Applying machine learning methods to ocean patterns and ocean regimes indicators

The global challenges that humankind is called to face highlight the need for establishing innovative algorithms and technologies to enable the transition from data to knowledge, and foster the consolidation of a science-informed decision-making process. 

For a successful implementation of this value chain, the development of science-based algorithms clearly represents a crucial phase. We will analyse the latest updates on the application of machine learning methods to ocean patterns and the ocean regimes indicators in the context of Blue-Cloud.

The Blue-Cloud demonstrator “Marine Environmental Indicators” has a specific focus on data related to the marine environment. Its development is led by the CMCC Foundation, in collaboration with IFREMERMercator Ocean International, the Royal Netherlands Meteorological Institute (KNMI), and the University of Bergen.

Its dedicated Virtual Lab was created in the Blue-Cloud Virtual Research Environment powered by D4Science, and introduced in a public webinar in December 2020 outlining its scope, key features and the potential benefits for the ocean science community.

Test the Virtual Lab

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Bachelot, Loïc; Balem, Kevin; Drago, Federico; Drudi, Massimiliano; Garcia Juan, Andrea
10.5281/zenodo.5896651