This session invites presentations about methods, algorithms and results from GRACE/GRACE-FO data analysis and error assessments providing insights into spatio-temporal signal content including diverse methods of error reduction. We also invite discussions on inter-comparisons between various GRACE/GRACE-FO gravity field time-series and assessments of the significance of the differences and analysis of possible causes.
Moritz Huckfeldt, Florian Wöske, and Benny Rievers
The Center for Applied Space Technology and Microgravity (ZARM) has recently developed monthly gravity field solutions from GRACE Follow-On data, which we present here including generation specifications and comparisons to solutions from other well known institutions.
Because the GRACE-D accelerometer data deteriorated shortly after launch, we developed a procedure to reproduce the accelerometer signal as precisely as possible using high-precision environment modelling. The modelling approach is extended by a physically-motivated and minimalistic transplant to considerably improve the precision of the acceleration data. In this context transplant means that properties from one GRACE satellite can be used for the other GRACE satellite due to the close proximity of both satellites. The transplant property is a thermospheric density value, which is estimated at positions of GRACE-C and applied by a time-offset to the GRACE-D satellite. This is necessary due to the insufficient accuracy of thermospheric density models and improves the artificial data in along-track direction. This is crucial because this is also the the main measuring direction of the inter-satellite microwave ranging instrument.
The data generation procedure includes accelerometer calibration parameter obtained from tailored precise orbit determination (POD) to reduce the influence of simulation errors and GRACE-C characteristics on the GRACE-D data.
This procedure provides artificial accelerometer data, which enables us to generate monthly gravity field solutions of high accuracy. We show how our solutions compare to solutions using GRACE-D transplant data from TU Graz or JPL, for different periods of the mission duration and present the limitations and potential improvement capabilities.
The GRACE-D accelerometer and other auxiliary data from our process is published as additional material to the monthly gravity field solutions on a publicly accessible data server. We encourage the community to use this data for comparisons and further research.
How to cite:
Huckfeldt, M., Wöske, F., and Rievers, B.: ZARM monthly GRACE-FO gravity field solutions utilizing GRACE-D data from high-precision environment modelling, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-82, https://doi.org/10.5194/gstm2024-82, 2024.
Martin Lasser, Ulrich Meyer, Daniel Arnold, and Adrian Jäggi
At the Astronomical Institute of the University of Bern, we study gravity field determination from GRACE Follow-On satellite-to-satellite tracking using the inter-satellite link (KBR and LRI) and kinematic positions of the satellites as observations. The kinematic positions are obtained from a precise point positioning, where the carrier phase ambiguities are fixed to integer values. We use a simplified stochastic model based on epoch-wise covariance information, which may be efficiently derived in the kinematic point positioning process, and extend this model by an empirical noise model derived from the residuals of a reduced-dynamic orbit fit of the kinematic positions to correctly characterise their stochastic behaviour. In addition, we use empirical covariances of range-rate residuals to characterise the inter-satellite link noise. We investigate the interplay between the empirical noise model and the stochastic parameters of our Celestial Mechanics Approach (CMA) for gravity field determination. We validate the performance of our gravity field determination by analysing the residuals of combined orbits calculated using both kinematic positions and K-band data, and by analysing the quality of co- estimated gravity field solutions. Furthermore, we provide an update about on-going investigation regarding GRACE Follow-On at the AIUB.
How to cite:
Lasser, M., Meyer, U., Arnold, D., and Jäggi, A.: Time-variable gravity field determination from GRACE Follow-On data at the AIUB, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-85, https://doi.org/10.5194/gstm2024-85, 2024.
Jean-Michel Lemoine, Stéphane Bourgogne, Sean Bruinsma, Thomas Vaujour, Julia Pfeffer, and Chloé Thenoz
Since December 2019, CNES is producing its fifth release of GRACE and GRACE-FO time-variable gravity solutions. This presentation will provide an update on the evolution of processing since last year and on the prospect of a new reprocessing in 2025, based on the new FES2022 barotropic tide model that recently became available and on the update of the TUGO ocean dealiasing model by the LEGOS/CLS team.
