Observation impact studies with ocean reanalysis Elisabeth REMY, Nicolas FERRY, Laurent PARENT, Marie DREVILLON, Eric GREINER and the Mercator-Ocean team

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): , - ORCA2/SAM2 : , ORCA2/SAM3 : (Ctrl, in situ only, different MDTs for ) Use of reanalysis in observation impact/sensitivity studies

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/SAM

Glorys (ORCA025/SAM2) Sensitivity of the analysis to the number of assimilated in-situ observations

Planned experiments: One simulation 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

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 geoid Ellipsoid of reference

Cumulative trend of the mean temperature and salinity m ORCA2/SAM3 reanalysis trend T m (°C) trend S 0-300m (PSU) Assim. with the model MDT Assim. with the Rio MDT

Trend of the mean temperature m and deep salinity Glorys1v1 reanalysis , Rio MDT Trend S m (PSU/year) Trend T m (°C/year)

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

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

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.

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

Thank you!

Trend T m In situ only In situ, MDT model + SLA In situ, Rio MDT + SLA