The Future of Ocean Observation: Leveraging Real-Time Data to Enable Responsive Action

Accurate ocean observation, simulation, and prediction has long presented a major challenge to scientists, vessel operators, and environmentalists seeking to accurately report on the physical, chemical, and biological components of our oceans. Recent advancements in computing technology and machine learning have significantly enhanced our capabilities of processing large quantities of raw ocean data and enhanced our ability to predict future ocean states. An area that could significantly benefit from these enhancements is the model-based prediction of downstream effects of accidental events, such as oil spills resulting from vessel collisions. This paper outlines the necessity for real-time data in building adaptive models capable of responding to unforeseen circumstances, the need for real-time sensors to support them, the requirement for community feedback in determining optimal sensor station placement to maximally enable research and innovation, and how COVE's Digital Harbour Initiative is approaching this problem.