create a digital twin of a wave overtopping in order to build a deployable coastal warning tool that predicts wave hazards.


 

Related information

UK Research & Innovation news about the TWINE funding

Earth Observation Investment Package (EOIP)