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Assimilation of Altimeter data in the ECWMF operational ocean analysis

Assimilation of Altimeter data in the ECWMF operational ocean analysis. Arthur Vidard <vidard@imag.fr> Madalena A. Balmaseda David Anderson. Outline. The new ECMWF operational ocean analysis system Historical reanalysis and real time Use of altimeter data

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Assimilation of Altimeter data in the ECWMF operational ocean analysis

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  1. Assimilation of Altimeter data in the ECWMF operational ocean analysis Arthur Vidard <vidard@imag.fr> Madalena A. Balmaseda David Anderson Venice, 13-17 March 2006

  2. Outline • The new ECMWF operational ocean analysis system • Historical reanalysis and real time • Use of altimeter data • Sensitivities to the assimilation scheme - Combining altimeter with in-situ information • Sensitivities to the prescribed MDT • Grace derive products versus model MDT • Summary and conclusions Venice, 13-17 March 2006

  3. ECMWF: Weather and Climate Dynamical Forecasts 10-Day Medium-Range Forecasts Seasonal Forecasts Monthly Forecasts Atmospheric model Atmospheric model Wave model Wave model Ocean model Real Time Ocean Analysis ~8 hours Delayed Ocean Analysis ~12 days Venice, 13-17 March 2006

  4. Real time Probabilistic Coupled Forecast time Ocean reanalysis Consistency between historical and real-time initial initial conditions is required Quality of reanalysis affects the climatological PDF Main Objective: to provide ocean Initial conditions for coupled forecasts Coupled Hindcasts, needed to estimate climatological PDF, require a historical ocean reanalysis Venice, 13-17 March 2006

  5. 1 2 3 4 5 6 7 8 9 10 11 12 BRT ocean analysis: D1-12 NRT ocean analysis: D1 Time (days) Assimilation at D1-12 Assimilation at D1-5 Operational Ocean Analysis Schedule D1 • BRT ( Behind real time ocean analysis): ~12 days delay to allow data reception • For seasonal Forecasts. • Continuation of the historical ocean reanalysis • NRT (Near real time ocean analysis):~ 8 hours delay • For Monthly forecasts Venice, 13-17 March 2006

  6. From AVISO, ~twice a week Data acquisition • SLA gridded maps from T/P+ERS+GFO • Anomalies respect to 7 year mean • Weekly averages Data processing • Spatial Interpolation into model grid • Time interpolation to obtain daily values • Persist last daily value for the NRT analysis Reception and preparation of the altimeter data TO THE OCEAN DATA ASSIMILATION Venice, 13-17 March 2006

  7. System-3 • Ocean model: HOPE (~1x1, equatorial refinement) • Assimilation Method OI • Assimilation of T + Balanced relationships (T-S, ρ-U) • 10 days assimilation windows, increment spread in time • New Features • ERA-40 fluxes to initialize ocean • Retrospective Ocean Reanalysis back to 1959. • Multivariate on-line Bias Correction . • Assimilation of salinity data. • Assimilation of altimeter-derived sea level anomalies. • 3D OI Venice, 13-17 March 2006

  8. Assimilation of Salinity Contribution To ENACT: Assimilation of salinity along T surfaces (TM #458, Haines et al MWR) and are orthogonal Nice property: Venice, 13-17 March 2006

  9. T/S conserved OI T/S Changed OI Assimilation of S(T) not S(z) Assimilation in the ECMWF operational System 3 Venice, 13-17 March 2006

  10. Where/how does the altimeter information fit? • Comparison of 3 different methods • Comparison of 3 different MDTs Starting point: Assimilation of in situ T and S. HOPE-E 1°x1° global (down to .3°x1° at the equator) OI of T (with S, u and v balanced increment) and S (along T surfaces). ERA40/OPS forcing Quality controlled in situ Temperature and Salinity from ENSEMBLES dataset. Followed by automatic QC In all the cases, no altimeter data is assimilated poleward of 60 degrees Venice, 13-17 March 2006

  11. Method 1: CH96 is used to convert SLA into Temperature increments, that combined with the model background are used as pseudo observations along with in situ observation of temperature in the OI of T. This approach was introduced in Segschneider et al (2000). Venice, 13-17 March 2006

  12. Method 2: CH96 is used to convert SLA into Temperature and Salinity increments, that combined with the model background fields, are used as background Temperature and Salinity for the assimilation of in situ T and S. Venice, 13-17 March 2006

  13. Method 3: similar to Method 2, but the assimilation of in situ T and S is performed first, and the analysed T and S are used as background for the assimilation of SLA Venice, 13-17 March 2006

  14. Temperature NINO3 Temperature NINO4 Method 1 Method 2 Method 3 Comparison with observationsmean (model – obs) Method 1 has larger bias: Warmer East Pacific and Colder West Pacific Venice, 13-17 March 2006

  15. Method 1 Method 2 Method 3 Comparison with observationsmean (model – obs) Temperature EQATL Salinity EQATL Method 1 has larger bias also in the Atlantic, both in temperature and in salinity. Venice, 13-17 March 2006

  16. T/S conserved T/S conserved OI CH96 T/S Changed OI So… we choose Method 2 Assimilation of S(T) not S(z) Venice, 13-17 March 2006

  17. CHOICE OF MEAN DYNAMIC TOPOGRAPHY Ingredients: We tried ‘external’ mean sea level products derived from GRACE (Rio4/5 from CLS, NASA, …) but the choice of the reference global mean is not trivial and the system can be quite sensitive to this choice Observed SLA from T/P+ERS+GFO Respect to 7 year mean of measurements A Mean Sea Level Venice, 13-17 March 2006

  18. Results are very sensitive to the MDT TRPAC Averaged Temperature in first 300m Not good for consistent historical reanalysis Venice, 13-17 March 2006

  19. Why such a sensitivity? • Systematic differences between MODEL-MDT and GRACE derived products: • Pacific-Atlantic SL gradient is steeper in MODEL-MDT • We need appropriate methods to treat this systematic difference in the assimilation scheme. • If correct, the information from GRACE-MDT could be used before the altimeter era. • For System 3 we have chosen the MODEL_MDT Venice, 13-17 March 2006

  20. No Data Assimilation Assimilation:T+S Assimilation:T+S+Alt Correlation with OSCAR currents Monthly means, period: 1993-2005 Seasonal cycle removed Venice, 13-17 March 2006

  21. Summary • 3 different methods to assimilate altimeter-derived SLA have been tested in the ECMWF ocean analysis system (OI-based) • It is shown that in the method by Segschneider et al 2000 can increase the bias in the analysis • The impact of using GRACE-derived MDT in the ECMWF has been evaluated • There are large systematic differences between the ECMWF analysis and GRACE-derived MDTs • In particular, the Pacific-Atlantic SL gradient is larger in the analysis. • It is premature to use the MDT from GRACE. We need adequate multivariate bias-methods to use this information. • The use of altimeter SLA improves the representation of the interannual variability of the currents. • The assimilation of altimeter has been implemented in the new ECMWF operational system. Venice, 13-17 March 2006

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