Furthermore, in order to characterize as objectively as possible the quality of the time-variable gravity field solutions produced by the different groups involved in the GRACE/GRACE-FO processing, a software for detecting defects in the solutions by supervised artificial intelligence methods was developed for CNES by the company Magellium. A description of the algorithms used (Random Forest and Convolutional Neural Network) will be presented, as well as the performance indices obtained for the CNES solution and, we hope, for a set of other solutions.
How to cite:
Lemoine, J.-M., Bourgogne, S., Bruinsma, S., Vaujour, T., Pfeffer, J., and Thenoz, C.: Evaluation of CNES RL05 by AI and prospects for a sixth re-iteration, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-84, https://doi.org/10.5194/gstm2024-84, 2024.
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Bryant Loomis, Dorothy Hall, Nicolo DiGirolamo, Terence Sabaka, Kenny Rachlin, and Michael Croteau
The benefit of combining long spans of GRACE data for enhancing the spatial resolution of the mean field and regression model parameters (e.g., trend and annual) has been demonstrated for years with the series of GOCO spherical harmonic gravity models (and others). More recently, our group has been applying the same general approach to the estimation of regularized regression mascons, with a particular focus on enhancing the spatial resolution of the recovered mass trends. Initial studies estimated the global trends over the full span of GRACE and GRACE-FO data, but recently we have been working to exploit the same approach over multiple time intervals within the data record, to capture mass change information over shorter intervals while also leveraging the higher spatial resolution afforded by the stacking of normal equations over many months. This approach was recently applied towards the quantification and classification of terrestrial water storage changes in the Great Basin in the Western U.S. (Hall et al., 2024). In this presentation, we provide a summary of this recent study, and discuss the challenges associated with estimating, comparing, and assessing uncertainties for high-resolution regression mascons over multiple time intervals.
How to cite:
Loomis, B., Hall, D., DiGirolamo, N., Sabaka, T., Rachlin, K., and Croteau, M.: Optimization and assessment of high-resolution regression mascons for multiple time intervals within the GRACE/GRACE-FO record, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-18, https://doi.org/10.5194/gstm2024-18, 2024.
Paul Tregoning, Rebecca McGirr, Anthony Purcell, and Herb McQueen
The ANU mascon monthly solutions are derived from least squares inversions of inter-satellite range acceleration signals, using irregularly shaped mass concentration (mascon) elements that cover the Earth. As with all GRACE and GRACE-FO monthly solutions of the temporal gravity field, regularisation of the data inversion must be applied to mitigate the noise in the solutions to permit the geophysical signals to be detected. Previous releases of ANU mascon solutions have used a “regional” regularisation approach, whereby continent-scale areas have been assigned the same mascon parameter uncertainty, which has been used for every month, in what was an attempt to use a “standard” (rather than a “tailored”) regularisation. While individual monthly solutions are smooth and free of striping errors, this standard approach led to noisy time series, with unrealistic variations in mass from one month to the next.
In our ANU RL03 mascon solution we use the level of signal in the range acceleration residuals to determine a unique regularisation sigma for each mascon for each month. While much more time consuming to generate, the RL03 time series of monthly temporal gravity field estimates are more realistic in mass change variations, while maintaining similar long-term trends as the RL02 solutions. Comparisons of degree variance of our RL03 solutions show a comparable level to the other mascon solutions (CSR, JPL, GSFC).
In this presentation we will explain the process of deriving the “tailorerd” regularisation matrix for each month and compare our RL03 solutions to the other mascon solutions. We will show some interesting differences between our and the other solutions, in particular for the polar ice sheets.
How to cite:
Tregoning, P., McGirr, R., Purcell, A., and McQueen, H.: ANU RL03 mascon solutions: regularisation based on range acceleration signal content, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-41, https://doi.org/10.5194/gstm2024-41, 2024.
Thorben Döhne, Martin Horwath, Matthias Willen, and Vasaw Tripathi
Spatially resolved, or spatially constrained, mass changes are the primary science application from GRACE and GRACE-FO. Mascon solutions provide a framework for such mass change solutions, and Mascon solutions based on the analysis of L1 data have become convenient and popular for many users. However, design choices inherent to L1-based solutions are difficult to assess, or to adapt, by users with regard to their specific applications. Mascon solutions based on L2 gravity field solutions allow more access to, and control of, design choices by a wider range of scientists. Such L2-based globally gridded mass change solutions require to find a compromise between propagated GRACE L2 solution errors and leakage errors.
