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Paper title Met-ocean and oil spill pilots for the ILIAD Digital Twin of the Ocean
Authors
  1. Maria Luisa Quarta MEEO srl
  2. Laura Vettorello Meteorological Environmental Earth Observation - MEEO s.r.l.
  3. Katerina Spanoudaki Foundation for Research and Technology Hellas (FORTH) Speaker
  4. Marco Folegani MEEO srl
  5. Nikolaos Kampanis Foundation for Research and Technology Hellas (FORTH)
Form of presentation Poster
Topics
  • C2. Digital Twins
    • C2.01 Towards a Digital Twin of the Earth - advances and challenges ahead
Abstract text The ocean plays a crucial role in sustaining life on Earth: it regulates our climate and its resources, while the ecosystem services contribute to our economy, health and wellbeing. The role of the ocean in addressing the challenges of future food and energy supply is increasingly recognized as part of the European Green Deal, as is the potential of ocean resources as raw material or inspiration for future innovation. Nowadays the ocean is exposed to pressures at both anthropogenic level (transports, tourism, trades, migration) and environmental level (climate change, ocean warming, salinization, extreme events) that implies a need for innovative and modern monitoring tools to identify threats, to predict risks, to implement early warning systems and to provide advanced decisions support systems based on observations and forecasts. Such tools should integrate available data from in-situ sensors and satellites to enhance the performance of high-resolution state-of-the-art models simulating ocean processes and exploiting data analytics tools to access what-if-scenarios.

The EC recently funded the ILIAD project, through the Horizon 2020 Research and Innovation Programme, which aims at developing, operating and demonstrating the ILIAD Digital Twin of the Ocean (DTO). ILIAD will develop an interoperable, data-intensive and cost-effective DTO, capitalizing on the explosion of new data provided by many different earth sources, modern computing infrastructure including the Internet of Things, social networking, big data, cloud computing and more. It will combine high-resolution modelling with real-time sensing of ocean parameters, advanced AI algorithms for forecasting of spatiotemporal events and pattern recognition. The DTO will consist of several real-time to near-real-time digital replicas of the ocean.

The current work presents ongoing and planned activities for a coastal pilot around Crete, Greece, to be demonstrated in the frame of the ILIAD project. The pilot will combine advanced, high-resolution forecasting services based on numerical hydrodynamic, sea state and particle tracking/oil spill models, enhanced by the integration of Sentinel data and in-situ observations from low-cost wave meters, drifting trackers, drones equipped with met-ocean sensors, as well as citizen/social network sensing. The COASTAL CRETE platform will be integrated into ILIAD for a seamless, robust and reliable access to Earth Observation (EO) data and Copernicus Med MFC products to be integrated into the met-ocean forecasting models and EO data triggering the oil spill model. The COASTAL CRETE pilot will feed results of oil spill fate and transport for the ILIAD DTO. The interaction between the pilot and the ILIAD DTO is essential for oil spill detection. The COASTAL CRETE pilot aims to:
- support and increase the efficiency and the optimization of critical infrastructure operations (e.g., ports) by providing reliable and very high-resolution forecast data, alerts and early warning services for regular day-to-day operational activities;
- support regional authorities in marine spatial planning;
- support regional and local authorities in early detection of and response to oil spill pollution events.

Through the above-mentioned activities, this work aims at contributing to the ILIAD major goal of supporting the implementation of the EU’s Green Deal and Digital Strategy and the seven UN Ocean Decade’s outcomes in close connection with the 17 Sustainable Development Goals (SDG).


Acknowledgement: Part of this research has received funding from the European Union’s Horizon 2020 research and innovation programme under GA No 101037643. The information and views of this research lie entirely with the authors. The European Commission is not responsible for any use that may be made of the information it contains.