Geocenter Variations Assessment using Frequency Analysis and Allan Variance Method

The objective of this work is to characterize the signals and noises of Geocenter variations time series obtained from different space geodesy techniques as Global Positioning System (GPS), Doppler Orbitography and Radiopositioning Integrated on Satellite (DORIS), and Satellite Laser Ranging (SLR). The proposed methodology is based on the estimation of periodic signals by performing frequency analysis using FAMOUS software (Frequency Analysis Mapping On Unusual Sampling) and evaluation of level and type of noises by Allan variance technique and Three Corned Hat (TCH) method. The available data concern 13 years (from 1993 to 2006) of weekly series of Geocenter residuals components and scale factor variations, according to ITRF2000. The results estimated are more accurate according to GPS and SLR of about 2-8 mm than DORIS of about 8-42 mm, for Geocenter. Better RMS of scale factor was obtained of about 0.1ppb (0.6mm) for GPS technique than SLR and DORIS with 0.6 and 0.9 ppb (3.6 and 5.4mm), respectively. The estimated seasonal signals amplitudes are in the range of few milimeters per technique with centimetre level for Z Geocenter component of DORIS. The Geocenter motion derived from SLR technique is more accurate and close to the geodynamic models. The noise analysis shows a dominant white noise in the SLR and DORIS Geocenter solutions at a level of 0.6-1 mm and 10-40 mm, respectively. However, the GPS solution is characterized by a flicker noise at millimetre level, relating to mismodeling systematic errors.

Tropospheric and range biases in Satellite Laser Ranging

The Satellite Laser Ranging (SLR) technique provides very accurate distance measurements to artificial Earth satellites. SLR is employed for the realization of the origin and the scale of the terrestrial reference frame. Despite the high precision, SLR observations can be affected by various systematic errors. So far, range biases were used to account for systematic measurement errors and mismodeling effects in SLR. Range biases are constant for all elevation angles and independent of the measured distance to a satellite. Recently, intensity-dependent biases for single-photon SLR detectors and offsets of barometer readings and meteorological devices were reported for some SLR stations. In this paper, we study the possibility of the direct estimation of tropospheric biases from SLR observations to LAGEOS satellites. We discuss the correlations between the station heights, range biases, tropospheric biases, and their impact on the repeatability of station coordinates, geocenter motion, and the global scale of the reference frame. We found that the solution with the estimation of tropospheric biases provides more stable station coordinates than the solution with the estimation of range biases. From the common estimation of range and tropospheric biases, we found that most of the systematic effects at SLR stations are better absorbed by elevation-dependent tropospheric biases than range biases which overestimate the total bias effect. The estimation of tropospheric biases changes the SLR-derived global scale by 0.3 mm and the geocenter coordinates by 1 mm for the Z component, causing thus an offset in the realization of the reference frame origin. Estimation of range biases introduces an offset in some SLR-derived low-degree spherical harmonics of the Earth’s gravity field. Therefore, considering elevation-dependent tropospheric and intensity biases is essential for deriving high-accuracy geodetic parameters.

The mean seasonal cycle in relative sea level from satellite altimetry and gravimetry

Satellite altimetry and gravimetry are used to determine the mean seasonal cycle in relative sea level, a quantity relevant to coastal flooding and related applications. The main harmonics (annual, semiannual, terannual) are estimated from 25 years of gridded altimetry, while several conventional altimeter “corrections” (gravitational tide, pole tide, and inverted barometer) are restored. To transform from absolute to relative sea levels, a model of vertical land motion is developed from a high-resolution seasonal mass inversion estimated from satellite gravimetry. An adjustment for annual geocenter motion accounts for use of a center-of-mass reference frame in satellite orbit determination. A set of 544 test tide gauges, from which seasonal harmonics have been estimated from hourly measurements, is used to assess how accurately each adjustment to the altimeter data helps converge the results to true relative sea levels. At these gauges, the median annual and semiannual amplitudes are 7.1 cm and 2.2 cm, respectively. The root-mean-square differences with altimetry are 3.24 and 1.17 cm, respectively, which are reduced to 1.93 and 0.86 cm after restoration of corrections and adjustment for land motion. Example outliers highlight some limitations of present-day coastal altimetry owing to inadequate spatial resolution: upwelling and currents off Oregon and wave setup at Minamitori Island.

Improving the products of global GNSS data analysis by correcting for loading displacements at the observation level

<p>In recent years, the sensitivity of the GNSS station time series to the loading displacements is demonstrated by multiple studies, mainly for the non-tidal atmospheric loading (NTAL) and non-tidal ocean loading (NTOL). But the impact of the loading displacements is beyond the coordinate time series, including and not limited to geocenter motion, Earth Orientation Parameters, satellite orbits, etc. We extensively evaluate the impact on and the improvements of the reference frame products from reprocessed 25 years of GPS and GLONASS network solution with a consistent application of non-tidal loading and Continental Water Storage Loading (CWSL) displacement at the observational level. We also discussed the differences of correcting for the loading displacements at the observation level and correction at the product level on GNSS station coordinates and Geocenter motions, we elaborate the advantage of the inclusion of correction at the observational level.</p><p> </p><p>Significant improvements are found in estimated coordinate time series, almost 90% of the station shows improved WRMS in North and Up directions and over 75% in East. CWSL dominates the contribution in the North direction. The annual Geocenter variations (over 80% of the x and y components) can be explained by the loading displacement. A small and consistent reduction of orbit disclosure is found among all 32 GPS satellites and most of the GLONASS satellites (23 out of 25) after the inclusion of all the loading displacements.  All the improvements demonstrate the urgent need for the adoption of loading displacements in the global GNSS analysis.</p>

Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction

Geocenter is the center of the mass of the Earth system including the solid Earth, ocean, and atmosphere. The time-varying characteristics of geocenter motion (GCM) reflect the redistribution of the Earth’s mass and the interaction between solid Earth and mass loading. Multi-channel singular spectrum analysis (MSSA) was introduced to analyze the GCM products determined from satellite laser ranging data released by the Center for Space Research through January 1993 to February 2017 for extracting the periods and the long-term trend of GCM. The results show that the GCM has obvious seasonal characteristics of the annual, semiannual, quasi-0.6-year, and quasi-1.5-year in the X, Y, and Z directions, the annual characteristics make great domination, and its amplitudes are 1.7, 2.8, and 4.4 mm, respectively. It also shows long-period terms of 6.09 years as well as the non-linear trends of 0.05, 0.04, and –0.10 mm/yr in the three directions, respectively. To obtain real-time GCM parameters, the MSSA method combining a linear model (LM) and autoregressive moving average model (ARMA) was applied to predict GCM for 2 years into the future. The precision of predictions made using the proposed model was evaluated by the root mean squared error (RMSE). The results show that the proposed method can effectively predict GCM parameters, and the prediction precision in the three directions is 1.53, 1.08, and 3.46 mm, respectively.

Geocenter coordinates derived from multi-GNSS: a look into the role of solar radiation pressure modeling

The Global Navigational Satellite System (GNSS) technique is naturally sensitive to the geocenter motion, similar to all satellite techniques. However, the GNSS-based estimates of the geocenter used to contain more orbital artifacts than the geophysical signals, especially for the Z component of the geocenter coordinates. This contribution conveys a discussion on the impact of solar radiation pressure (SRP) modeling on the geocenter motion estimates. To that end, we process 3 years of GPS, GLONASS, and Galileo observations (2017–2019), collected by a globally distributed network of the ground stations. All possible individual system-specific solutions, as well as combinations of the available constellations, are tested in search of characteristic patterns in geocenter coordinates. We show that the addition of a priori information about the SRP-based forces acting on the satellites using a box-wing model mitigates a great majority of the spurious signals in the spectra of the geocenter coordinates. The amplitude of the 3 cpy (about 121 days) signal for GLONASS has been reduced by a factor of 8.5. Moreover, the amplitude of the spurious 7 cpy (about 52 days) signal has been reduced by a factor of 5.8 and 3.1 for Galileo and GPS, respectively. Conversely, the box-wing solutions indicate increased amplitudes of the annual variations in the geocenter signal. The latter reaches the level of 10–11 mm compared to 4.4 and 6.0 mm from the satellite laser ranging observations of LAGEOS satellites and the corresponding GNSS series applying extended empirical CODE orbit model (ECOM2), respectively. Despite the possible improvement in the GLONASS-based Z component of the geocenter coordinates, we show that some significant power can still be found at periods other than annual. The GPS- and Galileo-based estimates are less affected; thus, a combination of GPS and Galileo leads to the best geocenter estimates.

Copernicus Sentinel Orbit Validation – Investigations on systematic geographical differences

<p>The Copernicus POD (Precise Orbit Determination) Service delivers, as part of the PDGS of the Copernicus Sentinel-1, -2, and -3 missions, orbital products and auxiliary data files for their use in the corresponding PDGS processing chains. The precise orbit results from the three missions are validated based on orbit comparisons to independent orbit solutions from member of the Copernicus POD Quality Working Group (QWG). In the case of Sentinel-3 a validation based on satellite laser tracking (SLR) measurements is also possible. The orbit comparisons are done based on orbit time series. Typically, only daily RMS metrics are derived, and its time-series mean and standard deviation are provided. Another possibility is to analyse the dependence of orbit differences with geographical differences; this is already done for the altimeter satellites to guarantee long-term stability of the orbit solutions.</p><p>Geographical orbit differences may reveal systematics due to, e.g., different background models or different geocenter motion models used in the orbit determination process. The geographical orbit differences of all six satellites and from all POD QWG contributions are analysed and checked for model- or satellite-specific systematics to improve the orbit quality and long-term stability.   </p><p>Additionally, it is proposed to analyse the orbit differences (with respect to other orbital solutions, either reduced-dynamic or kinematic) with Fourier transformation, in order to derive amplitude vs. frequency plots. This could provide light into the sub-daily differences. The Fourier analysis of the sub-daily differences will be assessed for all the six satellites.</p>

The Estimation and Prediction of Geocenter Motion Based on GNSS Weekly Solutions

<p>The development of satellite space geodesy technology makes the establishment of global terrestrial reference frame based on the Earth’s center of mass become reality. Precise and stable terrestrial reference frame is the foundation of the Earth science research, while determination and analysis of the position of the Earth's center of mass and its change is an important part to build high precision terrestrial reference frame. Based on GNSS weekly solutions provided by IGS, the geocenter motion (GM) time series between 2007 and 2017 are obtained by means of net translation method. Then the amplitude of the annual term of geocentric motion is 2.27mm, 1.84mm and 2.13mm in the direction of X, Y and Z respectively, and the amplitude of the half-year term is 0.1mm, 0.20mm and 0.15mm respectively. In addition, some other inter-annual changes with relatively small contribution rate are found. Finally, in order to get reliable GM prediction ,two kinds of methods are used, which are ARMA and SSA+ARMA. In the short-term prediction, the accuracy of the two methods is the same, both can reach the millimeter level of prediction accuracy, but SSA+ARMA is more stable. SSA+ARMA algorithm is much better in the medium and long-term scale, and it can provide 1mm medium term prediction accuracy and 1.5mm long term prediction accuracy.</p>