Here we continue previous work on assessments of L2-based mass change solutions. We extend the method of tailored sensitivity kernels, which was originally derived for regional mass changes of the ice sheets, to derive globally distributed mascons based on GRACE Level-2 spherical harmonics. This method allows for a fast solution iteration for assessing different design choices. The resulting sensitivity kernels, which describe the weighting functions that are used to integrate the input data, allow for a direct interpretation of the mass integration step of individual mascons. We present the impact of design choices on ocean mass change and signal leakage over the land-ocean margin. We focus on two design choices: (a) the amendment of a-priori mascon patterns by their sea-level fingerprints and (b) the choice of signal variances and covariances.
How to cite:
Döhne, T., Horwath, M., Willen, M., and Tripathi, V.: Investigating effects of solution design choices on L2-based mascon estimates, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-77, https://doi.org/10.5194/gstm2024-77, 2024.
Pallavi Bekal, Vitali Müller, Malte Misfeldt, Laura Müller, Reshma Krishnan Sudha, and Gerhard Heinzel
The GRACE-FO mission is equipped with two ranging instruments, namely a laser ranging interferometer (LRI) and a microwave instrument (MWI), which are used to measure the distance variations between the two spacecraft (GF1 and GF2). Despite the LRI's role as a technology demonstrator in the current mission, the successor mission, GRACE-C, will exclusively utilise the LRI due to its nanometre-level accuracy in range measurements.
As a consequence of the high level of accuracy achieved, many more features can be observed at high frequencies compared to the MWI range. The range variations have, in general, a gravitational signal, which rolls off quickly above 10 mHz, and non-gravitational signals stemming from atmospheric drag and thruster firings. However, additional spontaneous and sudden range changes are observed (above the gravity-signal band) in LRI and the accelerometer, which we have designated as 'momentum transfer event' (MTE) candidates. When such events turn out to transfer considerable momentum (confirmed MTE), we attribute them to external factors, such as impacts by meteoroids or space debris. However, some events seem to produce no net Δv change but are like vibrations that we attribute to internal structural changes, as previously observed in the GRACE mission (Nadir radiator foil, Kornfeld et al., 2019).
The raw ranging phase, φLRI, is utilised to detect the MTE candidates, from which the range and range acceleration are calculated. A filter has been constructed using the algorithm created by Bähre (2023) in order to facilitate the calculation of the precise change in range rate (ΔvLRI). By applying a specific threshold to the ΔvLRI data, it is possible to identify instances where momentum transfer or vibrations could have occurred between each spacecraft. Moreover, the correlation between the range accelerations of these events and the change in momentum recorded by the accelerometer (ACC) data is analysed. This process detected over 150 events per satellite between June 2018 and July 2023.
In order to improve the detection algorithm, the filter is characterised by simulating different event types while varying the filter parameters. This parametric study facilitated the selection of optimal filter parameters that enable effective detection and accurate Δv estimation.
We then apply the filter to GRACE-FO LRI data, classify the detected events in LRI data according to their correlation with accelerometer data, and present the event statistics. Subsequently, the classifications are examined to ascertain whether the events occur when specific surfaces of the satellite are illuminated by the sun.
As was the case with the effects identified in GRACE data, which informed the development of GRACE-FO, detecting and analysing the effects observed in LRI data are essential for understanding their underlying causes and preventing their recurrence in future missions like GRACE-C and NGGM.
How to cite:
Bekal, P., Müller, V., Misfeldt, M., Müller, L., Sudha, R. K., and Heinzel, G.: Momentum Transfer Events: Detection and Analysis in LRI Data, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-48, https://doi.org/10.5194/gstm2024-48, 2024.
