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Observation impact studies with ocean reanalysis

Elisabeth REMY, Nicolas FERRY, Laurent PARENT, Marie DREVILLON, Eric GREINER and the Mercator-Ocean team

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Reanalysis provide ocean state estimates over longer time period than the operational systems that are regularly evolving. Their analysis can reveal impact of the changes in the observation system.

Different diagnostics can be usefull to identify observations impact:

- physical diagnostics

- assimilation diagnostics: innovation, increment, residual.

Recent reanalysis at Mercator-Océan:

- Glorys1v1 (ORCA025/SAM2): 2002-2008,

- ORCA2/SAM2 : 1980-2008, ORCA2/SAM3 : 1960-2005 (Ctrl, in situ only, different MDTs for 1993-2005)

Use of reanalysis in observation impact/sensitivity studies

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Sensitivity of the global analysis error to the number of assimilated in-situ observations

Number of assimilated observations

Global mean misfit to T observations in°C

Global rms misfit to T observations in °C

ORCA2/SAM3 1960-2005

1960-1992 1993-2005

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Glorys (ORCA025/SAM2)2002 - 2008

Sensitivity of the analysis to the number of assimilated in-situ observations

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Planned experiments:

One simulation 2002-2009 of Glorys without the ARGO data,

Tests of dispersion of virtual floats using the code « ARIANE » (lagrangian diagnostics tool) with the reanalysis outputs.

OSE experiments for in situ observations

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The assimilation of Sea Level Anomalies requires the use of a Mean Dynamical Topography.

Inconsistencies can exist between the dynamical height deduced from the in-situ observations and from the « SLA + MDT » infomation, if the prescribed MDT differs from the « real one » or the model is not able to represent it.

- OSE with ORCA2 : synthetic « Rio » MDT and model MDT

- Currently looking at MDT errors impact with Glorys

- No bias correction

MDT sensitivity

SSH = MSSH + SLADT = MDT + SLA

geoidEllipsoid of reference

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Cumulative trend of the mean temperature and salinity 0-300 m

ORCA2/SAM3 reanalysis 1993-2001

trend T 0-300 m

(°C)

trend S 0-300m

(PSU)

Assim. with the model MDT Assim. with the Rio MDT

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Trend of the mean temperature 0-300 m and deep salinity

Glorys1v1 reanalysis 2002-2008, Rio MDT

Trend S 700-1500m (PSU/year)

Trend T 0-300 m (°C/year)

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Mdt rio

Mean Atlantic Meridional Overturning Streamfunction

ORCA2/SAM3 with Rio MDT

Glorys1v1 with Rio MDT

ORCA2/SAM3 with model MDT

ORCA2 without assimilation

ORCA025 without assimilation

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Need of realistic mean dynamical topography to assimilate SLA + in situ observations : better position of the gyres.

the analysis with ORCA2 or ORCA025 follows the prescribed MDT (Rio or model),

still problems when using the Rio MDT:

• effect on unconstrained regions/variables of the system (deep T-S fields),

• local problems can have large impact trhrough the ocean dynamic. (The MOC anomaly reveals a regional unrealistic meridional cirulation cell located around 35°O. This response is probably due to a pressure gradient, linked to the MDT constrain (work in progress)).

Planned experiments :

test of the new Rio MDT based on GRACE geoid.

MDT sensitivity : comments

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Real Time and re-processed observations

Mean sea level evolution from NRT observations (blue), DT observations (red), ORCA2°/SAM3 reanalysis (green) and PSY3v2 (black)

In situ observations data sets

Use of CORA in GLORYS and CORIOLIS in PSY3v2 : differences are seen in the analysis (M. Drevillon presentation)

→ Comparison of the reanalysis and real time outputs.

SLA observations Delayed Time /Near Real Time

To look at climatological signal, re-processed data are necessary.

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Long term Impact of changes in the observation systems can be difficult to follow in an operational system which is rapidly evolving.

We can see impact of observation system changes/incoherencies between data sets in our reanalysis.

To evaluate precisely their impact, it requires the setup of dedicated diagnostics/experiments.

The conclusions of those experiments will partly depend on the system (model configuration, assimilation scheme, error specification…), light configurations can be usefull.

We are still trying to make use of the assimilated observations in an optimal way (observation operator, observation error covariance matrix estimation…)

The use of the nemo adjoint is planned to identify model bias sources. Can also be used for observation array design?

Conclusion

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Thank you!

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Trend T 0-300 m

In situ only In situ, MDT model + SLA In situ, Rio MDT + SLA