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 (products@mercator-ocean.fr)

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