ALBERT

Description: Over the last 15 years, the Gravity Recovery and Climate Experiment (GRACE) mission has provided measurements of temporal changes in mass redistribution at and within the Earth that affect polar motion. The newest generation of GRACE temporal models, are evaluated by conversion into the equatorial components of hydrological polar motion excitation and compared with the residuals of observed polar motion excitation derived from geodetic measurements of the pole coordinates. We analyze temporal variations of hydrological excitation series and decompose them into linear trends and seasonal and non-seasonal changes, with a particular focus on the spectral bands with periods of 1000–3000, 450–1000, 100–450, and 60–100 days. Hydrological and reduced geodetic excitation series are also analyzed in four separated time periods which are characterized by different accuracy of GRACE measurements. The level of agreement between hydrological and reduced geodetic excitation depends on the frequency band considered and is highest for interannual changes with periods of 1000–3000 days. We find that the CSR RL06, ITSG 2018 and CNES RL04 GRACE solutions provide the best agreement with reduced geodetic excitation for most of the oscillations investigated.

Description: Advanced geodetic and astronomical tasks, such as precise positioning and navigation require forecasted Earth Orientation Parameters (EOP). The Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) aims to compare various EOP forecast methods implemented by different institutes from all over the world. Here we focus on universal time (UT1-UTC) and Length-of-Day (LOD) predictions received in the period between September 1st, 2021 and May 29th, 2022. The forecasts are preliminarily evaluated against the EOP 14 C04 solution delivered by the International Earth Rotation and Reference System Service (IERS) by using the mean absolute error (MAE) as the prediction quality measure. Exemplarily, we compare forecasts from IERS delivered by U.S. Naval Observatory (USNO) and a selected campaign participant to assess the impact of both input data and computation methodology on predictions. We show that improper treatment of long-periodic ocean tides has severely degraded LOD forecasting until this issue has been brought to the attention of the participant during a meeting of the 2nd EOP PCC. We consider this as a good example for the benefit of the campaign to the overall scientific community by providing specific feedback to individual processing centres on deficits in their products, which lead to quick and effective adaptations. The lessons learned from this analysis could be applied to other EOP forecasting methods based on Effective Angular Momentum (EAM) predictions.

Description: Precise positioning and navigation on the Earth’s surface and in space require accurate earth orientation parameters (EOP) data and predictions. In the last few decades, EOP prediction has become a subject of increased attention within the international geodetic community, e.g., space agencies, satellite operators, researchers studying Earth rotation dynamics, and users of navigation systems. Due to this fact, many research centres from around the world have developed dedicated methods for the forecasting of EOP. An assessment of the various EOP prediction capabilities is currently being pursued in the frame of the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC), which began in September 2021 and will be continued until the end of the year 2022. The new campaign was prepared by the EOP PCC Office run by Centrum Badań Kosmicznych Polskiej Akademii Nauk (CBK PAN) in Warsaw, Poland, in cooperation with GeoForschungsZentrum (GFZ) and under the auspices of the International Earth Rotation and Reference Systems Service (IERS). In this paper, we provide an overview of the 2nd EOP PCC five months after its start. We discuss the technical aspects and present statistics about the participants and valid prediction files received so far. Additionally, we present the results of preliminary comparisons of different reference solutions with respect to the official IERS 14 C04 EOP series. Root mean square values for different solutions for polar motion, length of day, and precession-nutation components show discrepancies at the level from 0.04 to 0.36 mas, from 0.01 to 0.10 ms, and from 0.01 to 0.18 mas, respectively.

Description: The variations in the Terrestrial Water Storage (TWS) through seasonal soil moisture changes, ice and snow loading and melting influence the Earth’s inertia tensor. Quantitative assessment of the hydrological effects in polar motion persists unclear because of the lack of global observations as well as differences between various atmospheric and oceanic models. Here, we compare the results of several geodetic hydrological excitation functions, that are calculated by removing modeled atmospheric and oceanic effects from precise observations of full polar motion excitations. Geodetic hydrological excitations (GAO), called geodetic residuals as well, are analyzed and compared with hydrological excitation function determined from hydrological models and Gravity Recovery and Climate Experiment (GRACE) satellite mission. The obtained geodetic residuals computed for different models of AAM (Atmospheric Angular Momentum) and OAM (Oceanic Angular Momentum) are different from one model to another. The discrepancies between observed polar motion variations and geophysical contributions appear more likely to be caused by the errors of the atmospheric, in particular of the motion term, and oceanic models. In this study, we analyze the polar motion budget at decadal, seasonal, and short term oscillations for a most often used models of atmosphere and oceans considered the global mass balance inside AAM, OAM and HAM excitation functions. Here, we would like to present the consistency between full polar motion excitations and geophysical excitations, that are the sum of AAM (pressure + wind) and OAM (bottom pressure + currents) contributions. This analysis could let us indicate, which components of different AAM and OAM models cause the biggest errors in the geodetic budget.

