The Global Geodetic Observing System (GGOS) is a collaborative contribution of the global Geodesy community to the observation and monitoring of the Earth System. Geodesy is the science of determining the shape of the Earth, its gravity field, and its rotation as functions of time. Essential to reach this goal are stable and consistent geodetic reference frames, which provide the fundamental layer for the determination of time-dependent coordinates of points or objects, and for describing the motion of the Earth in space. With modern instrumentation and analytical techniques, Geodesy is capable of detecting time variations ranging from large and secular scales to very small and transient deformations – all with increasing spatial and temporal resolution, high accuracy, and decreasing latency. The geodetic observational and analysis infrastructures as well as the high-quality geodetic products provide the foundation upon which advances in Earth and planetary system sciences and applications are built. In this way, GGOS endeavors to facilitate and enable production and sharing of the Earth observations needed to monitor, map, and understand changes in the Earth’s shape, rotation, and mass distribution. GGOS also advocates the global geodetic frame of reference as the fundamental backbone for measuring and consistently interpreting global change processes as well as the essential geospatial infrastructure to ensure a homogeneous and sustainable development worldwide.

GGOS closely works with its parent organization, the International Association of Geodesy (IAG), to keep these fundamental geodetic contributions sustainable. The IAG Services provide the infrastructure and products on which all contributions of GGOS are based, and the IAG Commissions and IAG Inter-Commission Committees provide expertise and support to address key scientific issues within GGOS. Additionally, GGOS supports the IAG by strengthening external and interdisciplinary relations and contributions to the broader geospatial information community, including relevant United Nations groups, in particular, the UN Committee of Experts on Global Geospatial Information Management (GGIM), its Subcommittee on Geodesy, and the new UN Global Geodetic Centre of Excellence (scheduled to commence operations in 2023). The main contribution of GGOS in this regard is to support actions and initiatives to communicate the value of Geodesy to society as well as to help to understand and solve complex issues facing the global geodesy community. Towards this objective, GGOS have developed a comprehensive Geodesy portal (https://ggos.org/) including detailed descriptions of geodetic observations (https://ggos.org/obs/) and products (https://ggos.org/products/), and various outreach tools such as short videos to explain the roles and importance of Geodesy to non-geodesists.

How to cite: Miyahara, B., Sánchez, L., Sehnal, M., and Craddock, A.: The Global Geodetic Observing System (GGOS) - infrastructure underpinning Science and Society -, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11302, https://doi.org/10.5194/egusphere-egu23-11302, 2023.

The use of digital object identifiers (DOI) for scientific data and scientific software is increasingly common practice for more than a decade. As a result of the Coalition on Publishing Data in the Earth and Space Sciences (COPDESS) and other initiatives, DOI-referenced datasets are fully citable in scholarly literature and more and more journals require the availability of data underlying scientific results and their citation. Technical implementations, like Scholix (a framework for Scholarly Link Exchange) enable direct links and between literature and data and support the visibility of research data. Key elements for enabling these links are persistent identifier (PID). These PIDs allow, e.g., to uniquely identify data, scholarly literature and code (via DOIs), persons (via ORCID), institutions and funding agencies (via ROR – the registry of research organizations), via machine-actionable links and should be included in the DOI metadata.

Similar to other scientific disciplines, the use of DOI for geodetic data is increasing in the last years. While this is easy for static data, like for global of regional gravitational models or GNSS campaign data, most geodetic data are large (mainly due to the large number of files and high temporal resolution) and highly dynamic (real time data acquisition) and highly granular. Geodetic services of the International Association for Geodesy (IAG) are international key player for geodetic data provision and distribution and their operating institutions and funding agencies increasingly require the provision of tangible data use and access statistics. Credit through citation was a major reason for the Global Geodetic Observing System (GGOS) to establish a Working Group on using DOI for geodetic data sets (GGOS DOI WG) and for the working group members.

The GGOS DOI WG was established in 2019 and includes international representatives of IAG Services and geodetic data centres and associated members that aims at developing best practices and recommendations for the consistent implementation of DOIs across all IAG Services and in the greater geodetic community. This presentation will give an update on recent group activities and on the status of DOI minting for geodetic datasets across IAG Services.

