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On a possible contribution of VLBI to geocenter realization via satellites
assessed by simulations
N. Mammadaliyev1, S. Glaser2, K. Balidakis2, P. Schreiner2, R. König2,K. Neumayer2, J. Anderson1, R. Heinkelmann2, H. Schuh1,2
1 Technische Universität Berlin, Berlin, Germany 2 GFZ German Research Centre for Geosciences, Potsdam, Germany
Journées 20198 October 2019, Paris
Motivation
Achieved accuracy of the ITRF 2014
OriginAccuracy: 3 mmStability: 0.2 mm/yr
ScaleAccuracy: 1.37 ppbStability: 0.02 ppb/yr
Motivation
Requirements to a TRF on GGOS
OriginAccuracy: 1 mmStability: 0.1 mm/yr
ScaleAccuracy: 0.10 ppbStability: 0.01 ppb/yr
Currently DORIS, GNSS, SLR and VLBI are combined applying local ties to construct global terrestrial reference frames
(Altamimi et al. 2016) (Gross et al. 2009)
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DFG Project at GFZ and TU Berlin with the targets:
– Investigation of the global TRF accuracy
– Co-location in space using space ties
Focus of this study:Geocenter estimates from VLBI observations to satellites - a simulation study
Geocenter motion: translation motion of the center of network (CN) relative to Earth's center of mass (CM)
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Strategy
Data
Orbit integration
Network configuration– Network A : 14 Stations, weakly distributed observation network,
V = 0.21 Mm3
– Network B : 15 Stations, globally well distributed observation
network, V = 0.56 Mm3
Perigee[km]
Apogee [km]
Inclination [o]
Eccentricity
LEO Sat. 762 7472 63.4 0.32
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Data
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Geophysical loading models
Non-tidal atmospheric, oceanic and hydrological loadings:− have been consistently derived,
− conserve the global mass, and
− have been successfully tested in GNSS and VLBI data analysis(e.g., Männel et al. 2019)
Products generated by the Earth-System-Modeling group GFZ (ESMGFZ) (Dill and Dobslaw 2013)(https://isdc.gfz-potsdam.de/esmdata/loading/)
Data
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Scheduling• Daily sessions• Time span: January 2008 – December 2009• Observation time: 1 min• Only spacecraft observations
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Scheduling• Daily sessions• Time span: January 2008 – December 2009• Observation time: 1 min• Only spacecraft observations
Simulation• Observations simulated in VieVS2tie software (Plank et al. 2014)
• Different geophysical models + white noise• 10 different scenarios (5 geophysical models × 2 station
networks)
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Scheduling• Daily sessions• Time span: January 2008 – December 2009• Observation time: 1 min• Only spacecraft observations
Simulation• Observations simulated in VieVS2tie software (Plank et al. 2014)
• Different geophysical models + white noise• 10 different scenarios (5 geophysical models × 2 station
networks)
Estimation• Station coordinates, troposphere, clock, geocenter
coordinates
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Results
• Difference between two networks – 4.3 mm in Y component
Non-tidal atmospheric loading
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0.41 mm/27o
1.30 mm/8o
1.88 mm/11o
0.40 mm/15o
1.53 mm/-2o
1.88 mm/18o
Corr: 0.86
Corr: 0.87
Corr: 0.90
Amp./Phase:
Amp./Phase:
Amp./Phase:
Non-tidal oceanic loading
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• Difference between two networks < 1.5 mm for all components0.99 mm/-53o
0.30 mm/-78o
0.17 mm/-4o
1.00 mm/-54o
0.21 mm/-78o
0.15 mm/-33o
Corr: 0.98
Corr: 0.94
Corr: 0.95
Amp./Phase:
Amp./Phase:
Amp./Phase:
Hydrological loading
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• Difference between two networks – 1.5 mm in Y component1.84 mm/-87o
1.43 mm/77o
1.71 mm/-71o
1.77 mm/-82o
2.28 mm/92o
1.57 mm/68o
Corr: 0.97
Corr: 0.96
Corr: 0.95
Amp./Phase:
Amp./Phase:
Amp./Phase:
Total non-tidal loadings
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• Difference between two networks – up to 5.5 mm3.66 mm/-73o
2.59 mm/38o
3.69 mm/-37o
3.62 mm/-70o
3.11 mm/53o
3.44 mm/-35o
Corr: 0.98
Corr: 0.92
Corr: 0.95
Amp./Phase:
Amp./Phase:
Comparison
Simulation vs. IGSGeocenter coordinates from the IGS contribution to ITRF2014 (Rebischung et al. 2016)
