IGS Analysis Center Workshop, 2-6 June 2008, Florida, USA

1. IGS Analysis Center Workshop, 2-6 June 2008, Florida, USA GPS in the ITRF Combination D. Angermann, H. Drewes, M. Krügel, B. Meisel Deutsches Geodätisches Forschungsinstitut, München E-Mail: angermann@dgfi.badw.de

2. Outline • ITRS Combination Center at DGFI • Input data for TRF computations • Analysis and accumulation of GPS time series • GPS in the inter-technique combination • Contribution of GPS to the datum realization • Conclusions and outlook

3. ITRS Combination Center at DGFI • General concept: Combination on the normal equation level • Software: DGFI Orbit and Geodetic Parameter Estimation Software (DOGS) Geodetic datum

4. Input data sets for TRF computations (1/2) ITRF2005: Time series of station positions and EOP • ITRF2005 data sets are not fully consistent, the standards and • models were not completely unified among analysis centers • Shortcomings concerning GPS: • IGS solutions are not reprocessed (e.g., model and software changes) • Relative antenna phase center corrections were applied

5. Input data sets for TRF computations (2/2) GGOS-D: Time series of station positions and EOP • Improvements of GGOS-D data compared to ITRF2005: • Homogeneously processed data sets - Identical standards, conventions, models, parameters - GPS: PDR (Steigenberger et al. 2006, Rülke et al. 2008) • Improved modelling - for GPS: absolute instead of relative phase centre corr. - for VLBI: pole tide model was changed GGOS-D: German project of BKG, DGFI, GFZ and IGG funded by BMBF

6. TRF computation strategy • First step: Analysis of station coordinate time series and computation of a reference frame per technique • Modelling time dependent station coordinates by • epoch positions • linear velocities • - (seasonal signals) • - discontinuities Second step: Combination of different techniques by - relative weighting - selection of terrestrial difference vectors (local ties) - combination of station velocities and EOP - realization of the geodetic datum

7. TRF per technique (1/4) Analysis of GPS station position time series Instrumentation changes Earthquakes Seasonal variations ITRF2005. 221 discontinuities in 332 GPS stations (1996 - 2005) GGOS-D: 95 discontinuities in 240 GPS stations (1994 - 2007)

8. TRF per technique (2/4) Effect of annual signals ? Equating of station velocities ? 1997 2000 2003 2006 1997 2000 2003 2006 Sol. ID 1 Sol. ID 2 GPS station Irkutsk (Siberia) GPS station Hofn (Iceland) Velocity differences w.r.t. a linear model

9. TRF per technique (3/4) Seasonal signals - Comparison with geophysical data [cm] 2 0 -2 Models consider atmospheric, oceanic and hydrologic mass loads: NCEP, ECCO, GLDAS Potsdam Correlation coefficient = 0,50 2 0 -2 Krasnoyarsk Correlation coefficient = 0,79 2 0 -2 Bahrain Correlation coefficient = 0,73 1997 1999 2 001 2003 2005

10. TRF per technique (4/4) Shape of seasonal signals can be approximated by sine/cosine annual and semi-annual functions Brasilia Ankara Estimation of annual signals in addition to velocities ? • Disadvantages / open questions: • More parameters (stability) ? • Seasonal signal geophysically meaningful ? • How to parameterize seasonal signals ? • Advantages: • Improved velocity estimation • Better alignment of epoch solutions

11. Computation of the TRF (1/3) Selection of local ties at co-location sites SLR-VLBI (9) SLR-GPS (25) VLBI-GPS (27)

12. Computation of the TRF (2/3) Selection of terrestrial difference vectors (1) Three-dimensional differences between space geodetic solutions (GPS and VLBI) and terrestrial difference vectors [mm] ITRF2005 GGOS-D = stations in southern hemisphere Krügel et al. 2007: Poster presented at AGU Fall Meeting 2007

13. Computation of the TRF (3/3) Selection of terrestrial difference vectors (2) Mean pole difference Mean pole difference: 35 mas (≈1 mm) Network deformation: ≤ 0.3 mm Number of co-locations: 19 ITRF2005: Pole difference: 41 mas Deformation: 1.0 mm No. co-locations: 13 Network deformation

14. Realization of the geodetic datum (1/4)

15. Realization of the geodetic datum (2/4) Station velocity residuals for 56 core stations used to realize the kinematic datum of the ITRF2005D solution w.r.t. APKIM

16. Realization of the geodetic datum (3/4) Translation and scale estimates of similarity transformations between combined PDR05 and weekly solutions (Rülke et al., JGR 2008)

17. Realization of the geodetic datum (4/4) Datum information of GPS observations (compared to SLR) Cdatum = (GT CGPS-1 G)-1 Method: CGPS: Covariance matrix of GPS solution (loose constrained) G: Coefficients of 7 parameter similarity transformation matrix Cdatum: Covariance matrix of datum parameters Standard deviations for datum parameters [mm]

18. Conclusions and outlook • Discontinuities: Number of jumps reduced due to homogeneous re- processing; discontinuity tables among techniques should be adjusted. • Annual signals: Treatment of seasonal variations in station positions (e.g., by estimating sine/cosine functions) should be investigated. • Co-locations: Discontinuities are critical; at least two GPS instruments should be operated at each co-location site. • Geodetic datum: GPS reprocessing provides stable results for the scale and for the x- and y-component of the origin, the z-component shows large seasonal variations which should be investigated. • GPS reprocessing is essential for the next ITRF (unified standards and models should be applied for different techniques).