1. Assimilation of Sea Surface Temperature in OPAVAR State of the art: Relaxation to Reynolds SST (daily, interpolated to ORCA grid, ENACT) - strong relaxation coefficient for seasonal forecasting (E.N.A.C.T) (λ = - 200 W / m².K) - moderate relaxation coefficient for ocean modelling standard approach (λ = - 40 W / m².K) Initial workplan for assimilation of SST data - Reynolds SST, daily, gridded data - Turn off relaxation for SST - Use T, S in-situ data for validation only - Univariate formulation of B since T-S relation doesn’t apply at the surface Ricci Sophie CERFACS/ECMWF meeting 11-2006

2. Assimilation of Reynolds SST product First approximation (but wrong) : R diagonal Should the assimilation be turned on/off in semi-closed sea ? Should the relaxation be turned on/off in semi-closed sea ? Should the relaxation to SSS be modified? Should we assimilate past 60 N and 60 S and how ? Which format should we choose for outputting the statistics ? with daily gridded data, we could create daily maps of BmO and AmO, or output all information for each data (ENACT way). Ricci Sophie CERFACS/ECMWF meeting 11-2006 Questions

3. Assimilation of Reynolds SST product

4. Development : R non-diagonal Observation errors for gridded products will likely be highly correlated In the assimilation system we need to model R -1 - (Inverse) correlations in space can be modelled using a diffusion equation - (Inverse) correlations in time can be modelled using a diffusion eq. or recursive filter What is the impact of the correlations in R ? - Simple examples Should we make the background vertical error correlations dependent on the mixed layer depth to assimilate SST more effectively ? If so, the diffusion model has to be solved (to be developed!) in implicitly. What is the influence of the outer loops? Assimilation of Reynolds SST product Ricci Sophie CERFACS/ECMWF meeting 11-2006

5. Future work: other SST products Non exhaustive listing: - RTG-SST NCEP, daily, 1/2° (Reynolds like?) - SAFO (SST AVHRR) - GHRSST Need to adapt R to gappy data