The Terrestrial Reference Frame is fundamental for monitoring Earth rotation in space and for all geoscience applications that require absolute positioning and precise orbit determination of artificial satellites. The goal of this session is to provide a forum to discuss reference systems theory, data analysis improvement, realization and applications in geosciences and society, with a special emphasis on the scientific applications of the International Terrestrial Reference Frame (ITRF), and namely its next release, the ITRF2020. Participants can discuss concerns not only related to the contributing technique services, but also all ITRF uses, ranging from local, regional to global applications. Contributions are sought from the individual technique services and various ITRF users, covering the complete range of topics, such as data analysis, parameter estimation and correction models. Of special interest is the assessment of the impact of non-linear station motions, e.g. periodic signals and post-seismic deformations. Contributions by the technique services related to the preparation for ITRF2020 focusing especially on identifying and mitigating technique systematic errors are highly appreciated. Contributions on local tie survey methodology are also welcome.
vPICO presentations: Tue, 27 Apr
Earth’s surface is elastically deformed by time-variable surface mass loads such as variations in atmospheric surface pressure, ocean bottom pressure, and terrestrial water storage. We look at the individual environmental loading contributions from the three different subsystems (atmosphere, terrestrial water storage, ocean) as well as from sea-level variations induced by the global water mass balance between land and ocean. Dividing the contributions into a set of period bands by means of a Wavelet decomposition, we show that non-tidal atmospheric surface loading (NTAL) by far dominates non-tidal ocean (NTOL) and hydrospheric loading (HYDL) for periods as long as a few months. The contribution of terrestrial water storage is continuously growing for increasingly longer periods and dominates atmospheric pressure at periods of 300 days and above. Ocean dynamics including sea-level variations due to the seasonal global mass balance are only important in the immediate vicinity of the coast.
In representative regions, we compare different environmental loading estimates, e.g. ESMGFZ based on ECMWF operational atmospheric data, NTAL and NTOL based on ECMWF ERA5, HYDL based on GRACE/GRACE-FO. Depending on the geographical location and considered frequency range, different estimates for NTOL and HYDL can exhibit large differences. In contrast, all latest loading models show a very consistent picture of atmospheric surface pressure loading deformations. To evaluate the ability of different GNSS solutions to confirm the vertical deformations predicted by the geophysical fluid models, we compared at selected sites vertical station coordinates from six GNSS solutions with loading model predictions. In many cases, GNSS-derived variations heavily dependent on subjective choices within the GNSS data processing.
How to cite: Dill, R., Dobslaw, H., and Klos, A.: Predicting elastic deformations of the crust induced by environmental loading on time-scales from days to decades, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2197, https://doi.org/10.5194/egusphere-egu21-2197, 2021.
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.
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.
How to cite: Wang, L., Thaller, D., Susnik, A., and Dach, R.: Improving the products of global GNSS data analysis by correcting for loading displacements at the observation level, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12920, https://doi.org/10.5194/egusphere-egu21-12920, 2021.
Over the past two decades, numerous studies demonstrated that the stochastic variability in GNSS position time series – often referred to as noise – is both temporally and spatially correlated. The time correlation of this stochastic variability can be well approximated by a linear combination of white noise and power-law stochastic processes with different amplitudes. Although acknowledged in many geodetic studies, the presence of such power-law processes in GNSS position time series remains largely unexplained. Considering that these power-law processes are the primary source of uncertainty for velocity estimates, it is crucial to identify their origin(s) and to try to reduce their influence on position time series.
Using the Least-Squares Variance Component Estimation method, we analysed the influence of removing surface mass loading deformation on the stochastic properties of vertical land motion time series (VLMs). We used the position time series of over 10,000 globally distributed GNSS stations processed by the Nevada Geodetic Laboratory at the University of Nevada, Reno, and loading deformation time series computed by the Earth System Modelling (ESM) team at GFZ-Potsdam. Our results show that the values of stochastic parameters, namely, white noise amplitude, spectral index, and power-law noise amplitude, but also the spatial correlation, are systematically influenced by non-tidal atmospheric and oceanic loading deformation. The observed change in stochastic parameters often translates into a reduction of trend uncertainties, reaching up to -75% when non-tidal atmospheric and oceanic loading deformation is highest.