How to cite: Elger, K. and the GGOS DOI Working Group: The world of DOIs for geodetic data – metadata recommendations and status report of the GGOS DOI Working Group, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6384, https://doi.org/10.5194/egusphere-egu23-6384, 2023.

Water levels from hydrodynamic models typically lack an absolute vertical reference, and can thus not be linked directly to digital elevation models to assess coastal floodrisks. Instead, most workarounds rely on tide gauges that are connected to the land-based vertical reference to establish this link. The lack of an absolute vertical reference also makes it impossible to directly assimilate observed total water levels into models as this requires both observed and modeled water levels to refer to the same vertical datum.

The first consequence underlines the urgency of realizing an international height reference system that is easily accessible to users and which is adopted as the vertical reference in global tide gauge datasets and digital terrain models. Indeed, the lack of such an international height reference frame makes it impossible to accurately determine the impact and risks of sea level rise and changes in extreme water levels due to climate change. Let alone that an agenda for adaptation measures can be drawn up. The second consequence limits the accuracy of modeled water levels as existing workarounds do not exploit the observed long-term mean water level variations. At the same time, the assimilation of total water levels imposes strong requirements to the accuracy of an international height reference frame. Hydrodynamic models are extremely sensitive to slopes in observed water levels. Even small erroneous slopes between tide gauges introduced by errors in the vertical referencing, impose false currents that in turn result in model instabilities.

In turn, hydrodynamic models offer great and unique opportunities to assist in the realization of an international height reference system. The difference between the observation-derived mean water level (MWL) at location B and the sum of the observation-derived MWL at location A and the model-derived mean water level difference between the two locations is a proxy for the datum shift between the height datums used at locations A and B. The asset and uniqueness of the technique referred to as ‘model-based hydrodynamic leveling’ lies in the fact that it allows to transfer a height datum over large water bodies without the need to acquire new measurements. In the Dutch Versatile Hydrodynamics project, we implemented the technique and combined the data with geopotential differences from spirit leveling/gravimetry to compute a new realization of the European Vertical Reference System (EVRS).

This presentation will i) explain and demonstrate the need for an international height reference system from the perspective of hydrodynamic modelers; ii) demonstrate the potential contribution of hydrodynamic models to the realization of such a height system using the results obtained in the Versatile Hydrodynamics project, and iii) outlines ideas for future work.

How to cite: Slobbe, C., Verlaan, M., Klees, R., and Afrasteh, Y.: Hydrodynamic modeling and the realization of an international height reference system - urgent need and potential contribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1539, https://doi.org/10.5194/egusphere-egu23-1539, 2023.

High-resolution regional applications require regional reference frames with dense networks of reference stations. These regional reference frames can be realised in the form of multi-year reference frames (that can be fixed to a specific tectonic plate like EUREF for Europe) or as epoch reference frames to represent non-linear phenomena such as earthquakes or loading effects (like SIRGAS for Latin America). Common to these realisations is that they are based on GNSS networks with a geodetic datum that is realised by alignment to the global reference frame (ITRF or IGS TRF).

In consequence, the origin of these networks reflects the Earth’s centre of figure rather than the Earth’s instantaneous centre of mass. Moreover, the quality of the realised datum decreases over time, as the linearly-parameterised coordinates of the global reference frame have to be extrapolated beyond the observation period. These effects mean a significantly reduced value of station-specific displacement time series for the study of, e.g., local geophysical effects.

This study presents an alternative approach for the realisation of a regional epoch reference frame for Latin America. The approach is based on the common weekly solution of global SLR, VLBI and GNSS networks combined at the normal equation level. Thereby, SLR determines the origin, SLR and VLBI jointly determine the scale, and a homogeneously distributed global GNSS network is used to realise the orientation. This GNSS network is densified by the stations of the regional sub-network, namely the stations of the Latin American SIRGAS network. The approach does not necessarily rely on fiducial points in the region of interest, which means that it is conceptually transferrable to other regional networks.

In order to cope with system-specific deficiencies of SLR and VLBI, namely data gaps, low station performances and frequently changing observational networks deteriorating the realised datum parameters, we propose a strategy to stabilise the realised datum via filtering the input data of these techniques at the normal equation level before combination with GNSS.