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3.66 mm/-73o
2.59 mm/38o
3.69 mm/-37o
2.41 mm/-70o
3.27 mm/37o
4.67 mm/142o
Corr: 0.48
Corr: 0.68
Corr: -0.36
Amp./Phase:
Amp./Phase:
Amp./Phase:
Simulation vs. SLRUT/CSR monthly geocenter estimates from the analysis of SLR observations (Cheng et al. 2013)
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3.66 mm/-73o
2.59 mm/38o
3.69 mm/-37o
3.40 mm/-61o
1.85 mm/42o
5.61 mm/-45o
Corr: 0.83
Corr: 0.74
Corr: 0.82
Amp./Phase:
Amp./Phase:
Amp./Phase:
Conclusion
Conclusion• VLBI’s capability to determine geocenter explored via simulations to LEO satellite, utilizing non-tidal loading models
− VLBI to LEO satellite observations have been scheduled and simulated for two different station networks
− Station network affects geocenter estimation up to 5 mm
− Effects of the geophysical loading models:− Non-tidal atmospheric loading : to Y and Z components
− Non-tidal oceanic loading : to X component
− Hydrological loading : to all components
− Total impact of the loadings can reach up to 12 mm
• Good agreement with real data:− SLR (UT/CSR) : in all components− GNSS (IGS combined) : in X and Y components
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Conclusion• VLBI’s capability to determine geocenter explored via simulations to LEO satellite, utilizing non-tidal loading models
− VLBI to LEO satellite observations have been scheduled and simulated for two different station networks
− Station network affects geocenter estimation up to 5 mm
− Effects of the geophysical loading models:− Non-tidal atmospheric loading : to Y and Z components
− Non-tidal oceanic loading : to X component
− Hydrological loading : to all components
− Total impact of the loadings can reach up to 12 mm
• Good agreement with real data:− SLR (UT/CSR) : in all components− GNSS (IGS combined) : in X and Y components
Thanks for your attention!22
References• Altamimi, Z., Rebischung, P., Métivier, L., and Collilieux, X. (2016), ITRF2014: A new release of the
International Terrestrial Reference Frame modeling nonlinear station motions, J. Geophys. Res.Solid Earth, 121, 6109– 6131, https://doi.org/10.1002/2016JB013098.
• Chen, J. & Wilson, Clark & Eanes, Richard & Nerem, Robert. (1999). Mass Variations in the EarthSystem and Geocenter Motions. IERS Technical Note 25.
• Cheng, M.K., J.C. Ries, B.D. Tapley (2013) Geocenter Variations from Analysis of SLR data, inReference Frames for Applications in Geosciences, International Association of Geodesy Symposia,Vol. 138, 19-26 (Springer-Verlag Berlin Heidelberg).
• Collilieux, X., Altamimi, Z., Ray, J., van Dam, T., and Wu, X. (2009), Effect of the satellite laserranging network distribution on geocenter motion estimation, J. Geophys. Res., 114, B04402,https://doi.org/10.1029/2008JB005727.
• Dill, R. and H. Dobslaw (2013), Numerical simulations of global-scale high-resolution hydrologicalcrustal deformations, J. Geophys. Res. Solid earth 118, doi:10.1002/jgrb.50353.
• Gross R., Beutler G., Plag HP. (2009) Integrated scientific and societal user requirements andfunctional specifications for the GGOS. In: Plag HP., Pearlman M. (eds) Global Geodetic ObservingSystem. Springer, Berlin, Heidelberg
• Männel, B. H. Dobslaw, R. Dill, S. Glaser, K. Balidakis, M. Thomas, and H. Schuh (2019) Correctingsurface loading at the observation level: Impact on global GNSS and VLBI station networks, Journalof Geodesy (accepted)
• Plank, L., Boehm, J., and Schuh, H. (2014). Precise station positions from VLBI observations tosatellites: a simulation study, Journal of Geodesy, 88(7):659–673.
• Rebischung, P., Altamimi, Z., Ray, J. et al. J Geod (2016) 90: 611.https://doi.org/10.1007/s00190-016-0897-6
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Backup
Common visibility of satellite
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Number of observations
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Satellite observations of Network A
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Satellite observations of Network A
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Satellite observations of Network B
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Satellite observations of Network B
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Sea level loading
• Calculated from daily barystatic sea-level variations
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