Salient results from the Merging Ocean Models and Observations at the Meso and Sub-mesoscales (MOMOMS) project

Emmanuel Cosme (UGA-CNRS-IRD-GINP/IGE, France)


Jean-Michel Brankart (UGA-CNRS-IRD-GINP/IGE, France); Pierre Brasseur (UGA-CNRS-IRD-GINP/IGE, France); Marina Duran Moro (UGA-CNRS-IRD-GINP/IGE, France); Laura Gomez Navarro (UGA-CNRS-IRD-GINP/IGE, France); Lionel Gourdeau (CNES-CNRS-IRD-UPS/LEGOS, France); Florian Le Guillou (UGA-CNRS-IRD-GINP/IGE, France); Sammy Metref (UGA-CNRS-IRD-GINP/IGE, France); Julien Le Sommer (UGA-CNRS-IRD-GINP/IGE, France); Ananda Pascual (CSIC-UIB/IMEDEA, Spain); Michel Tchilibou (CNES-CNRS-IRD-UPS/LEGOS, France); Ann'Sophie Tissier (UGA-CNRS-IRD-GINP/IGE, France)

Event: 2020 Ocean Surface Topography Science Team Meeting (virtual)

Session: Salient results from the 2017-2020 OSTST PIs

Presentation type: Type Forum

This contribution highlights progresses made in the Merging Ocean Models and Observations at the Meso and Sub-mesoscales (MOMOMS) OSTST project. The project mainly focused on (i) Observability of mesoscale dynamics by altimetry, (ii) new, multi-scale algorithms for data inversion and assimilation, and (iii) multi-sensor based ocean reconstruction. Two new algorithms are presented to address the assimilation of non-local observations, i.e. observations possibly affected by geographically distant quantities, and the assimilation of observation sets containing non-local, large-scale signature. Both problems are rendered difficult in Ensemble data assimilation by the necessary use of analysis localization techniques. Applications with altimetry are presented. The presentation also introduces an algorithm combining the assimilation of altimetry, which adjusts the mesoscale dynamics, with the assimilation of SST images to adjust the finer scales. Finally, the benefit of assimilating (future) surface current observation in addition to altimetry is shortly illustrated.
Emmanuel Cosme