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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. Use of reanalysis in observation impact/sensitivity studies.

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observation impact studies with ocean reanalysis
Observation impact studies with ocean reanalysis

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


Use of reanalysis in observation impact/sensitivity studies

  • 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)

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

ORCA2/SAM3 1960-2005

Number of assimilated observations

Global mean misfit to T observations in°C

Global rms misfit to T observations in °C




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

Glorys (ORCA025/SAM2)2002 - 2008


OSE experiments for in situ observations

  • 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.




Ellipsoid of reference

MDT sensitivity

  • 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

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

ORCA2/SAM3 reanalysis 1993-2001

Assim. with the model MDT

Assim. with the Rio MDT

trend T 0-300 m


trend S 0-300m



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

Glorys1v1 reanalysis 2002-2008, Rio MDT

Trend T 0-300 m (°C/year)

Trend S 700-1500m (PSU/year)


Mean Atlantic Meridional Overturning Streamfunction

Mdt rio

ORCA2/SAM3 with Rio MDT

ORCA2 without assimilation

ORCA2/SAM3 with model MDT

ORCA025 without assimilation

Glorys1v1 with Rio MDT


MDT sensitivity : comments

  • 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.

Real Time and re-processed observations

  • SLA observations Delayed Time /Near Real Time
  • To look at climatological signal, re-processed data are necessary.

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.


  • 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?

Trend T 0-300 m

In situ, Rio MDT + SLA

In situ, MDT model + SLA

In situ only