Description: Real-time information on Earth Orientation Parameters (EOP) is needed for many advanced geodetic and astronomical tasks including positioning and navigation on Earth and in space. Therefore, EOP short-term prediction has become a subject of increased attention within the international geodetic community.Scientific progress in the prediction methods but also in the geodetic data processing, and modelling effective angular momentum functions raise the need to re-evaluate various EOP prediction approaches. This was the objective of the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC). The campaign lasted from September 1, 2021 to December 28, 2022. During this period, more than 7000 predictions were submitted by registered participants. Thanks to international cooperation, the campaign was a great success of the geodetic community.In this study, we provide a summary of the 2nd EOP PCC, focusing on the quality of EOP predictions. We present time evolution of the prediction accuracy obtained on the basis of the mean absolute error for the IERS 14 C04 solution as a reference. We also analyse the impact of filtering outlier predictions on the overall accuracy of the EOP forecasts. We end the presentation with initial conclusions on the most encouraging prediction methodologies together with plans for the possible continuation of the campaign involving new release of IERS 20 C04.

Description: Gravimetric excitation of polar motion (PM) can be determined from the models of Earth’s gravity field variations based on observations of Gravity Recovery and Climate Experiment (GRACE) andits successor GRACE Follow-On (GRACE-FO). Such excitation reflects mainly the impact of continental hydrosphere and cryosphere on PM variation and is usually described with series of hydrological plus cryospheric angular momentum (HAM+CAM).Previous research on the use of GRACE/GRACE-FO data for HAM+CAM analysis focused on exploiting for this purpose more popular monthly solutions. In this study, in contrast to former analyses, we use daily and 10-day data provided by the Institute of Geodesy at Graz University of Technology (ITSG) and Centre National d’Études Spatiales (CNES) to study PM excitation at sub-monthly time scales. We analyse several oscillations in HAM+CAM series obtained from GRACE/GRACE-FO and compare them with geodetic excitation reduced bythe influence of the atmosphere and oceans (so-called geodetic residuals, GAO) and with HAM determined from hydrological models. This analysis aims to check whether the daily and 10-day solutions carry any additional information about PM that is not provided by monthly data.We show that sub-monthly GRACE/GRACE-FO data can be useful especially for the analysis of HAM+CAM changes with periods above 20 days. Despite underestimating GAO variability, HAM+CAM series are quite well correlated with GAO, especially in terms of 10-day data.

Description: Despite being important contributor to polar motion (PM) variation especially at seasonal time scales, hydrological angular momentum (HAM) is a main source of uncertainties in the estimation of PM excitation.With the growing scientific interest in climate change in recent years, works have intensified on the development of new climate models that simulate changes in the properties of the atmosphere, oceans and hydrosphere. One of the effects of these activities is latest implementation of the CMIP (Coupled Model Intercomparison Project) – CMIP6.In this study, we use various CMIP6 historical simulations to determine HAM series. We focus on the analysis of HAM calculated from clustered models determined on the basis of the mean of several models or on their combination with use of refined statistical algorithms. The obtained HAM series are analysed in different spectral bands and evaluated taking the hydrological signal in geodetically observed PM excitation as a reference. The results are also compared with those received for data from Gravity Recovery and Climate Experiment (GRACE) mission. Our research shows that despite the large differences between the HAM series obtained from single CMIP6 simulations, it is possible to choose the groups or combinations of models that allow for quite reliable determination of HAM, especially in seasonal spectral band. In terms of phase, the chosen models perform better than GRACE for annual prograde and semiannual retrograde term. In terms of amplitudes, the chosen models perform better than GRACE for annual prograde and annual retrograde term.

Description: This dataset contains predictions of Earth orientation parameters (EOP) submitted during the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC). The 2nd EOP PCC has been carried out by Centrum Badań Kosmicznych Polskiej Akademii Nauk CBK PAN in Warsaw in cooperation with the GFZ German Research Centre for Geosciences in Potsdam (Germany) and under the auspices of the International Earth Rotation and Reference Systems Service (IERS) within the IERS Working Group on the 2nd EOP PCC. The purpose of the campaign was to re-assess the current capabilities of EOP forecasting and to find most reliable prediction approaches. The operational part of the campaign lasted between September 1, 2021 and December 28, 2022. Throughout the duration of the 2nd EOP PCC, registered campaign participants submitted forecasts for all EOP parameters, including dX, dY, dPsi, dEps (components of celestial pole offsets), polar motion, differences between universal time and coordinated universal time, and its time-derivative length-of-day change. These submissions were made to the EOP PCC Office every Wednesday before the 20:00 UTC deadline. The predictions were then evaluated once the geodetic final EOP observations from the forecasted period became available. Each participant could register more than one method, and each registered method was assigned an individual ID, which was used, e.g., for file naming. The dataset contains text files with predicted parameters as submitted by campaign participants and MATLAB file which is a database with all correct predictions from each participant loaded into a structure.