How to cite: Gobron, K., Rebischung, P., de Viron, O., Van Camp, M., and Demoulin, A.: Influence of non-tidal atmospheric and oceanic loading deformation on the stochastic properties of over 10,000 GNSS vertical land motion time series, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9860, https://doi.org/10.5194/egusphere-egu21-9860, 2021.
A local tie survey was carried out at Hartebeesthoek observatory (South Africa) in February 2014 by surveyors from Rural Development & Land Reform, University of KwaZulu-Natal, NASA and IGN. Hartebeesthoek observatory is one of the few sites in the world which currently hosts instruments from the four space geodesy techniques, namely DORIS, GNSS, SLR and VLBI. A first adjustment of the survey observations was carried out in 2014 and the tie vectors between instrument reference points were published.
As the precision of the VLBI axis offsets was requested by the International VLBI Service and a new version of the IGN adjustment software COMP3D was released, it was decided to reprocess the survey data of the main Hartebeesthoek observatory sub-site HartRAO. Indeed, the new software package allows processing in one step complex survey data, specifically in case of indirect determination of VLBI and SLR telescope reference points. The new processing strategy will be described and the tie vectors compared with 2014 results.
How to cite: Collilieux, X., Muller, J.-M., and Pesce, D.: Reprocessing of the Hartebeesthoek 2014 co-location survey, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2108, https://doi.org/10.5194/egusphere-egu21-2108, 2021.
To achieve a regional or continental-scale reference frame that is a densification of the International Terrestrial Reference Frame (ITRF), one can use a set of fiducial GPS / GNSS stations in the ITRF and regional frames. Predicting coordinates in the realization epoch using the fiducial stations’ trajectory parameters in the ITRF and applying a Helmert transformation aligns the regional solution’s polyhedron onto the ITRF. This paper shows inconsistencies in the regional realization of ITRF when the fiducial stations’ trajectory model ignores the periodic terms, resulting in a periodic coordinate bias in the regional frame. We describe a generalized procedure to minimize this inconsistency when realizing any regional frame aligned to ITRF or any other ‘primary’ frame. We show the method used to realize the Argentine Geodetic Positions (Posiciones Geodésicas Argentinas, POSGAR) reference frame and discuss its results. Inconsistencies in the vertical were reduced from 4 mm to less than 1 mm for multiple stations after applying our technique. We also propose adopting object-oriented programming terminology to describe the relationship between different reference frames, such as a regional and a global frame. This terminology assists in describing and understanding the hierarchy in geodetic reference frames.
How to cite: Gomez, D., Bevis, M., and Caccamise, D.: Realizing ITRF-Consistent Continental-Scale Geodetic Reference Frames, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13607, https://doi.org/10.5194/egusphere-egu21-13607, 2021.
Long GNSS position time series contain offsets typically at rates between 1 and 3 offsets per decade. We may classify the offsets whether their epoch is precisely known, from GNSS station log files or Earthquake databases, or unknown. Very often, GNSS position time series contain offsets for which the epoch is not known a priori and, therefore, an offset detection/removal operation needs to be done in order to produce continuous position time series needed for many applications in geodesy and geophysics. A further classification of the offsets corresponds to those having a physical origin related to the instantaneous displacement of the GNSS antenna phase center (from Earthquakes, antenna changes or even changes of the environment of the antenna) and those spurious originated from the offset detection method being used (manual/supervised or automatic/unsupervised). Offsets due to changes of the antenna and its environment must be avoided by the station operators as much as possible. Spurious offsets due to the detection method must be avoided by the time series analyst and are the focus of this work.
