1. 1 Institut für Physikalische Geodäsie INTERGEO 07 Integrated use of GRACE, Altimetry and Models for the Assessment of Interannual Mass Variation in the Mediterranean Sea and Black Sea L. Fenoglio, M. Becker Institut für Physikalische Geodäsie, TU Darmstadt J. Kusche, R. Rietbroek GeoForschungsZentrum Potsdam S. Grayek, E. Stanev ICBM Universität Oldenburg

2. 2 Motivation Basin-averaged watermass change from Grace & steric-corrected altimetry (BAMV) Accuracy of annual & inter-annual BAMV estimation Closing the Water Budget Black Sea: Water balance & numerical modelling of 3D circulation Conclusion OUTLINE

3. 3 MED (2.5 10 6 km 2 ) WEST-MED (0.5 10 6 km 2 ) EAST-MED (2.0 10 6 km 2 ) BLACK SEA(0.48 10 6 km 2 ) Motivation Data Method Results Conclusions STREMP PROJECT AREA (in coastal oceans)  h! seawater mass GRACE.NE. a-s (in coastal oceans)  h! a – s = G – h (both terms filtered) Closing the balance: dm/dt = P-E+R+FG+B (MED) dm/dt = P-E+R-FB (BS) smoothing (de-striping) to reduce spatially correlated noise & RE-SCALE

4. 4 G: GRACE : - L2 GSM (GFZ rl04), GSM 2002.04-2006.9 (2-90, 400 km) - atmosphere and ocean response restored (GAD) A: ALTIMETRY single & multi-mission (T/P, J1, E2, Envisat 02-07) O: STERIC(T,S) oc: ECCO/JPL, MFSTEP (MED) cl: Medar, WOA05, Ishii (MED), Black Sea H: HYDROLOGY (LAD/Fraser, WGHM) 0.5x0.5, 1x1 grids R: River Run-off (Climatology, Water Gap) E: Evaporation (ECMWF, NCEP) P : Precipitation (ECMWF, NCEP) F: Flow at Straits (Bosphoro, Gibraltar) Integration Motivation Data Method Results Conclusions Grace R P FG Altimetry E FB Steric Hydrology 9 components :

5. 5 Reduction of correlated GRACE noise: Gaussian filter Anisotropic filter (Kusche 2007) Center of mass correction to compare with altimetry: annual model from GPS loading inversion (Jansen et al., 2006, see JIGOG Presentation) Annual amplitude eq. Water height= 2 cm G: GRACE Motivation DataMethod ResultsConclusions Example: annual Sine/Cosine

6. 6 A: ALTIMETRY / O: OCEANOGRAPHY Motivation DataMethod ResultsConclusions Single-mission, multi-mission, objective analysed grids IBC to be applied in agreement to GRACE processing and ocean modelling (DUACS grids, in Black Sea MOG2D correction not available) Correction of atmospheric forcing effects is an issue in semi-closed basins ! Med Sea: MFSTEP / steric component Black Sea: 3-D modelling with the “best” water balance terms PARAMETRISATION: Horizontal tracer diffusion: geopotential laplacian operator Horizontal dynamic viscosity: geopotential bilaplacian operator Vertical viscosity/diffusivity: TKE closure scheme, enhanced vertical diffusion. Horizontal: 1/9° x 1/12°, Vertical: 31 levels FORCING: Meterological forcing: bulk aerodynamic formulas using atmospheric temperature and humidity, winds, and simulated SST ASSIMILATION of SLA from altimetry (“Cooper and Heins” scheme)

7. 7 BASIN AVERAGE Motivation Data Method Results Conclusions Basin Average Kernel

8. 8 GRACE – hydrology*Altimetry* – steric* COMPARISON G-h and a-s (filtered time-series) The worstThe best & Motivation Data Method Results Conclusions

9. 9 steric 25% SLA hydrology 80% GRACE 2002.6-2004.6 steric 60% SLA, hydrology 30% GRACE MED BASIN AVERAGE: Annual Amplitude &Phase, trend (eq. water height) FieldMED Amp (mm) MED Phase (mm) MED Trend (mm/y) BS Amp. (mm) BS Phase( deg BS Trend (mm/y) altimetry 83 +/- 2284+/-21.1 +/- 0.5--- Steric 55 +/ 4251+/-4-1.6+/-0.229 +/- 4238+/-40.0 Hydrology 26 +/- 329 +/- 7-64 +/- 559 +/- 5- Grace filt. 43 +/- 78 +/-7-56 +/- 775 +/- 7- a-s 45 +/- 4301+/- 5--- A-s_filt 24 +/- 3301+/- 63.2 +/- 2.2 G-h 28 +/- 6327+/ 135.4 +/- 2.6--- G-h_scaled 52 +/- 11327+/ 12--- 22002.6-2006.6 Motivation Data Method Results Conclusions (02-04 in Fenoglio et al. GRL2006, JGR in press )