We evaluate the realised datum of the epoch-wise weekly solutions by comparison against the ITRF2014 as an independent multi-year realisation of the ITRS and against the JTRF2014 as an independent sub-secular realisation of the ITRS. Moreover, station-specific displacement time series are validated against non-tidal loading displacement time series derived from geophysical fluid models provided by ESMGFZ in order to demonstrate that the displacement time series reflect seasonal geophysical processes in a geocentric frame.

How to cite: Kehm, A., Sánchez, L., Bloßfeld, M., Seitz, M., Drewes, H., Angermann, D., and Seitz, F.: Combination strategy for regional geocentric epoch reference frames, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13216, https://doi.org/10.5194/egusphere-egu23-13216, 2023.

From the investigation of GRACE and GRACE-FO instrument data, we are aware of quite a number of unmodeled effects and deficiencies in the calibration of instruments. We want to use these deficiencies as an example to discuss how for a core GGOS observation technique, such as GRACE / GRACE-FO, all opportunities to assess and improve sensor calibration and to identify and characterize unmodeled effects affecting the measurements should be explored. This may seem obvious, but we will show that a major effort on this field would be very desirable. We deliberately choose the GGOS session for a broader discussion of the topic, and we want to highlight the importance of an overarching approach that combines insight from different satellite missions and space techniques.

How to cite: Flury, J., Koch, I., and Duwe, M.: Well calibrated space sensor systems for GGOS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8078, https://doi.org/10.5194/egusphere-egu23-8078, 2023.

On 1 July 2023, the International DORIS Service (IDS) will celebrate the 20th anniversary of its creation under the umbrella of the International Association of Geodesy (IAG). The IDS was established to foster scientific research related to the French DORIS tracking system and to deliver scientific products, mostly related to the International Earth rotation and Reference systems Service (IERS). Since its start, the organization has continuously evolved, leading to additional and improved operational products. IDS is now based on a reinforced structure with two Data Centers, six Analysis Centers, four Associated Analysis Center, a Combination Center, and several partner groups.

The DORIS system recorded its first measurement on February 3rd, 1990, from the SPOT-2 remote sensing satellite. 32 years after, the system is at its best. DORIS has proven greatly valuable for geodesy and geophysics applications: measuring tectonic plate motions, determination of the rotation and the gravity parameters of the Earth, contributing to the international reference system, ... Technological and methodological improvements have allowed the improvement in the estimates of the positions of the DORIS tracking ground stations, the Earth rotation parameters and other geodetic variables such as the geocenter and the scale of the ITRF. This year, a 9th satellite joins the current constellation of DORIS satellites. It is SWOT, launched on 16 December 2022. Never before have so many DORIS instruments been in operation simultaneously.

This presentation addresses the recent achievements made by IDS and its components, and the future plans of the service.

How to cite: Soudarin, L., Lemoine, F., and Sellé, A.: The International DORIS Service: almost 20 years old., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15885, https://doi.org/10.5194/egusphere-egu23-15885, 2023.

As the unique approach to obtain centimeter-level seafloor positioning information, Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) (Spiess, 1985) has drawn increasing attention and plays an important role in ocean engineering and marine geoscience research (Gagnon et al. 2005; Tadokoro et al. 2006; Watanabe et al.2014; Yokota et al. 2016; Yang et al. 2018).

GNSS-A positioning accuracy is significantly restricted by temporal and spatial variation errors related to propagation velocity of acoustic signals, the bridge medium to connect sea-surface platform and seafloor stations. Valuable investigations focusing on sound speed structure (SSS) modelling and inversion have been released and contribute to the GNSS-A performance improvements (Fujita et al. 2006; Ikuta et al. 2008; Honsho et al. 2017; Yokota et al. 2019; Watanabe et al. 2020; Yang et al. 2020; Yokota et al, 2022; Xue et al. 2023, in prep). It’s promising to progressively suppress SSS errors effect on seafloor positioning capability based on the increasingly refined SSS model policy.

Besides concentration on SSS errors modeling and corrections, additional consideration of positional uncertainty of sea-surface platform, one of vital parts of entire GNSS-A observation system, is reasonable for refined seafloor positioning policy. Currently, joint/total adjustment model and parameter estimation of the transducer and seafloor transponder for underwater precise point positioning have been published (Zhao et al. 2021). Furthermore, for seafloor geodetic network scene, numerical tests considering the positional uncertainty of sea-surface transducer were conducted. Further research may be hopeful to evaluate and control error propagation effect on seafloor positioning from sea-surface segment and helpful for usage of more flexible platform.