Even if manual offset detection by expert analysis is likely to perform better, automatic offset detection algorithms are extremely useful when using massive (thousands) GNSS time series sets. Change point detection and cluster analysis algorithms can be used for detecting offsets in a GNSS time series data and R offers a number of libraries related to performing these two. For example, the “Bayesian Analysis of Change Point Problems” or the “bcp” helps to detect change points in a time series data. Similarly, the “dtwclust” (Dynamic Time Warping algorithm) is used for the time series cluster analysis. Our objective is to assess various open-source R libraries for the automatic offset detection.
How to cite: Bhattacharjee, S. and Santamaría-Gómez, A.: Automatic offset detection using R open source libraries, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8678, https://doi.org/10.5194/egusphere-egu21-8678, 2021.
All satellites of the Galileo and GLONASS navigation systems are equipped with laser retroreflector arrays for Satellite Laser Ranging (SLR). SLR observations to Global Navigation Satellite Systems (GNSS) provide the co-location of two space geodetic techniques onboard navigation satellites.
SLR observations, which are typically used for the validation of the microwave-GNSS orbits, can now contribute to the determination of the combined SLR+GNSS orbits of the navigation satellites. SLR measurements are especially helpful for periods when the elevation of the Sun above the orbital plane (β angle) is the highest. The quality of Galileo-IOV orbits calculated using combined SLR+GNSS observations improves from 36 to 30 mm for β> 60° as compared to the microwave-only solution.
Co-location of two space techniques allows for the determination of the linkage between SLR and GNSS techniques in space. Based on the so-called space ties, it is possible to determine the 3D vector between the ground-based co-located SLR and GNSS stations and compare it with the local ties which are determined using the ground measurements. The agreement between local ties derived from co-location in space and ground measurements is at the level of 1 mm in terms of the long-term median values for the co-located station in Zimmerwald, Switzerland.
We also revise the approach for handling the SLR range biases which constitute one of the main error sources for the SLR measurements. The updated SLR range biases consider now the impact of not only of SLR-to-GNSS observations but also the SLR observations to LAGEOS and the microwave GNSS measurements. The updated SLR range biases improve the agreement between space ties and local ties from 34 mm to 23 mm for the co-located station in Wettzell, Germany.
Co-location of SLR and GNSS techniques onboard navigation satellites allows for the realization of the terrestrial reference frame in space, onboard Galileo and GLONASS satellites, independently from the ground measurements. It may also deliver independent information on the local tie values with full variance-covariance data for each day with common measurements or can contribute to the control of the ground measurements as long as both GNSS and SLR-to-GNSS observations are available.
How to cite: Bury, G., Sośnica, K., Zajdel, R., Strugarek, D., and Hugentobler, U.: Co-location of SLR and GNSS techniques onboard Galileo and GLONASS satellites, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7142, https://doi.org/10.5194/egusphere-egu21-7142, 2021.
The SLR observations to GNSS play a significant role as space tie, and allow investigations of many quantities related to the global Terrestrial Reference Frames (TRF), e.g., satellite orbits, scale, station coordinates, local ties. The differences between the observed ranges (via SLR observations) minus the computed spatial distances (via GNSS orbits based on GNSS observations) form the so-called “SLR residuals”. The analysis of these SLR residuals offers the opportunity to investigate the biases of the SLR measurements, the quality of the GNSS orbits and the quality and consistency of station coordinates. However, the absolute residuals contain a various number of inconsistencies and systematics which are not straightforward to be identified and separated, and, therefore to be further investigated. The present study focuses on the derivation of three alternative scenarios/cases through the usage of differential residuals between epochs, satellites and stations. These differential SLR residuals are derived from the processing of 25 years of SLR observations to GNSS (using GPS and GLONASS). The advantage of using the differential residuals is the elimination of one or more sources of systematic errors, according to each scenario. The comparison between the absolute and the differential residuals, respectively, is proven to stand as a useful diagnostic tool for the assessment of the systematic effects.
