Phytoplankton carbon assimilation in a global ensemble marine ecosystem data assimilation system

Marine ecosystems are a vital component of the global carbon cycle. Our understanding of the cycle within the ocean relies on a combination of numerical models and satellite observations, which are combined through data assimilation (DA) methods. Here we developed a global ensemble DA system for marine ecosystem prediction using the NEMO-MEDUSA coupled ocean-biogeochemistry model and the Parallel Data Assimilation Framework. Unlike deterministic DA systems, the ensemble approach provides flow-dependent uncertainty estimates, improving the reliability of global marine ecosystem forecasts.

We applied this ensemble system to investigate the assimilation of a novel phytoplankton carbon product derived from satellite ocean colour observations. Compared to the widely used phytoplankton chlorophyll product, the phytoplankton carbon product demonstrated improved global error statistics and facilitated significant adjustments in unobserved components of the marine ecosystems, including ocean carbon fluxes. Our findings also reveal a discrepancy in the ratio of phytoplankton constituents between observations and model forecasts, highlighting the potential benefits of assimilating different ocean color products to enhance marine ecosystem prediction beyond typical error metrics. These results show the advantage of novel ocean colour products for marine ecosystem modeling and understanding.