10. 10 MED BASIN AVERAGE: G-h ~ a-s with : GRACE, LAD, J1, ECCO rms=14 mm, corr=0.8, N=475.4 +/- 2.6 mm/yr 3.2 +/- 2.2 mm/yr 2002.6-2006.7 Motivation Data Method Results Conclusions

11. 11 Error estimates for monthly means, annual component and trend (from RMS and Error Propagation) in 2002.6 – 2004.6 1 cm (*1-2)! --1013Grace – h_filt - - - 10 2 Annual Phase error(d) 3715WM from a-s -715WM GRACE -310GRACE_filt -911Hydrology 5613Steric 148altimetry Trend (mm/yr) Annual Amplitude error (mm) Eq. water Monthly error(mm) Field 1-2 cm (*2-4) ACCURACY OF ESTIMATION FOR MED BASIN AVERAGE * * (Fenoglio et al. GRL2006, JGR in press ) Motivation Data Method Results Conclusions

12. 12 ACCURACY of ESTIMATION: BASIN DETAILS Motivation Data Method Results Conclusions

13. 13 WATER BUDGET IN THE MEDITERRANEAN SEA Hydrological cycle: water thickness change (mm/mon) MED E P R E-P-R E-P FG = (E-P-R-B) + dm/dt P-E (mm/mon) R (mm/mon) FG (a-s) (mm/mon) FG (G-h) (mm/mon) 16-30539+/-760+/-7 48 +/-7 R~ B Motivation Data Method Results Conclusions dm/dt = P-E+R+FG+B (MED) Annual Amplitude

14. 14 BS: A DIFFICULT REGION? -H: huge contribution to GRACE -A: strong interannual, ibc not realistic - S: small ~ constant - large water fluxes Motivation Data Method Results Conclusions

15. 15 Mean yearly water fluxes Motivation Data Method Results Conclusions Contribution of individual terms to BS level change - P: from atmospheric analyses (large errors). - E: computed by model using bulk formulas (big errors) - R: for some rivers only, input statistically generated - B: Bosporus transports reconstructed (linearly from R) FOR BS NUMERICAL MODELLING of 3D CIRCULATION

16. 16 Problem in reconstructing BS Water balance: SENSITIVITY TO STRAIT TRANSPORTS (ST) Still problems with theoretical/statistical reconstruction Constraining the balance by altimetry (0D) –> consistently close water balance a) ST Statistically reconstructed from R b ) ST Computed as a residual ( use of satellite data) Motivation Data Method Results Conclusions

17. 17 COMPARING RESULTS Motivation Data Method Results Conclusions Integrated P-E+R-B watermass change from a-s dm/dt = P-E+R-FB (BS)

18. 18 Simulated Mean Sea Level 0D/3D Linear equation of state 0D (mean area) forcing fields Unesco eq. of state (non linear) 2D forcing fields BEST (Presently) FIT OF SEA LEVEL TO DIFFERENT DATA Motivation Data Method Results Conclusions Model captures well the vertical structure of thermohaline fields (known from observations)

19. 19 In MED the water-mass signal could be recovered (both seasonal and long-term variations), in the BS it is more difficult. Basin averages: smoothed spatial averaging kernel (isotropic and anisotropic), small improvement with anisotropic MED : Basin average a-s and G-h with comparable error estimates (15 mm monthly, 1 cm Annual Ampl., 2 mm/yr) Land hydrology contamination to be considered, dominant in Black Sea Closing the water balance in MED (Gibraltar estimation ~ observations) Closing the water balance in BS is necessary for realistic modelisation. BS is complex system (LARGE sensitivity to water fluxes & errors in WF components, straits flows inaccurate, numerical parameterizations of straits transport not solved). Motivation Data Method Results Conclusions CONCLUSION

20. 20 Oceanography: Improve modeling : Physical (not by residuals) closing of water budgets, More appropriate assimilation scheme, focus on absolute sea level analysing its role for the evolution of baroclinic structure and circulation Geodesy: Improve filtering of GRACE data reduce leakage of hydrology in watermass estimation Overall : Budget Closure & separation of components Motivation Data Method Results Conclusions OUTLOOK