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Laura Müller, Vitali Müller, Yihao Yan, Malte Misfeldt, Pallavi Bekal, and Gerhard Heinzel
Although the Laser Ranging Interferometer (LRI) on GRACE Follow-On has a higher precision than the K/Ka-Band Ranging (KBR) system, special circumstances lead to the decision to operate the satellites in nadir pointing mode and, starting in July 2023, in wide deadband mode to improve the quality of the accelerometer transplants and reduce propellant consumption. During these periods, the LRI is unable to record ranging data due to its narrow pointing requirements. However, the LRI will be the primary and only ranging instrument on future missions, and it is important to understand its data and optimize the data processing.
Therefore, we have continued to (re-)analyze the raw telemetry from the LRI and have advanced the data processing, resulting in alternative LRI1B datasets that we are making publicly available. These data products include the Tilt-to-Length Coupling Correction (aka Antenna Offset Correction in KBR), an alternative calculation of the Light Time Correction, different models for a time-dependent absolute laser frequency, consideration of relativistic effects acting on the spacecraft proper time when converting the phase to a range, and also a quality flag to mark special events such as sun blinding periods.
We have recently produced a new LRI1B v54 release that includes all available LRI data (June 2018 to June 2023) and a dataset with a sampling rate of 0.2 Hz, the same as the KBR sampling, to facilitate comparisons. We will present an analysis of the differences between LRI1B v54 and KBR1B v04 in the spectral, geographic, and time domains to support ongoing investigations into why the ocean RMS values of the monthly gravity fields from LRI are often slightly higher than those from KBR.
In addition, Duwe et al. [2024] recently showed that the post-fit residuals of LRI1B v04 exhibit some artifacts of the order of +/- 2.5 nm/s2, visible when the residuals are high-pass filtered. We were able to confirm most of these features with the LRI1B v04 data, but could not observe them in our internally derived alternative product, LRI1B v54. We further show that the spurious signatures appear even without gravity field recovery by comparing LRI1B v04 and v54 at the level of the raw biased range (or range rate), i.e. without applying correction terms for light-time and antenna offset. We also show that the effects are most likely not present in the LRI1A v04 phase data, leading to the conclusion that these artifacts arise in the v04 Level1a to Level1b processing of SDS.
All of our data products are publicly available at https://www.aei.mpg.de/grace-fo-ranging-datasets.
Duwe et al [2024]: Residual Patterns in GRACE Follow-On Laser Ranging Interferometry Post-Fit Range Rate Residuals, Advances in Space Research, https://doi.org/10.1016/j.asr.2024.03.035.
How to cite:
Müller, L., Müller, V., Yan, Y., Misfeldt, M., Bekal, P., and Heinzel, G.: Recent Analyses with Alternative LRI1B Datasets of AEI, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-70, https://doi.org/10.5194/gstm2024-70, 2024.
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Markus Hauk, Christoph Dahle, Frank Flechtner, Laura Müller, and Vitali Müller
The main observations to recover monthly gravity fields from the GRACE-FO mission are provided by two different and independent instruments, which are the K-band ranging (KBR) instrument and the Laser Ranging Interferometer (LRI). From general perspective, both instruments should measure the same gravitational signals and lead to a similar recovery of monthly gravity fields.
Official Level-1B products for KBR and LRI are provided by the GRACE-FO Science Data System (SDS) and are processed at NASA’s Jet Propulsion Laboratory (JPL). For LRI, alternative Level-1B products are also provided by the Albert-Einstein-Institute (AEI). The German Research Centre for Geosciences (GFZ) processed monthly gravity field solutions using the different Level-1B data sets mentioned before to assess the quality of these solutions and identify possible differences caused by the different Level-1B products. In view of the upcoming reprocessing of an improved GFZ release 7 (RL07) time series, the processing method was already adapted compared to the current GFZ RL06 standards, e.g., by an optimized stochastic modelling of instrument errors for KBR/LRI, GPS and accelerometer observations.
In this presentation, comparisons between GFZ RL06 KBR solutions and improved GFZ preliminary RL07 KBR and LRI (using different LRI data sets) solutions are made in the spatial and frequency domain, and conclusions are driven in terms of quality and quantity.