How to cite: Zhao, S. and Yokota, Y.: Consideration of positional uncertainty of sea-surface platform for GNSS-A seafloor positioning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12103, https://doi.org/10.5194/egusphere-egu23-12103, 2023.

The accurate determination of Earth Orientation Parameters (EOP) requires post-processing of observational data collected from various space geodetic techniques, which causes delays in providing EOP solutions. However, receiving instantaneous information about EOP in real time is crucial in precise positioning and navigation. Therefore, EOP prediction (particularly short-term) has become a subject of increased attention within the international geodetic community.

In the light of the developments of advanced geodetic data processing, modelling effective angular momentum functions, and developing new prediction methods, a re-assessment of the various EOP predictions was pursued in the frame of the Second Earth Orientation Parameters Prediction Comparison Campaign (2^nd EOP PCC). The campaign was run by Centrum Badań Kosmicznych Polskiej Akademii Nauk (CBK PAN), in cooperation with GeoForschungsZentrum (GFZ) and under the auspices of the International Earth Rotation and Reference Systems Service (IERS). The campaign started on 1st September 2021 and finished on 28^th December 2022, giving 7327 submitted predictions within 82 weeks. The campaign was a great success of the geodetic community thanks to international cooperation.

The presentation provides the summary of the 2^nd EOP PCC. We focus on the recap of the statistics on the involved participants, i.e., the number of prediction methods and input data. Then we will present the accuracy of EOP predictions based on the mean absolute error computed for IERS 14 C04 solution as a reference. Additionally, we present the quality of predictions in clusters created from the campaign participants (IDs) based on their modern prediction methods combined with input data (EOP observations and data on the Earth’s surficial fluids) We conclude the presentations with plans for the prediction assessment, also in terms of the possible continuation of the campaign involving new release of IERS C04 20.

How to cite: Śliwińska, J., Kur, T., Nastula, J., Wińska, M., Dobslaw, H., and Partyka, A. and the 2nd EOP PCC Participants: Achievements of the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14052, https://doi.org/10.5194/egusphere-egu23-14052, 2023.

Time-variations in the orientation of the solid Earth are largely governed by the exchange of angular momentum with the surface geophysical fluids of atmosphere, oceans, and the land surface. Modelled fields of atmospheric winds, atmospheric surface pressure, ocean currents, ocean bottom pressure, and terrestrial water storage allow to calculate effective angular momentum (EAM) functions that provide highly reliable information about the orientation changes of the Earth. EAM forecasts derived from model forecast runs support substantially short-term Earth Orientation Parameters (EOP) Predictions. So far, routinely available EAM forecasts do not include any error information needed for rigorous combination of EAM forecasts with EOP predictions from various geodetic techniques. Based on hindcast experiments, we analysed the EAM forecast error and trained a neural network to predict EAM forecast errors. As expected, EAM forecast errors increase with the prediction horizon but we found also irregular large variation in the EAM forecast error that seem to be well predictable with machine learning methods. 

How to cite: Dill, R. and Dobslaw, H.: Predicting Effective Angular Momentum Function Forecast Errors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3090, https://doi.org/10.5194/egusphere-egu23-3090, 2023.

Variations in Earth orientation parameters (EOP) are related to mass redistribution, gravitational, and geodynamic processes in the Earth system and have gained a great deal of attention in Earth science, astronomy, and climate change studies. In addition, real-time EOP information is needed for many space geodetic applications, including satellite navigation from the ground and low-Earth orbit, like tracking interplanetary spacecraft and forecasting the weather. Currently, the EOP can be estimated at the best possible accuracy with modern high-precision space geodetic techniques like Very Long Baseline Interferometry (VLBI), Global Navigation Satellite Systems (GNSS), and Satellite Laser Ranging (SLR). However, the complex nature of data processing and the time it takes to process it always lead to delays. Consequently, predicting EOP is of great scientific and practical importance. Accordingly, several methods have been developed and applied to EOP prediction. In spite of this, the accuracy of EOP still needs to meet our expectations, even for forecasts of a few days into the future. We will therefore have to face two major challenges in order to provide the best prediction data: which input data to use and which prediction methods are superior to others. In order to answer these two questions, new methods or a combination of existing approaches are investigated to improve the accuracy of the predicted EOP time seires. Such in-depth investigations are currently conducted within the “Second EOP Prediction Comparison Campaign (EOP-PCC)” organized by IAG and IERS. In this study, we investigate a redesigned prediction package (input data and method) to improve the possibility of bridging the existing gap between the observation and the final estimated product.

