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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