How to cite:
Hauk, M., Dahle, C., Flechtner, F., Müller, L., and Müller, V.: Comparison of monthly GRACE-FO gravity fields from KBR and different LRI Level-1B data sets, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-17, https://doi.org/10.5194/gstm2024-17, 2024.
Eugene Fahnestock, Christopher McCullough, Matthias Ellmer, Athina Peidou, Dah-Ning Yuan, David Wiese, and Felix Landerer
The GRACE Follow-On (GRACE-FO) mission’s Laser Ranging Interferometer (LRI) technology demonstration has produced ranging data functionally equivalent to the mission’s dual-band microwave (KBR) ranging data for most months between June 2018 and June 2023. Despite the LRI having much better measurement precision than KBR, in the presence of temporal aliasing errors the quality of unconstrained spherical harmonic gravity solutions using LRI data has been at best mostly comparable to solutions using KBR data. We present recent efforts at JPL to make improved LRI gravity solutions in view of the upcoming GRACE Continuity (GRACE-C) mission’s sole reliance on LRI.
Incorporating previous improvements in our de-glitching algorithm for removal of phase jumps in LRI piston phase (both "normal" magnitude and "mega-jumps"), and incorporating master cavity frequency corrections, we consistently reprocessed the whole mission’s LRI data. We reprocessed multiple flavors through level-1 with various choices: 1) estimating and applying both LRI scale factor and LRI time tag bias (ttb); 2) estimating both but applying only ttb; 3) estimating both but constraining ttb to zero, thus relying on LRI datation reporting (for select months); and 4) estimating neither scale factor nor ttb. For the first two of these, our scale factor and ttb estimates agreed well with the Albert Einstein Institute (AEI) LRI1B v50 and v54 values. Motivated by initial experiments, we used settings for our compression and differentiation algorithm acting on LRI data that were identical to such settings for the same algorithm acting on KBR data. This minimized data processing differences between the two ranging products and produced lower-rate (5 s rather than the default 2 s) LRI1B containing instantaneous range, range rate, and range acceleration.
For level-2 processing, we adapted prior 2 s LRI data edits made based on LRI range acceleration postfit residuals for the new 5 sec LRI data, but also needed to do fresh data editing for the early mission timespan (due to GPS data). We optimized relative weighting between LRI and GPS and tried both traditional (white noise model) and VCE (determining full colored noise model) solution strategies. We omitted additional estimation of scale factor or ttb within level-2 solution parameterizations. Comparison of gravity fields between repro flavors supports necessity of the planned scale factor unit (SFU) on GRACE-C. Comparison of the "best-flavor" and "best weighting" monthly gravity fields (52 in all) against their KBR equivalents (accounting for KBR-vs-LRI data coverage differences) also supports the sufficiency of our LRI processing and solution methods for GRACE-C.
The research presented in this abstract has been carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
How to cite:
Fahnestock, E., McCullough, C., Ellmer, M., Peidou, A., Yuan, D.-N., Wiese, D., and Landerer, F.: Recent GRACE Follow-On Laser Ranging Interferometer Gravity Field Processing at JPL, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-23, https://doi.org/10.5194/gstm2024-23, 2024.
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The GRACE Follow-On (GRACE-FO) mission features a unique setup with two independent inter-satellite ranging systems that operate simultaneously. In addition to the K-Band Ranging System (KBR), the GRACE-FO satellites are equipped with an experimental Laser Ranging Interferometer (LRI), offering significantly higher measurement precision than the KBR. The availability of these two concurrent ranging systems enables cross-calibration between the instruments and helps to partially distinguish ranging noise from other sources, such as noise from the accelerometer measurements.
A stochastic model is presented here taking the cross-correlation of the two ranging observation types into account by using variance component estimation to determine the noise covariance function. With this method, the KBR, LRI, and accelerometer noise can be partially separated. This modeling approach results in formal errors of the spherical harmonic coefficients that align well with empirical estimates which is crucial for a combination with other data types and uncertainty propagation. Gravity field solutions from the combined least-squares adjustment using LRI and KBR will be compared to KBR-only solutions.