We will briefly present our contribution to EOP-PCC and illustrate the result of EOP data obtained from single space geodetic techniques provided by the department of geodesy at BKG. Then, we run our prediction algorithm with the official IERS EOP series and our BKG’s single-technique analysis products for VLBI and SLR using the combination of a deterministic and a stochastic method and compare it with different prediction techniques. Finally, we will show the potential of using a combination of VLBI and GNSS techniques to obtain real-time EOP estimates.

How to cite: Modiri, S., Thaller, D., Klemm, L., König, D., Hellmers, H., Bachmann, S., Flohrer, C., and Walenta, A.: EOP Prediction with special focus on using EOP products by different space geodetic techniques as input, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14827, https://doi.org/10.5194/egusphere-egu23-14827, 2023.

Polar Motion is the movement of the Earth's rotational axis relative to its crust, reflecting the influence of the material exchange and mess redistribution of each layer of the Earth on the Earth's rotation axis.
The real-time estimation of Polar Motion (PM) is needed for the navigation of Earth satellites and interplanetary spacecraft. However, it is impossible to have real-time information due to the complexity of the measurement model and data processing.

Various prediction methods have been developed. However, the accuracy of PM prediction is still not satisfactory even for a few days in the future. Therefore, a new technique or a combination of the existing methods needs to be investigated for improving the accuracy of the prediction PM.
In this study, we combine the 1D  Convolutional Neural Network with the Singular Spectrum Analysis (SSA).
 The computational strategy follows multiple steps, first, we model the predominant trend of the PM time series using SSA. Then, the difference between the PM time series and its SSA estimation is modeled using the 1D Convolution Neural Network. However, we developed a Multivariate Multi step 1D-CNN Model with a Multi-output strategy to predict at the same time both components (Xp, Yp)  of the PM.  . We introduce to the  Model: the Ocean Angular Momentum, Atmospheric Angular Momentum, and Hydrological Angular Momentum (OAM+AAM+HAM) to improve the results. Multiple sets of PM predictions which range between 1 and 10 days have been performed based on an IERS 14 C04 time series to assess the capability of our hybrid Model. Our results illustrate that the proposed method can efficiently predict both (Xp, Yp) of PM.

How to cite: Guessoum, S., Belda, S., Ferrándiz, J. M., Modiri, S., Heinkelmann, R., Schuh, H., and Dhar, S.: The short-term prediction of Polar Motion using the combination of SSA and the Multivariate Multi-step 1D- Convolutional Neural Networks with Multioutput strategy., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6737, https://doi.org/10.5194/egusphere-egu23-6737, 2023.

Earth orientation parameters (EOPs) are currently determined from measurements taken by the space-geodetic techniques of SLR, VLBI, GNSS, and DORIS. But each technique has its own unique strengths and weaknesses in this regard. Not only is each technique sensitive to a different subset and/or linear combination of the EOPs, but the averaging time for their determination is different, as is the interval between observations, the precision with which they can be determined, and the duration of the resulting EOP series. By combining the individual series determined by each technique, a series of the Earth's orientation can be obtained that is based upon independent measurements and that spans the greatest possible time interval. Such a combined Earth orientation series is useful for a number of purposes, including a variety of scientific studies and as an a priori series for use in data reduction procedures. However, care must be taken in generating such a combined series in order to account for differences in the underlying reference frames within which each individual series is determined (which can lead to differences in the bias and rate of the Earth orientation series). Traditionally, differences in the underlying reference frames are accounted for by applying a correction to the bias and rate of each individual series being combined with the goal of placing the series within a common reference frame. But there is an uncertainty associated with estimating the bias and rate correction that needs to be applied to each series. In fact, this uncertainty is a major (if not the major) source of error in combined EOP series. However, this source of error can be mitigated by jointly combining the EOP series with the terrestrial reference frame. Recent ITRF and JTRF solutions such as ITRF2020 and JTRF2020 have included EOP series in their determination. In this presentation, the ITRF2020 and JTRF2020 combined polar motion series will be compared to the more traditionally determined IERS Bulletin A and JPL KEOF (Kalman Earth Orientation Filter) combined polar motion series in order to study the improvement attained by jointly determining the combined EOP series with the terrestrial reference frame.

