Mercator Ocean activity Yann Drillet and Mercator Ocean team.
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Transcript of Mercator Ocean activity Yann Drillet and Mercator Ocean team.
Mercator Ocean activity
Yann Drillet and Mercator Ocean team
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Outline
Operational production and services
R&D activities
Model
Assimilation
OSE/OSSE
Intercomparison
Conclusions
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Mercator Ocean operational production and services
Monitoring of the production : Production is delivery in time in more
than 98%
Monitoring of the quality: http://
www.mercator-ocean.fr/eng/
science/Qualification-validation2
Monitoring the of users
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Carateristitics of the systems
Lellouche et al., 2013, Ocean Science.
Global IBI
RT RAN 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
SEEK and 3Dvar bias correction (SLA, SST, T/S)
Atmospsheric Forcing
ECMWF ERA interim ECMWF ERA interim
Period 2007 (2013)-RT 1993-2013 2010-present 2002-2011
Products available on MyOcean (http://www.myocean.eu/) and Mercator ([email protected])
Part are distributed on ftp server GOV multi model approach
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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
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Validation of chlorophyl interannual variability
1st EOF
Winter 2002 NAO+
Winter 2005 NAO-
Model Observations
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Ocean Model
Global and regional ocean physic and biogeochemistry configurations
Reference simulation : global 1/12° 1979-2012Sensitivity experiments:•Numerical scheme in NEMO model, advection, diffusion, mixing •Surface forcingCoupling physical ocean with atmosphere, Sea Ice and biogeochemistry
NEMO consortium at european level. Partnership between
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UBS EEN 1
EEN 2EEN 3.
Impact on advection and diffusion schemes on global 1/12° configuration
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Assimilation
• Bias correction • Observation error• Ensemble approach• Assimilation of new observations (sea ice, surface
velocity)
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Adaptive tuning of observations errors
• Ideally, ratio=1 • ratio < 1 => obs. error overestimated• ratio > 1 => obs. error underestimatedRatio Desroziers =
[ residual (innovation)T ]
R
E
Jason1 SSTEnvisat
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.
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Adaptive tuning of observations errors
• Ideally, ratio=1 • ratio < 1 => obs. error overestimated• ratio > 1 => obs. error underestimatedRatio Desroziers =
[ residual (innovation)T ]
R
E
Jason1 SSTEnvisat
The prescription of observation errors in the assimilation systems is often too approximate...
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Adaptive tuning of observations errors - SLA -
cm
0 5 10
Envisat error on 20061227 without tuning
cm
0 5 10
Envisat error on 20061227 with tuning
Fit Slope= 0.78 Fit Slope= 0.71
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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
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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) : 09-14/03/2009
(5day-Assimilation window)J2; J1n; En Swot
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Ssh Correlation (2009) : NR(Data) vs FreeSim vs OSSE1 vs OSSE2
NR/FreeSim
0.0 0.5 1.0
Mean : 59%
0.0 0.5 1.0
NR/OSSE1
Mean : 72%
0.0 0.5 1.0
NR/OSSE2
Mean : 80%
NR (IBI36, ‘True Ocean’)FreeSim; OSSE1; OSSE2
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Model intercomparison
Ryan et al, GODAE OceanView Class 4 forecast verication framework: Global ocean inter-comparison
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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