Monthly gravity field solutions up degree and order 120 only benefit slightly from the incorporation of the LRI data, however when determining gravity field solutions to a higher degree (200) a significant improvement can be seen. This is especially beneficial for the upcoming combined gravity field model GOCO, which is planned to be published in 2025.
How to cite:
Öhlinger, F. and Mayer-Gürr, T.: Towards a new release of the combined global gravity field model GOCO: Contribution of GRACE-FO LRI data, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-58, https://doi.org/10.5194/gstm2024-58, 2024.
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Krzysztof Sośnica, Filip Gałdyn, Adrian Nowak, Joanna Najder, and Radosław Zajdel
Satellite Laser Ranging (SLR) to spherical geodetic satellites is used for recovering the Earth’s gravitational product GM, geocenter motion, and low-degree zonal spherical harmonics, especially C20 and C30. However, the orbital parameters of all geodetic satellites launched after 1992 were not optimized toward the gravity field recovery to maximize their sensitivity to specific gravity field parameters. Instead, the minimization of the potential errors of confirming general relativistic effects, such as the Lense-Thirring, was the main trigger in the selection of orbital parameters.
The diversity of orbital parameters in the current SLR constellation is limited. Most of the geodetic satellites have similar inclination angles: LAGEOS-2, Starlette, and Ajisai about 50°; LARES-1 and LARES-2 about 70°; Stella, Westpac, Larets—in the near sun-synchronous orbit with the inclination of 98°. The inclination angle of LAGEOS-1 is complementary to that of LARES-2 forming the butterfly configuration. The geodetic satellites cover only 60° out of 180° possible inclination angle ranges, i.e., only 33%. Moreover, the orbital heights classify satellites into consistent groups: the LAGEOS-1, LAGEOS-2, and LARES-2 orbit at a height of 5800 km; LARES-1 and Ajisai have a height of about 1500 km; whereas Starlette, Stella, and Westpac have the perigees at the height of about 800 km. Therefore, the gravity field recovery and decorrelation of some gravity field parameters by a diversity of orbital parameters is deficient in the current constellation of geodetic satellites.
We employ the Kaula theorem of gravitational perturbations caused by gravity field coefficients to find the best possible orbital parameters for a future geodetic satellite to maximize orbit sensitivity in terms of the recovery of low-degree gravity field harmonics, geocenter, and GM. We use the maximization of the secular rates of the ascending nodes as the measure of the even-zonal harmonics’ recovery and the maximum of periodic perturbations of the orbital eccentricity vector for the odd-zonal harmonics. We found that the best inclination for a future geodetic satellite is 35°–45° or 135°–145° with a height of about 1500–1700 km to recover C20 and C30. For the optimum heights, we consider three factors emerging from the (1) sensitivity of the satellite to a degree-specific gravity field coefficient, (2) the number of satellite revolutions within a pre-defined period, and (3) observability of a satellite from the perspective of ground stations. For a better geocenter recovery and derivation of the standard gravitational product, the preferable height is 2300–3500 km. We found that none of the existing geodetic satellites have, unfortunately, the optimum inclination angle and height for deriving GM, geocenter, and C20 because there are no spherical geodetic satellites at the heights between 1500 (Ajisai and LARES-1) and 5800 km (LAGEOS-1/2, LARES-2).
How to cite:
Sośnica, K., Gałdyn, F., Nowak, A., Najder, J., and Zajdel, R.: What are the best inclination angles and satellite heights for recovering geocenter, C20, C30, and other low-degree harmonics?, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-3, https://doi.org/10.5194/gstm2024-3, 2024.
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At IfE we estimate monthly gravity field coefficients in terms of spherical harmonic coefficients by using our in-house developed software GRACE-SIGMA. Our recent publication about the post-fit residual analysis of LRI monthly gravity fields showed some unknown effects, (range-rate effects, panel-effects, CNR-effects), which we address further in order to improve our understanding of the overall LRI processing. In addition, we want to give an overview of ocean tide errors and non-modeled ocean tide frequencies that have been identified in GRACE(-FO) K-band post-fit range rate residuals. Furthermore, we present our recent analyses of the spherical harmonic coefficients obtained from LRI gravity fields as well as the combined processing and quality assessment of LRI and KBR.
