Physics-Based AI Enables First Global Predictions of Ocean Sediment Carbon Cycling
A team of researchers has developed a new artificial intelligence approach that combines physics-based modeling with machine learning to predict carbon cycling in ocean sediments at a global scale for the first time. Ocean sediments play a crucial role in the global carbon cycle, acting as a long-term sink for organic carbon and influencing atmospheric CO2 levels over geological timescales. Traditional methods for studying these processes have been limited to local measurements and small-scale experiments, making comprehensive global predictions extremely challenging. The new physics-based AI framework is able to process vast amounts of environmental data while respecting the fundamental physical and chemical laws that govern sediment carbon dynamics. This advancement could significantly improve climate models and help scientists better understand how the ocean's sedimentary systems may respond to ongoing environmental changes.