SEAMLESS: Services based on Ecosystem data AssiMiLation: Essential Science and Solutions (SEAMLESS)

The project is led by PML and focuses on state indicators that are linked to the ocean “health” (e.g. to oxygenation, acidification, eutrophication), “services” (e.g. to sustainable aquaculture) and “response” to climate change (e.g. to the transfer of carbon in the ocean depths). Currently, these indicators are monitored and/or simulated routinely by observatories and models of the European Copernicus Marine Services (CMEMS). SEAMLESS will improve the current CMEMS methods that integrate the information from monitored and simulated indicators, i.e. “data assimilation” methods.

SEAMLESS will provide improved ocean model data to:

• Monitor and assess marine ecosystem health in policy frameworks
• Implement marine spatial planning
• Operate aquaculture and fisheries
• Investigate climate change impacts on ocean ecosystems

More specifically, SEAMLESS will focus on the following eight ocean indicators: oxygen concentration, pH, phytoplankton concentration and phenology, trophic efficiency, primary production and particulate organic carbon. Our project will cover, directly or indirectly, all the CMEMS ecosystem models and marine systems. We will advance stochastic ensemble data assimilation methods, encompassing Kalman and particle filters and variational approaches. These methods will be used to assimilate biogeochemical and physical data from both satellites and in situ platforms (e.g. gliders and biogeochemical-Argo floats).