Analysis and Combination of Geocenter Motion and Low-Degree Gravity Field Parameters

Geocenter motion can be derived through various space geodetic techniques and hydrological models using different methods, such as direct and inverse. Each technique suffers from specific issues associated with a sparse observing network, orbit modeling errors, or limited sensitivity of the observing techniques to particular components of the geocenter motion, especially to the Z component. Modeling issues result in the spurious signals observed in the time series of the geocenter motion, such as the draconitic periods, orbit resonance terms, and tidal aliasing signals.No official combined products currently exist for the geocenter motion and low-degree gravity field coefficients. Hence, different geocenter models are employed in various applications, such as altimetry, the analysis of GNSS station motions, or GRACE-based gravity field studies.We propose a combination and comparison campaign for the geocenter motion and low-degree gravity field parameters. The first step of the campaign includes technique-specific combinations, such as GNSS-only, DORIS-only, SLR-only, LEO-only, and a confrontation with hydrological models. In the second step, the system-specific solutions will be compared and combined, considering different methods of deriving geocenter motion, including the network shift approach, deriving degree-1 gravity field coefficients, and inverse methods based on surface load displacements, as well as GRACE-derived products supported by geophysical models. The following step will consist of the combination of low-degree gravity field coefficients using the variance component estimation (VCE) technique and other combination techniques to separate system-specific signals from those signals that have geophysical justification. Finally, the combination will be applied to the low-degree gravity field harmonics to expose software-specific issues in SLR-based values, as well as differences between the values obtained from SLR, GRACE, LEO satellites, and inverse methods applied to a dense GNSS network.