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Ocean biogeochemistry and ecosystems are an essential Earth system component, both because of their uptake of antrophogenic carbon emissions (through biological carbon pump, i.e. air-sea fluxes, photosynthesis in the ocean and transport of carbon to the ocean bottom) and for providing living resources for billions of people around the world.

However, ocean biogeochemistry is both exceptionally complex and significantly undersampled in terms of available observations. Data assimilation is then essential to both monitor and forecast the health of our oceans. This includes changes in biological productivity and carbon uptake, plankton communities underpinning the marine ecosystem structure, oxygen content in the oceans and ocean acidity.

NCEO scientists, in collaboration with other UK (e.g. Met Office) and international partners, are playing essential role in a number of developments expanding the marine biogeochemistry assimilation capacity to include (i) new observation types, e.g. phytoplankton size-classes (Ciavatta et al, 2018, Skakala et al, 2018), optical data (Ciavatta et al, 2014, Skakala et al, 2020), or carbon from space,  (ii) observations from multiple platforms, including autonomous gliders (Skakala et al, 2021), (iii) better estimates of forecast uncertainty through diagnostic methods (Fowler et al, 2022), or ensemble techniques (Skakala et al, 2024), (iv) adaptation of the assimilative system to a very-high (1.5km) model resolution, (v) capacity to implement data assimilation in digital twin applications, including navigating “smart’’ fully autonomous observing platforms to areas of observational interest (e.g. Ford et al, 2022). Beyond improving reanalyses and forecasts, many of these developments also provide essential recommendations for the observational community (e.g. on observing network design), or to the modelling community (e.g. on model parametrization).

Examples of past and present projects:

• Developing pre-operational capacity to assimilate phytoplankton size-class chlorophyll on the North-West European Shelf
• Developing bio-optical model to improve relationships between simulated biogeochemistry and optics, leading to new capacity to directly assimilate optical variables
• Assimilation of data from multiple platforms, including demonstration of the new capability in a fully autonomous observing system tracking the onset of phytoplankton bloom. This is now being expanded to a system with a very-high (1.5km) resolution model and multiple gliders, simultaneously tracking harmful algae blooms (HABs) and oxygen minima. 
• Development of ensemble capacity to globally assimilate carbon from space.
• Development of ensemble (hybrid) data assimilation capacity for the North-West European Shelf, including better model parameter estimates.
• Development of capacity to estimate water-surface reflectance (hyperspectral) through better resolution of ocean optics and assimilation of hyperspectral satellite reflectance data
• Development of machine learning techniques to aid multi-variate data assimilation in marine biogeochemistry