How to cite:
Duwe, M., Koch, I., and Flury, J.: Analysis and intercomparison of LRI and KBR gravity fields and their post-fit range rate residuals, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-75, https://doi.org/10.5194/gstm2024-75, 2024.
Matthias Ellmer, David Wiese, Da Kuang, Felix Landerer, Carmen Blackwooed, Christopher McCullough, Dah-Ning Yuan, Eugene Fahnestock, and Athina Peidou
The RL07 series of GRACE gravity field products generated at JPL is a reprocessing of updated Level 1 data for the entire mission duration. Some aspects of the Level 2 processing have been updated from the RL06 series, in an effort to improve solution quality and uncertainty quantification.
Level 2 processing improvements include the co-estimation and use of full observation covariance matrices for both GPS and inter-satellite ranging KBR observations, and the use of an updated background field (GOCO06s) and other models. The updates ensure consistency and continuity with the GRACE-FO data record, which is processed using the same standards.
We present time series and analysis of these new fields, and compare them to the previously released JPL RL06 series of gravity field solutions, showing higher fidelity in formal errors, and improvements in solution noise levels.
How to cite:
Ellmer, M., Wiese, D., Kuang, D., Landerer, F., Blackwooed, C., McCullough, C., Yuan, D.-N., Fahnestock, E., and Peidou, A.: GRACE and GRACE-FO Level 2 RL07 data processing at JPL, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-24, https://doi.org/10.5194/gstm2024-24, 2024.
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Torsten Mayer-Guerr, Patrick Dumitraschkewitz, Sandro Krauss, Felix Oehlinger, Andreas Strasser, Barbara Suesser-Rechberger, and Cornelia Tieber-Hubman
The Gravity Recovery Object Oriented Programming System (GROOPS) is a software package written in C++ that allows the user to perform core geodetic tasks. The software provides gravity field recovery from satellite and terrestrial data, determination of low earth orbits from Global Navigation Satellite System (GNSS) measurements, Satellite Laser Ranging (SLR), and computation of GNSS constellations and ground station networks. In addition, GROOPS contains a variety of tools for analyzing and displaying mass changes including filtering, surface loading corrections and division into river basins. For easy and intuitive setup of complex workflows, GROOPS includes a graphical user interface for creating and editing configuration files. The source code of GROOPS is released under the GPL v3 licence and is available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples and installation instructions for different platforms.
How to cite:
Mayer-Guerr, T., Dumitraschkewitz, P., Krauss, S., Oehlinger, F., Strasser, A., Suesser-Rechberger, B., and Tieber-Hubman, C.: GROOPS: The Open-source Software from TU Graz, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-55, https://doi.org/10.5194/gstm2024-55, 2024.
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Zitong Zhu, Vitali Müller, Changqin Wang, Yihao Yan, Heng Yin, Haoming Yan, and Gerhard Heinzel
Gravity measurements from Low-Low Satellite-to-Satellite Tracking (LL-SST) systems, such as GRACE and GRACE-FO, collect gravity field data using GPS-observed orbits and variations in inter-satellite distances measured by inter-satellite ranging systems. Unlike GRACE, GRACE-FO uses a Laser Ranging Interferometer (LRI) designed as a technology demonstrator for future gravity missions. Some issues, such as an uncertainty in the absolute laser frequency causing an LRI scale factor error, and baseline errors in the GPS observations, i.e., offsets in the 200 km separation, can lead to significant effects on the gravity field. These effects were evaluated by developing an analytical relationship between the observations and the spherical harmonic coefficients (SHCs) of the gravity field. Both the LRI scale factor and baseline errors affect the SHCs in a comparable manner, leading to significant non-stochastic errors, especially at the low levels of the gravity field. Numerical simulations show that a scale factor of 1E-8 results in a geoid height error of about 0.074 mm at degree 2. This effect exceeds that of the atmospheric and ocean de-aliasing (AOD) model errors. Furthermore, a comparison of the LRI scale factor time series for data from GRACE-FO in 2021-2022, based on the theoretical form developed here, with a scale factor calculated by cross-calibrating KBR and LRI, showed a consistency between the two, with an estimated uncertainty of about 5.75E-8. The analytical formulation presented here effectively describes the influence of the scale factor or baseline error on LL-SST gravity missions.
