Today, oceanographic research is no more conceivable without advanced mathematical methods, either to understand and simulate the behaviour of the ocean, or to interpret an synthesize all available observations. This is why the MEOM team participates to the development of these methods and to the conception and implementation of appropriate numerical tools

NEMO (Nucleus for European Modelling of the Ocean) is a state-of-the-art modelling framework for oceanographic research and operational oceanography.

Solutions of ocean models are most often computed at the nodes of a grid with finite resolution. The figure shows the horizontal grid of the DRAKKAR global ocean circulation model at a 1/2° résolution. (Every 10 lines is drawn.) | The computation of these solutions requires considerable informatic resources. The figure shows the division into subdomains of the DRAKKAR global ocean model grid at a 1/4° résolution (1442 x 1021 x 46 nodes) in order to distribute the computation (3400 CPU hours, for one year of simulation) over 186 processors of one of the IDRIS supercomputers (IBM Power4). | Bathymetry of the Gulf of Lions continental shelf, as resolved by a hugh resolution model grid (1/60° horizontal resolution and 130 vertical levels). |

The MEOM team participates to the development of NEMO in several ways:

- Developement of specific numerical methods: handling of the coastline, three-dimensional mesh refinements (AGRIF project), or coupling of models with different physics (Comodo project).
- Developement of parameterizations for small scale ocean processes (submesoscale), which have been proved (by non-hydrostatic ocean modelling) to have an important impact on the general ocean circulation.

The contribution of the MEOM team to the development of NEMO is mainly supported by the DRAKKAR and MERSEA. projects.

Data assimilation is the generic name of methods enabling to compute a coherent description of the time evolution of a phenomenon (for us, the ocean circulation), by combining a partial observation dataset to the theoretical knowledge of the phenomenon (for us, an ocean model, like NEMO).

The MEOM team contributes to the development of ocean data assimilation methods in several ways:

- Developments of reduced order Kalman filters (SEEK filter);
- Hybridation if a reduced rank Kalman filter (like the SEEK filter) with the 4D-VAR (in particular, by the development of multiscale estimation algorithm);
- Development of data assimilation for parameter estimation, with the aim of improving the parameterization of the ocean forcing, of the subgrid scale processes, or of the biogeochemical processes;
- Development of data assimilation for coupled models (circulation/ecosystem, ocean/atmosphere), or nested models (open ocean/coastal models).

The contribution of the MEOM team to the development of data assimilation is mainly supported by the MERSEA and ONR projects.