1. Mercator Ocean activity
Yann Drillet and Mercator Ocean team

2. Outline Operational production and services R&D activities Conclusions
Model
Assimilation
OSE/OSSE
Intercomparison
Conclusions

3. Mercator Ocean operational production and services
Monitoring of the quality:
Monitoring of the production : Production is delivery in time in more than 98%
Monitoring the of users

4. Carateristitics of the systems
Global
IBI RT
RAN
Physical model
NEMO ¼° and 1/12° 50L
NEMO ¼° 75L
NEMO 1/36° 50L tide and pressure
NEMO 1/12° 75L Tide and pressure
Biogeochemistry
model
PISCES ¼° forced by RT ¼°
PISCES ¼° forced by free simulation ¼°
N/A
PISCES 1/12° online
Assimilation
SEEK and 3Dvar bias correction (SLA, SST, T/S)
SEEK and 3Dvar bias correction (SLA, SST, T/S, ICE)
N/A weekly initialised with 1/12° solution. In development
Atmospsheric
Forcing
ECMWF
ERA interim
Period
2007 (2013)-RT
2010-present
Products available on MyOcean ( and Mercator
Part are distributed on ftp server GOV multi model approach
Lellouche et al., 2013, Ocean Science.

5. Useful tool for mapping errors velocities for drift applications
Quality of the analyses and forecast, Lagrangian drift
- Drifters give observed velocities and positions.
- Model velocities give virtual positions.
Distance between observed and virtual positions after 1 day
And after a 3-day Lagrangian drift
Useful tool for mapping errors velocities for drift applications
Scott et al., 2012; Drévillon et al., 2013, Ocean Dynamics + QuO Va Dis?

6. Validation of chlorophyl interannual variability
Winter 2002 NAO+
1st EOF
Winter 2005 NAO-
Model
Observations

7. Ocean Model NEMO consortium at european level. Partnership between
Global and regional ocean physic and biogeochemistry configurations
Reference simulation : global 1/12°
Sensitivity experiments:
Numerical scheme in NEMO model, advection, diffusion, mixing
Surface forcing
Coupling physical ocean with atmosphere, Sea Ice and biogeochemistry

8. Impact on advection and diffusion schemes on global 1/12° configuration
UBS
EEN 1
EEN 2
EEN 3.

9. Assimilation
Bias correction
Observation error
Ensemble approach
Assimilation of new observations (sea ice, surface velocity)

10. Adaptive tuning of observations errors
The prescription of observation errors in the assimilation systems is often too approximate...
Ideally, ratio=1
ratio < 1 => obs. error overestimated
ratio > 1 => obs. error underestimated
[ residual (innovation)T ] R E
Ratio Desroziers = a
Jason1
Envisat
SST
The objective of this diagnostic is to improve the error specification by tuning an adaptive weight coefficient a acting on the error of each assimilated observation.

11. Adaptive tuning of observations errors
The prescription of observation errors in the assimilation systems is often too approximate...
Ideally, ratio=1
ratio < 1 => obs. error overestimated
ratio > 1 => obs. error underestimated
[ residual (innovation)T ] R E
Ratio Desroziers =
Jason1
Envisat
SST

12. Adaptive tuning of observations errors - SLA -cm
Envisat error on without tuning cm
Envisat error on with tuning
Fit Slope= 0.78
Fit Slope= 0.71

13. OSEs and OSSEs experiments
Sensitivity of the forecasting system to current observations network
Number of altimeter satellite
Argo vs other in situ observations
New satellites in the system (Saral, HY2)
Design/impact of new observation network
Deep argo
SWOT

14. (5day-Assimilation window)
SWOT OSSE
Simulated Observations from IBI36 (Free Model, 1/36°~3km, 2009) :
SSH : (25 hours mean ; Inverse Barometer and tide removed)
Altimeters : J2, J1n, En
Swot ( 7Km)
Insitu : Temperature and salinity profiles (CORA Data positions)
SST : Daily Mean with 25 Km for horizontal resolution
SSH From NR(IBI36) : 09-14/03/2009
(5day-Assimilation window)
J2; J1n; En Swot
SSH IBI36 : 12/03/2009

15. Ssh Correlation (2009) : NR(Data) vs FreeSim vs OSSE1 vs OSSE2
NR/FreeSim
Mean : 59%
NR/OSSE1
Mean : 72%
NR/OSSE2
Mean : 80%
NR (IBI36, ‘True Ocean’)
FreeSim; OSSE1; OSSE2

16. Model intercomparison
Ryan et al, GODAE OceanView Class 4 forecast verication framework: Global ocean inter-comparison

17. Conclusions
Operational service with daily forecast
Update annually ocean reanalysis
In development new version of the global 1/12° analysis and forecasting system.
R&D work to improve the system and to improve interaction and coupling with atmosphere, sea ice, biogeochemistry.
Development of assimilation scheme (SAM2) and NEMO model
Involvement in GOV TT