How to cite: Ampatzidis, D., Thaller, D., and Wang, L.: Analysis of differential residuals of SLR observations to GNSS: Methodology and results from analyzing 25 years of data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3177, https://doi.org/10.5194/egusphere-egu21-3177, 2021.
Until now, the GPS and GLONASS satellite antenna phase center offsets (PCOs) used within the International GNSS Service (IGS) have been estimated based on the International Terrestrial Reference Frame (ITRF) scale provided by Satellite Laser Ranging (SLR) and Very Long Baseline Interferometry (VLBI). Therefore, the IGS products have themselves been conventionally aligned to the ITRF scale, hence could not contribute to its realization. However, the disclosure of metadata, including PCOs, for the Galileo satellites by the European GNSS Agency recently opened a unique opportunity to realize an independent GNSS-based terrestrial scale.
Before its ongoing third reprocessing campaign (repro3), the IGS thus re-evaluated the PCOs of the GPS and GLONASS satellites by fixing the PCOs of the Galileo satellites in multi-GNSS solutions. The repro3 products, based on these re-evaluated PCOs, can provide an independent Galileo-based scale, which could potentially contribute to the scale of the next ITRF2020. However, the re-evaluated GPS and GLONASS PCOs are introduced as known constant values in repro3 without realistic uncertainties. Therefore, finally no realistic uncertainty will be available for the realized terrestrial scale.
In this study, another re-evaluation of the GPS and GLONASS PCOs based on the Galileo PCOs is carried out, accounting this time for their variability and estimation errors, with the goal to obtain a more rigorous Galileo-based scale with realistic uncertainty, in particular during the pre-Galileo era. For that purpose, daily time series of GPS and GLONASS PCO estimates derived from the repro3 solutions of different IGS Analysis Centers (ACs) are first analyzed. Deterministic and stochastic models of the time series are then introduced in a global adjustment of all GPS and GLONASS PCOs based on the Galileo PCOs. The re-evaluated PCOs – together with their uncertainties – are finally re-injected into the AC terrestrial frame solutions. The analysis of the latter allows a more rigorous evaluation of the Galileo-based scale and its uncertainty and a more sound comparison to the ones realized by SLR and VLBI. The outcome of this study will provide valuable information for the final selection and realization of the ITRF2020 scale.
How to cite: Glaser, S., Rebischung, P., Altamimi, Z., and Schuh, H.: Rigorous propagation of Galileo-based terrestrial scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-864, https://doi.org/10.5194/egusphere-egu21-864, 2021.
When using a network approach, expressing reliably GNSS position and velocities in a given reference frame (ITRF2014, IGS14, …) requires the identification of ‘stable’ and ‘rebliable’ reference stations. The choice of these reference stations can have a non-negligible impact on the estimated positions and velocities and of course on the derived geodynamic interpretations.
This study will present the work done to address this issue within EUREF and help the users of the EUREF products (more specifically of the EPN multi-year position and velocity solution) to identify the best reference stations in the EUREF Permanent Network (EPN). To that aim, in addition to a station classification, a web tool (https://epncb.oma.be/_productsservices/ReferenceFrame/) has been developed in order to discover the most suitable EPN reference stations. The primary goal of this tool is to help the user of EUREF reference frame product select suitable EPN reference stations to be added to his network during the preparation of own GNSS processing.
The tool helps the selection of optimal reference stations:
- by providing a restricted list of reference stations (based on the station classification and the begin and end date of the user processing)
- by giving access to additional information (number of position or velocity discontinuities, post-seismic deformation,…) and plots (detrended position time series, selection criteria values, velocity variability) for the stations.
The web tool as well as the station classification will be presented.
How to cite: Legrand, J. and Bruyninx, C.: Station Classification and Reference Station Selection, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14190, https://doi.org/10.5194/egusphere-egu21-14190, 2021.
