Outline

1. Combining Satellite Altimetry, Tide Gauge Observations and an Oceanographic Model to Derive the Baltic Sea Mean Sea Surface Topography Kristin Novotny 1, Gunter Liebsch 3, Andreas Lehmann 2, Reinhard Dietrich1 1) Technische Universität Dresden, Institut für Planetare Geodäsie, Germany 2) Leibniz-Institut für Meereswissenschaften, Kiel, Germany 3) Bundesamt für Kartographie und Geodäsie, Leipzig, Germany

2. Outline 1 Data 2 Combination of the different data to reduce the variance in the altimeter time series 3 Estimation of mean heights along each satellite track 4 Adjustment of crossover differences 5 Result: Baltic Sea MSSTop 6 Error budget 7 Conclusions

3. 1 Data Satellite Altimetry Baltic Sea Oceanographic Model Geoid Model Tide Gauge Observations

4. 1 Data Satellite Altimetry Corrections applied: solid earth tide pole tide no inverse barometer no ocean tide TOPEX: TMR drift correction applied (Keihm et al. 2000)

5. 1 Data • General circulation three-dimensional • coupled sea ice-ocean model • of the Baltic Sea including • Kattegat and Skagerrak • Simplified North Sea connected to • western boundary • High spatial resolution (5 km x 5 km • horizontally, eddy-permitting) • temporal resolution: 6h • Forced by • realistic atmospheric conditions • and river runoff • Run for the period 01/1979-12/2004 Baltic Sea Oceanographic Model

6. 1 Data Satellite Altimetry Baltic Sea Oceanographic Model Geoid Model Tide Gauge Observations Regional geoid model NKG2004 (R.Forsberg et al.) Monthly mean heights from PSMSL data base

7. 1 Data: Structure of the Altimeter Data • data available as along-track data • transformed into binned data set: • mean ground tracks estimated from data • bin cells along the tracks defined • (bin length approximates distance between two 1Hz • altimeter measurements) • bin axis form a plane coordinate system within the bin • - all altimeter data related to corresponding bins, • such forming bin time series

8. 2 Combination of the different data to reduce the variance in the altimeter time series • Sea level variations in the Baltic Sea are • internal, short-term variations (mostly due to atmospheric forcing) • seasonal and interannual variations with external origin (water exchange • with North Sea) • The oceanographic model • very well reflects the Baltic Sea internal effects, • some missing low-frequency signal component connected with • Baltic Sea fill level variations  Spatially constant signal that can be modelled by the difference of (observed-modelled) monthly mean heights at one tide gauge (Stockholm)

9. 2 Combination of the different data to reduce the variance in the altimeter time series  altimeter data were reduced in two steps:

10. TOPEX Ext. Miss. reduced data TOPEX reduced data TOPEX reduced data TOPEX no reduction GFO reduced data ERS-2 reduced data 2 Variance reduction in the altimeter time series Standard deviation

11. 3 Estimation of mean heights along each satellite track • plane for each data bin estimated (along-/cross-track tilt) • bins adjusted by eliminating differences at bin boundaries •  Continuous progression of mean heights along each sat. track

12. 4 Adjustment of crossover differences differences of mean ssh at the crossover positions of the mean sat. tracks (1) contain information about * the accuracy of the mean heights * geographically correlated errors (single-satellite XO) * the relative bias between the missions (dual-satellite XO) (2) had to be minimized in order to tie the different satellite tracks together * one offset estimated for each single satellite track was estimated (least squares solution) * rank deficiency of 1, constraint: sum of all TOPEX offsets be zero Resulting mission biases relative to TOPEX Final rms of the residual crossover differences: 15 mm

13. 4 Adjustment of crossover differences Differences of mean ssh at crossovers, TOPEX single satellite ascending – descending tracks

14. 4 Adjustment of crossover differences no relative bias between TOPEX and TOPEX Extended Mission

15. 4 Adjustment of crossover differences Crossover differences ERS-2 * with ERS-2 * with TOPEX Crossover differences ERS-2 * with ERS-2 * with TOPEX: relative bias of about -90 mm (ERS-2 ssh higher)

16. 4 Adjustment of crossover differences Crossover differences GFO * with GFO * with TOPEX Crossover differences GFO * with GFO * with TOPEX: relative bias of about 0 mm

17. 5 Result: Baltic SeaMSSTop Mean Sea Surface Topography wrt. NKG2004 mean tide geoid

18. 6 Error Budget • rms of the mean heights along the satellite tracks 10..15 mm • rms of crossover differences 15 mm • systematic influences • - altimeter corrections, e.g. wet tropospheric • correction (radiometer observations near the • coast) 15..30 mm • - geoid heights 10..20 mm • total 20..40 mm • total accuracy of Baltic MSSTop can be estimated to • 30..50 mm

19. 7 Conclusions • combination of the altimetric observations with precise modelled • sea surface heights in the Baltic Sea is a powerful tool to reduce • the variance of the altimetric data • reduced altimeter data allow to estimate robust mean heights also • from short time series. • Baltic Sea MSSTop estimated with 3 to 5 cm accuracy • mean ssh differences at crossover locations • - adjusted to tie single satellite tracks together • - contain information about mission‘s geographically correlated • errors / relative bias between missions.

20. Thank You !