Section: Partnerships and Cooperations

European Initiatives

Collaborations with Major European Organizations

• Partner: GDR-E CONEDP

• Subject: Control of Partial Differential Equations.

• Partner: University of Reading, Department of Meteorology, Department of Mathematics

• Subject: Data assimilation for geophysical systems.

• Partner: Vicent Caselles of the Pompeu Fabra University, Barcelona Spain

• Subject: Image processing problems such as histogram transfer [18] or optical flow estimation. 6.5.1

• Partner: European Centre for Medium Range Weather Forecast. Reading (UK)

• World leading Numerical Weather Centre, that include an ocean analysis section in order to provide ocean initial condition fo the coupled ocean atmosphere forecast. They play a significant role in the NEMOVAR project in which we are also partner.

• Partner: Met Office (U.K) National British Numerical Weather and Oceanographic service. Exceter (UK).

• We do have a strong collaboration with their ocean initialization team through both our NEMO, NEMO-ASSIM and NEMOVAR activities. They also are our partner in the NEMOVAR consortium.

• Partner: Marine Hydrographic Institute, Natinal Ac.Sci. Ukraine, Sevastopol.

• We have a long term collaboration about data assimilation with the Black Sea. This collaboration is getting to a new level with their plan to adopt NEMO and NEMOVAR for their operational forecasting system. On our side, we will benefit from their expertise on the Black Sea dynamics, that is an excellent test case for our developments and methods.

• Partner: British Antarctic Survey, Cambridge, UK,

• Subject: Antarctic ice core chronology (AICC2012).

• Partner: University of Copenhagen, Ice and Climate Group, Denmark

• Subject: Antarctic ice core chronology (AICC2012).

• Partner: University of Strathclyde (Glasgow, UK)

• Subject: Quasi-second order analysis for the propagation and characterization of uncertainties in geophysical prediction 6.4.5

• Partner: Institute of Numerical Mathematics, Russian Academy of Sciences

• Subject: Quasi-second order analysis for the propagation and characterization of uncertainties in geophysical prediction 6.4.5