We have developed a novel method in which a pair of GNSS antennas with similar characteristics are used to evaluate hidden systematic errors in existing GNSS calibrations with the help of high-end industrial metrology equipment. We tilt the calibrated antennas out of parallel and sort the observations in individual antenna reference frames rather than epoch time. With the combined and compared measurements, we can sort out the different elevation dependent uncertainties in the GNSS observations and quantify the errors of the calibration methods. We show the extent to which the calibration method error systematically maps as troposphere and height components in the GNSS processing and in the worst case found this to be > 1 cm in the vertical when using the ionosphere-free frequency combination L3. While showing results in the presentation for the full elevation range in 5° elevation cells, we report here the 1σ uncertainties of our method for 30° elevation at ±0.38 mm on L1 and ±0.62 mm on L3 with respect to the antenna phase centers. Once uncertainties have been characterized at this level, the etalon antennas can be deployed as space geodetic anchor points at core sites without compromising existing installations.
How to cite: Bergstrand, S., Jarlemark, P., and Herbertsson, M.: GNSS antenna calibration tables evaluated by means of large volume metrology, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16495, https://doi.org/10.5194/egusphere-egu21-16495, 2021.
Based on a large network of continuously operated GNSS tracking stations, the International GNSS Service (IGS) has a valuable contribution to the realization of the International Terrestrial Reference System. To provide the most accurate and consistent solution, the IGS refined the strategy and the set of associated models for the ongoing third reprocessing campaign. Beyond updated background models, a significant improvement is the combined reprocessing of three GNSS, namely GPS, GLONASS, and Galileo. Furthermore, signal-specific receiving antenna calibrations for Galileo and scale-free transmission phase center positions are applied. These modifications will allow exciting new investigations based on the delivered products.
In this contribution, we will present the final GFZ contribution to the IGS reprocessing efforts. We will present selected aspects of the station selection, parametrization, and processing scheme in the first part. Secondly, we will focus on the results by discussing the derived orbits, Earth rotation parameters, and station coordinates. Thirdly, the first results of our TIGA (IGS Tide Gauge Benchmark Monitoring Project) reprocessing will be presented, which are based on the previously discussed orbits and satellite clocks.
How to cite: Männel, B., Brandt, A., Bradke, M., Brack, A., Sakic, P., and Nischan, T.: GFZ contribution to the third IGS reprocessing campaign, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4148, https://doi.org/10.5194/egusphere-egu21-4148, 2021.
The next realization of the International Terrestrial Reference System, the ITRF2020, is planned to be released in 2021. Our joint VLBI Analysis Center VIE which runs between TU Wien and BEV is one of eleven IVS (International VLBI Service for Geodesy and Astrometry) analysis centres which provide VLBI input to the ITRF2020. The SINEX files submitted to the IVS Combination Center are produced with the Vienna VLBI and Satellite Software VieVS and contain unconstrained normal equation systems for station position, source coordinates and Earth orientation parameters. In this presentation, we document the included sessions and stations in our submission and introduce the Vienna terrestrial reference frame based on our contribution to the ITRF2020. In particular, we highlight special settings in the Vienna solution and assess the impact on the terrestrial reference frame.
How to cite: Krásná, H., Mayer, D., and Böhm, S.: Contribution of the Vienna Center for VLBI to ITRF2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1088, https://doi.org/10.5194/egusphere-egu21-1088, 2021.
The ITRF2020 will be the next official solution of the International Terrestrial Reference Frame and the successor of the currently used frame, i.e., ITRF2014. Based on an inter-technique combination of all four space geodetic techniques VLBI, GNSS, SLR and DORIS, contributions from different international institutions lead to the global ITRF2020 solution. In this context, the IVS Combination Centre operated by the Federal Agency for Cartography and Geodesy (BKG, Germany) in close cooperation with the Deutsches Geodätisches Forschungsinstitut (DGFI-TUM, Germany) generates the final contribution of the International VLBI Service for Geodesy and Astrometry (IVS). Thereby, an intra-technique combination utilizing the individual contributions of multiple Analysis Centres (AC) is applied.
