Recent advancements in machine learning are being applied to enhance climate and ocean models, particularly in the area of ocean biogeochemistry.
Traditionally, the equations that underpin these models have been based on limited observations and various assumptions, which may not capture the full complexity of oceanic processes.
This new research has the potential to lead to more accurate predictions regarding ocean behavior and its impact on climate, reflecting a significant step forward in environmental science.