DTO-BioFlow DUC 8 - Applying Machine Learning to Forecast Ocean Productivity

This factsheet presents DUC8: Machine Learning for ocean colour seasonal forecasting (chlorophyll-a and primary production), one of the Demonstrator Use Cases (DUCs) developed within the DTO-BioFlow project. It is intended for members of the scientific community in need of long-term biogeochemical forecasts (such as ecosystem modellers, carbon-cycle researchers) and local/regional decision-makers who manage marine resources (e.g., fisheries, aquaculture, ecosystem surveillance).

DUC8 applies machine-learning algorithms to ocean-colour data to improve seasonal forecasts of chlorophyll-a and primary production, enhancing the predictive capacity of the DTO.)

The Demonstrator Use Cases (DUCs) are at the core of DTO-BioFlow, showcasing how biodiversity observations, AI models, and the Digital Twin of the Ocean (DTO) can deliver digital solutions for marine sustainability.