For the contribution to the upcoming ITRF2020 solution, sessions containing 24h VLBI observations from 1979 until the end of 2020 are processed by 10 to 12 ACs and submitted to the IVS Combination Centre. The required SINEX format includes datum-free normal equations containing station coordinates and source positions as well as full sets of Earth Orientation Parameters (EOP). For ensuring a consistently combined solution, time series of EOPs, source positions and station coordinates as well as a VLBI-only Terrestrial Reference Frame (VTRF) and a Celestial Reference Frame (CRF) were generated and further investigated.
One possibility to assess the quality of the IVS contribution to the ITRF2020 solution is to carry out internal as well as external comparisons of the estimated EOP. Thereby, estimates of the individual ACs as well as external time series (e.g. IERS C04, Bulletin A, JPL-Comb2018) serve as a reference. The evaluation of the contributions by the ACs, the combination procedure and the results of the combined solution for station coordinates, source positions and EOPs will be presented.
How to cite: Hellmers, H., Bachmann, S., Thaller, D., Bloßfeld, M., and Seitz, M.: Combined IVS contribution to the ITRF2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10678, https://doi.org/10.5194/egusphere-egu21-10678, 2021.
In the context of the realization of the next International Terrestrial Reference Frame (ITRF2020), the International DORIS Service (IDS) is involved in the estimation of DORIS station positions/velocities as well as Earth orientation parameters from DORIS data. Thus, the 4 IDS Analysis Centers have re-analyzed all the DORIS observations from the fifteen DORIS satellites from January 1993 to December 2020.0.
The primary objective of this study is to analyze the DORIS contribution to ITRF2020 in terms of (1) geocenter and scale solutions; (2) station positions and week-to-week repeatability; (3) Earth orientation parameters; (4) a cumulative position and velocity solution.
Comparisons with the IDS contribution to ITRF2014 will address the benefits of the new antenna models, new models, including improved methods to handle non-conservative force model error on the Jason satellites, as well as the addition of data (compared to ITRF2014) from the latest DORIS missions (e.g. Jason-3, Sentinel-3A/B) in the IDS combination.
How to cite: Moreaux, G., Lemoine, F., Capdeville, H., Stepanek, P., Otten, M., Saunier, J., and Ferrage, P.: The IDS Contribution to the ITRF2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2315, https://doi.org/10.5194/egusphere-egu21-2315, 2021.
The International Laser Ranging Service (ILRS) contribution to ITRF2020 has been prepared after the re-analysis of the data from 1993 to 2020, based on an improved modeling of the data and a novel approach that ensures the results are free of systematic errors in the underlying data. This reanalysis incorporates an improved “target signature” model (CoM) that allows better separation of true systematic error of each tracking system from the errors in the model describing the target’s signature. The new approach was developed after the completion of ITRF2014, the ILRS Analysis Standing Committee (ASC) devoting almost entirely its efforts on this task. The robust estimation of persistent systematic errors at the millimeter level permitted the adoption of a consistent set of long-term mean corrections for data collected in past years, which are now applied a priori (information provided by the stations from their own engineering investigations are still taken into consideration). The reanalysis used these corrections, leading to improved results for the TRF attributes, reflected in the resulting new time series of the TRF origin and especially in the scale. Seven official ILRS Analysis Centers computed time series of weekly solutions, according to the guidelines defined by the ILRS ASC. These series were combined by the ILRS Combination Center to obtain the official ILRS product contribution to ITRF2020.
The presentation will provide an overview of the analysis procedures and models, and it will demonstrate the level of improvement with respect to the previous ILRS product series; the stability and consistency of the solution are discussed for the individual AC contributions and the combined SLR time series.
