Abstract
A terrestrial reference frame (TRF) is derived based on historical geodetic data and is normally updated every 5–6 years. The three most recent International Terrestrial Reference System (ITRS) realizations, ITRF2014, DTRF2014, and JTRF2014, were determined with different strategies, which has resulted in different signals in the reference frame parameters. In this paper, we used the continuous site position time series of International GNSS Service (IGS) from 1995 to 2020 as a benchmark to investigate the characteristics of the three frames. In the comparison, the ITRS realizations were divided into the determination and prediction sections, where the site coordinates of the TRFs were extrapolated in the prediction period. The results indicated that the orientation and scale parameters of the ITRF2014, and the IGS solutions showed excellent agreement during the determination period of ITRF2014, while, during the prediction period, the orientation parameter diverged from IGS with rates of 11.9, 5.5, and 8.4 μas/yr, and the scale degraded with a rate of −0.038 ppb/yr. The consistency of the origin parameters between the DTRF2014 and the IGS solutions during the two periods changed from 0.07, 0.11, and −0.15 mm/yr to −0.17, −0.18, and −0.12 mm/yr; the consistency of orientation parameters from −3.6, −1.9, and 2.9 μas/yr to 15.9, −2.3, and 13.2 μas/yr; and the consistency of scale from 0.007 to −0.005 ppb/yr. In the comparison between the JTRF2014 and IGS solutions, annual signals in the origin differences were 1.5, 3.0, and 2.4 mm in the X, Y, and Z components, respectively, and the temporal variation trends in different periods disagreed with their long-term trends. Obvious trend switches in the rotation parameters were also observable, and the complex temporal variation characteristics of the scale offsets may be related to the scale definition strategy applied in different TRFs.
Highlights
The realization and maintenance of a terrestrial reference frame (TRF) is foundational for the understanding and investigation of the linear and nonlinear time variations of the solid earth’s shape caused by various geophysical processes, such as plate tectonics [1,2,3], glacial isostatic adjustment [4,5], and large scale surface mass variations [6,7], and sea level rise [8,9,10,11]
All three realizations are computed on the basis of the data from four space geodetic techniques [16], including Global Navigation Satellite System (GNSS), Doppler Orbitography and Radiopositioning integrated by Satellite (DORIS), Satellite Laser Ranging (SLR), and Very
Constant offsets exist in most station position time series between DTRF2014 and International GNSS Service (IGS); the magnitude may differ from the previous section in the comparison between ITRF2014 and IGS
Summary
The realization and maintenance of a terrestrial reference frame (TRF) is foundational for the understanding and investigation of the linear and nonlinear time variations of the solid earth’s shape caused by various geophysical processes, such as plate tectonics [1,2,3], glacial isostatic adjustment [4,5], and large scale surface mass (atmosphere, snow, glacier, soil moisture, and ground water storage) variations [6,7], and sea level rise [8,9,10,11]. Since geocenter motions estimated from the GNSS technique are biased by orbit modeling errors and severe correlation with other parameters (like clock offsets and tropospheric parameters) [20,21,22], the origin of the final combined solution is aligned to IGb08 with minimum constraints (no-net-translation, NNT) applied to a subset of core stations [23]; the orientation is aligned to IGb08 with no-net-rotation (NNR) applied to the same core network; and the scale is defined by using the igs08.atx based satellite PCO values [18,24]. The geodetic datum (origin, scale, and orientation) between the two long-term realizations, the ITRF2014 and DTRF2014, agreed within 5–6 mm by applying 14-parameter Helmert transformations individually for the four different space techniques. The IGS solutions are compared to ITRF2014, DTRF2014, and JTRF2014 and their predictions
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