The Digital Twin of the Ocean concept is to make a step further by integrating all European assets related to seas and oceans (data, models, physical ocean observatories at sea) with digital technologies (cloud, super HPC capacities, AI and data analytics) into a digital component that represents a consistent high-resolution, multi-dimensional and (nearly) real-time description of the ocean.
It will contribute to the Commission’s Green Deal and Digital Package commitments to develop a very high precision digital model of the Earth (Destination Earth initiative). AI and analytics, thematic or sectorial models and computing power will transform data into knowledge. They will facilitate co-creation and inter-disciplinary approaches between natural sciences, humanities and social sciences for the co-construction of methods, expertise and applications to support decision making. This digital view of the ocean will enable a multi-angle perception of the ocean: its physics, chemistry, geology, biology as well as the environmental and socio-economic impact of human activity. It will be a simulator to test scenarios that deal with different evolutions of the ocean environment. It will empower citizens, governments and industries to collectively share the responsibility to monitor, preserve and enhance marine and coastal habitats, while supporting also a sustainable blue economy (fishing, aquaculture, transport, renewable energy, etc.). It will enable measures to increase resilience to climate change, improve disaster risk management, develop spatial plans, report on the state of the environment, coastal or offshore activity and measure its impact. Proposals for such a development should demonstrate their usefulness with regard to Green Deal priorities (e.g. impact of ocean climate scenarios on aquaculture and fisheries, impact of sea-level rise and extreme waves on coastal risks, pollution monitoring and scenarios for mitigation and remediation strategies, and maritime spatial planning).
It needs to fulfil all of the following criteria: deliver break-through in accuracy and realism, represent optimal synergy between observations and models; fully integrate downstream impact sectors of the socio-economic areas addressed in their test case; include a rigorous handling of quality and confidence information.
Proposals should address:
• The development of an ocean digital twin at high resolution including the ocean model representation and the integration of all available datasets into a single digital framework compatible of Destination Earth infrastructure and technologies (cloud, euroHPC, AI-ready standards, datacubes, …). It should build on existing infrastructures and relevant Horizon 2020 and R&D projects to achieve this integration at short-term (e.g. CMEMS, BlueCloud, EMODNet, portals from ERICs, IMMERSE, ESA Ocean Science Cluster);
• The configuration of it as a simulation environment built on a consistent multi-variable multi-dimensional description of the ocean consistent from estuaries to the coast and to open ocean, from the surface to the seabed and allowing a digital exploration in time and space of the ocean physics and biodiversity according to different scenarios. It should provide an integrated, timely and persistent description of the ocean including at least physics, biogeochemistry, geology and human activities;
• The integration of data from existing or new automated sensors and autonomous mobile and fixed platforms, additional structured and unstructured data, alternative sources such as private companies data, citizen science or historic data collected before the digital age (chemical, physical, biological and ecological) and delivered through EMODnet and Copernicus;
• The implementation of data and model outputs in state-of-art standards and formats (INSPIRE, FAIR, ontologies, …) compliant with their exploitation by applications and appropriate user interfaces based on big data and artificial intelligence technologies; • The development of what-if scenarios to validate the representativeness of the digital ocean simulator in “real conditions of use” by configuring different ocean conditions and exploiting AI/data analytics tools, on concrete cases in local or regional sea basins.