How to cite:
Zhu, Z., Müller, V., Wang, C., Yan, Y., Yin, H., Yan, H., and Heinzel, G.: Impact of Scale Factor and Baseline Errors on Gravity Field Estimation: Analysis and Validation with GRACE Follow-On Data and Simulations , GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-64, https://doi.org/10.5194/gstm2024-64, 2024.
Michael Murböck, Christoph Dahle, Natalia Panafidina, Markus Hauk, Josefine Wilms, Karl-Hans Neumayer, and Frank Flechtner
The central hypothesis of the Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV), funded for the second three years phase by the German Research Foundation DFG, reads: only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-term consistency of mass transport series from satellite gravimetry can be significantly increased; and only in that case the potential of future technological sensor developments can be fully exploited.
In continuation of the first RU phase, the individual project Improved Stochastic Modeling in GRACE/GRACE-FO Real Data Processing (ISTORE-2) aims for completion of the optimized stochastic modeling for GRACE and GRACE-FO gravity field determination. This includes stochastic modelling of the non-tidal atmospheric and oceanic dealiasing (AOD) models which was recently implemented into the GRACE/GRACE-FO Level-2 processing at the German Research Centre for Geosciences (GFZ). In this context, we co-estimate AOD model coefficients using AOD error variance-covariance matrices (VCMs) in terms of constraint matrices.
This presentation provides an overview of the main processing steps together with AOD error analyses and different test cases for the AOD VCMs. In particular, we investigate the impact of taking into account not only static but also temporal correlations of the AOD models. Results are presented in terms of gravity field solutions for selected test months in the spectral and spatial domain.
How to cite:
Murböck, M., Dahle, C., Panafidina, N., Hauk, M., Wilms, J., Neumayer, K.-H., and Flechtner, F.: Stochastic modelling of non-tidal atmospheric and oceanic dealiasing models for GFZ GRACE/GRACE-FO Level-2 processing, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-36, https://doi.org/10.5194/gstm2024-36, 2024.
Natalia Panafidina, Michael Murböck, Christoph Dahle, Markus Hauk, Josefine Wilms, Karl-Hans Neumayer, Frank Flechtner, Linus Shihora, Henryk Dobslaw, and Laura Jensen
The Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV) aims at improving the understanding and providing new information about sensor data, background models and the processing strategies for the GRACE and GRACE-FO data. The achieved improvements in the standard GRACE data processing create a possibility for improvements in the computation of gravity fields with a high temporal resolution. In the current contribution we focus on the studying the potential of daily gravity filed solutions obtained by Kalman filtering. We use in particular the NEROGRAV results on stochastic modeling of the observations and background models used in the GRACE data processing, as well as the provided stochastic information on the geophysical processes governing the variations of the gravity field on sub-monthly time scales.
While the standard GRACE gravity field solutions are obtained using one month of observational data, there are on-going attempts to obtain high-quality gravity fields with a higher temporal resolution. Unlike the monthly solutions, which are computed fully independent of each other, the computation of the daily gravity fields requires taking into account the temporal correlations between the subsequent solutions. The assessment of this timely correlation is based on the knowledge of the stochastic properties of the underlying geophysical processes. In this contribution we study how the daily Kalman solutions are influenced by the stochastic information on the two main geophysical processes causing high-frequency variations in the gravity field: non-tidal atmospheric and oceanic variations and hydrology. We present results for daily gravity field solutions for several test months in the spectral and spatial domain.
How to cite:
Panafidina, N., Murböck, M., Dahle, C., Hauk, M., Wilms, J., Neumayer, K.-H., Flechtner, F., Shihora, L., Dobslaw, H., and Jensen, L.: Using stochastic information on geophysical processes for daily GRACE Kalman filter solutions, GRACE/GRACE-FO Science Team Meeting, Potsdam, Germany, 8–10 Oct 2024, GSTM2024-80, https://doi.org/10.5194/gstm2024-80, 2024.
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