How to cite: Gross, R., Abbondanza, C., Chin, M., Heflin, M., and Parker, J.: Improving Combined EOP Series by Jointly Determining Them with the Terrestrial Reference Frame, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3469, https://doi.org/10.5194/egusphere-egu23-3469, 2023.

Determination of Earth Orientation Parameters (EOP) with utmost accuracy requires the combination of various data sources from different space geodetic techniques, some of which requiring long processing time. This results in a latency of up to several weeks by which the so-called final EOP are released. Since some of the important applications, including satellite navigation and orientation of deep space telescopes, require instantaneous EOP information, the so-called rapid determination and also prediction of EOP are needed. International Earth Rotation and Reference Systems Service (IERS) provides rapid EOP by using the most recent Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) 24-hour and intensive sessions data. However, there are some discrepancies between these rapid data and the final, most accurate EOP. In order to reduce these discrepancies and achieve more accurate rapid EOP, we focus on applying machine learning algorithms for polar motion components (xp, yp) and dUT1=UT1-UTC. We focus on a window of 63 days with 31 day predictions to the past and 31 day predictions to the future.

We devise a new algorithm called ResLearner, which is a machine learning method based on multilayer perceptrons trying to learn the differences between rapid and final EOP data. We use informative features such as Effective Angular Momentum (EAM) data (both the observations provided by GFZ and the 14-day forecasts provided by ETH Zurich), tides, Liouville equation for (xp, yp), and a linear relation between dUT1 and the axial components of EAM.
We use ResLearner in the context of Deep Ensembles in order to derive the uncertainty in the estimations. We also address the so-called unmixing and self-calibration problems. The former enables us to unravel the causes behind the discrepancies between rapid and final EOP as provided by IERS, while the latter could help us reduce these erroneous effects. 

We train the algorithms on both the IERS and Jet Propulsion Laboratory (JPL) final EOP data. Our ResLearner method can consistently reduce the discrepancies between rapid and final EOP across all days. The improvement in accuracy is up to 55%. We observe some unexpected behaviour related to day 0 of prediction, in which the accuracy of the IERS is significantly better than the immediately preceding or following values. Our unmixing algorithm shows that this behaviour is probably related to erroneous, non-linear effects of EAM at day 0, and also semi-diurnal, diurnal, long-period retrograde and prograde, and zonal tides. Using our self-calibration algorithm for EAM, we can slightly improve the prediction performance by up to 14%.

Finally, we provide the improved rapid EOP data publicly, operationally, and on a daily basis, on the ETH Zurich prediction center website at https://gpc.ethz.ch/EOP/Rapid/

How to cite: Kiani Shahvandi, M., Dill, R., Dobslaw, H., Mishra, S., and Soja, B.: Improving the accuracy of rapid Earth Orientation Parameters with the "ResLearner" machine learning method, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4162, https://doi.org/10.5194/egusphere-egu23-4162, 2023.

The derivation and subsequent use of suitable corrections to the current IAU2006/IAU2000 precession/nutation models is a main objective of the IAU/IAG Joint Working Group on Improving theories and models of the Earth rotation (JWG ITMER). It has been recognized in the latter IERS/GGOS Unified Analysis Workshops as the fastest way of improving the accuracy of those models at the short-term and thus contributing to the development of the last Resolutions of the IAG and IAU on Earth rotation.

In the last few years, some research groups have proposed different sets of corrections or updates to precession and either the forced or free nutations – including alternative approaches to free core nutation (FCN) models. The derivations of the various sets are related to VLBI solutions or observational data to quite different extents. The purpose of this study is providing a wider view into the performance of such corrections, focusing on features and capabilities more directly related to VLBI data analysis

How to cite: Ferrándiz, J. M., Karbon, M., Belda, S., and Escapa, A.: On the performance of the corrections to the current precession-nutation models in VLBI data analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8821, https://doi.org/10.5194/egusphere-egu23-8821, 2023.