Assessment of the CMEMS global biogeochemical forecasting operational system, with assimilation of Ocean Colour data

The operational production of data-assimilated biogeochemical state of the ocean is one of the challenging core projects of the Copernicus Marine Environment Monitoring Service (hereafter CMEMS). In that framework, Mercator Ocean International is in charge of improving the realism of its global 1⁄4° coupled physical-biogeochemical simulations, analyses and re‐analyses, and to develop an effective capacity to routinely estimate the biogeochemical state of the ocean, including, amongst others, the implementation of biogeochemical data assimilation. Primary objectives are to enhance the time representation of the seasonal cycle in the real time and reanalysis systems, and to provide a better control of the production in the equatorial regions.

In that framework, Mercator Ocean International has successfully updated its global biogeochemical analysis and forecasting system with an Ocean Color data assimilation capability. In this system, successfully commissioned in September 2019, the biogeochemical model (NEMO/PISCES) is offline coupled with the dynamical ocean (1/12° coarsened to 1/4° resolution) from the CMEMS global physical analysis and forecasting operational system (PSY4), at a daily frequency, and benefits from the assimilation of satellite (SSH-SST-SIC) and in situ physical data. Nevertheless, a biogeochemical climatological damping is activated in the biogeochemical model in order to mitigate the impact of some misconstrained processes (vertical velocities) from this physical data-assimilated forcing (under investigation). The dedicated assimilation of biogeochemical data relies on a simplified version of the SEEK filter, where the forecast error covariances are built from a fixed-basis - but seasonally variable - ensemble of anomalies computed from a multi-year numerical experiment (without biogeochemical data assimilation) with respect to a running mean. Regarding Ocean Colour observations, the system relies, as a first step, on the CMEMS Global Ocean surface chlorophyll concentration products, delivered in NRT.

The objective of this presentation is thus to provide (1) a short description of the implementation of the aforementioned data assimilation methodology in the forecasting system; (2) a synthesis of the assessment of this global biogeochemical forecasting system, by cross-comparing the assimilated solution with various datasets, both spatial (Ocean Colour) and in situ (BGC-Argo, GLODAP), and (3) a synthetic overview of the impact/benefit of the assimilation of the Ocean Colour data.