Presentation is loading. Please wait.

Presentation is loading. Please wait.

Mercator Ocean activity Yann Drillet and Mercator Ocean team.

Similar presentations


Presentation on theme: "Mercator Ocean activity Yann Drillet and Mercator Ocean team."— Presentation transcript:

1 Mercator Ocean activity Yann Drillet and Mercator Ocean team

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

3 3 Mercator Ocean operational production and services Monitoring of the production : Production is delivery in time in more than 98% Monitoring of the quality: tor- ocean.fr/eng/scie nce/Qualification -validation2 Monitoring the of users

4 4 Carateristitics of the systems Lellouche et al., 2013, Ocean Science. GlobalIBI RTRANRTRAN Physical modelNEMO ¼° and 1/12° 50L NEMO ¼° 75LNEMO 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/APISCES 1/12° online AssimilationSEEK 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 SEEK and 3Dvar bias correction (SLA, SST, T/S) Atmospsheric Forcing ECMWFERA interimECMWFERA interim Period2007 (2013)-RT present Products available on MyOcean (http://www.myocean.eu/) and Mercator Part are distributed on ftp server GOV multi model approach

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

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

7 7 Ocean Model 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 NEMO consortium at european level. Partnership between

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

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

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

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

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

13 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 14 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 IBI36 : 12/03/2009 SSH From NR(IBI36) : /03/2009 (5day-Assimilation window) J2; J1n; En Swot

15 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 16 Model intercomparison Ryan et al, GODAE OceanView Class 4 forecast verication framework: Global ocean inter-comparison

17 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


Download ppt "Mercator Ocean activity Yann Drillet and Mercator Ocean team."

Similar presentations


Ads by Google