How to cite: Luceri, V., Pavlis, E. C., Basoni, A., Sarrocco, D., Kuzmicz-Cieslak, M., Evans, K., and Bianco, G.: The ILRS Contribution to ITRF2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14739, https://doi.org/10.5194/egusphere-egu21-14739, 2021.
The International GNSS Service (IGS) recently finalized its third reprocessing campaign (repro3). Ten Analysis Centers (ACs) reanalyzed the history of GPS, GLONASS and Galileo data collected by a global tracking network over the period 1994-2020. Combinations of the daily repro3 AC terrestrial frame solutions constitute the IGS contribution to the next release of the International Terrestrial Reference Frame, ITRF2020.
Compared to the previous IGS reprocessing campaign (repro2), a number of new models and strategies have been implemented in repro3, including the new IERS linear pole model, the new IERS-recommended sub-daily EOP tide model, and rotations of phase center corrections for tracking antennas not oriented North. Besides, a new set of satellite antenna phase center offsets was adopted in repro3, based on the published pre-flight calibrations of the Galileo satellite antennas. As a consequence, the IGS contribution to ITRF2020 provides for the first time an independent Galileo-based realization of the terrestrial scale, instead of being conventionally aligned in scale to the previous ITRF.
In this presentation, quality metrics from the daily repro3 terrestrial frame combinations are first introduced and compared to those from repro2. The impacts of the newly adopted models are then assessed and discussed. The terrestrial scale realized by the IGS repro3 solutions is in particular confronted to independent estimates from SLR and VLBI. The precision of the IGS repro3 station position time series is finally compared to that of the IGS repro2 series as well as of station position time series from independent groups.
How to cite: Rebischung, P.: Terrestrial frame solutions from the IGS third reprocessing, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2144, https://doi.org/10.5194/egusphere-egu21-2144, 2021.
The new ITRS realization, the ITRF2020, will be computed and released in 2021. Many institutions contributing to the international IAG services IGS, IVS, ILRS and IDS did work hard during the last months to finalize the ITRF2020 input data until mid of February 2021. The resulting data are series of SINEX files of daily or weekly global GNSS, VLBI, SLR and DORIS solutions. The ITRS Combination Centres (CC) are in charge of the computation of three ITRS realizations based on a combination of these input data. The three realizations can be seen as independent to some extent, as the combination strategies realized by the three CC partly differ considerably. This provides the opportunity of a cross-validation between the computed frames and ensures a high reliability of the final ITRF product. The ITRS CC will start in February 2021 with the analysis of the final input data series and their combination.
We will present first results of the analyses and computations performed at ITRS CC DGFI-TUM.
How to cite: Seitz, M., Bloßfeld, M., Glomsda, M., and Angermann, D.: First results of DTRF2020 computation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2329, https://doi.org/10.5194/egusphere-egu21-2329, 2021.
In preparation for ITRF2020, we developed a number of software tools and analysis strategies aiming at improving the quality, consistency and accuracy of the new frame. Our target is to enhance the modelling of the nonlinear station motions, including post-seismic deformation models for stations subject to major earthquakes, and periodic signals embedded in the station position time series. In addition to the classical annual and semi-annual signals, we foresee to simultaneously adjust some satellite draconitic harmonics and evaluate their impact on the estimated frame parameters. The ITRF2020 is expected to be provided in the form of an augmented reference frame so that in addition to station positions and velocities, parametric models for both PSD and periodic signals (expressed in the CM frame of satellite laser ranging) will also be delivered to the users. Depending on the availability of the input data of the four techniques at the time of this presentation, we expect to show and discuss some early results and give some indications regarding the specifications of the final ITRF2020 solution.
How to cite: Altamimi, Z., Rebischung, P., Metivier, L., Collilieux, X., Chanard, K., and Teyssendier-de-la-Serve, M.: Preparatory analysis and development for the ITRF2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2056, https://doi.org/10.5194/egusphere-egu21-2056, 2021.
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