Effect of the satellite laser ranging network distribution on geocenter motion estimation

SLR network translations estimated between a quasi-instantaneous station position set,
theoretically expressed with respect to the center of mass of the Earth (CM), and a secular
reference frame are the signature of the motion of the CM with respect to the Earth crust.
Geocenter motion is defined here to be the motion of the CM with respect to the geometric
center of the solid Earth surface (CF). SLR translational variations cannot be rigorously
interpreted as identical to geocenter motion due to the sparse and nonuniform distribution of
the SLR network. Their difference is called the network effect, which should be dominated
at subdecadal timescales by loading signals.We have computed translation time series of the
SLR network using two independent geophysically based loading models. One is a
displacement model estimated from surface fluid data (Green’s function approach), called
forward model, and the other is a displacement model estimated from GPS and ocean bottom
pressure (OBP) data, called inverse model. The translation models have been subtracted
from their respective geocenter motion models computed from degree-1 mass load
coefficients in order to evaluate their network effect biases. Scatter due to the SLR network
effect is at the level of 1.5 mm RMS. It could slightly shift the phase of the annual SLR
geocenter motion estimate by less than 1 month and could affect X and Z annual geocenter
motion amplitudes at the 1-mm level, which is about one third of the expected signal. Two
distinct methods are suggested to account for network effect when comparing SLR
translations to geocenter motion models. The first is to add the network effect term predicted
by a displacement model to the geocenter motion loading model. The second relies on an
adequate combination of SLR and GPS products to estimate SLR translation that could be
better compared with geocenter motion.