Digital Twin for Innovation in Oceanic Visualization and Exploration

Proposed solution

Proposed solution consists in the elaboration of a novel paradigm AI4Ocean. We implement 3 complementary functions to the existing DTO systems and beyond the state of the art: the “what-if” and “causal” exploration DT components and the “ocean visualizer”. Our novelty lays in focusing on physics informed models, performing beyond the classification and prediction tasks, elaborating multi-modal generative models for the ocean dynamic states and the on the discovery of causal relations. We generate actionable intelligence to discover new insights in the observations/modelling results. The proposed approach will facilitate the integration, visualization and scenario prediction from data emerging from biophysical ocean observations, simulation models and remote sensing. This promotes effective decision making in the management of sensitive marine communities and ecosystems in the face of climate change. Coupling observations and numerical coupling thanks to advanced AI methods will bring decisive short term weather information in the Atlantic and Mediterranean basins and allow for accurate decision tools for offshore wind farm operations. For the Black Sea, a novel approach based on high-resolution EO data will fuse the mean SAR Doppler velocities and the in-situ measured data in a scenario for environmental impact assessments, and geo-spatial analysis and statistics. For the Norwegian Sea, the DTO is the first all-in-one solution that can: (i) integrate multi-platform ecological data, (ii) visualize, (iii) make scenario predictions while (iv) making these digital products available to the target groups, such as managers, policymakers, and the public.