G4.2

The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission has collected nearly 4 years of monthly gravity and mass change observations since its launch in May 2018. On March 17 we have celebrated the 20^th anniversary of the GRACE launch. The combined GRACE/GRACE-FO mass change data record is therefore now spanning exactly two decades, and is an essential tool to quantify and track Earth’s water movement and surface mass changes across the planet. Monitoring changes in ice sheets and glaciers, near-surface and underground water storage, the amount of water in large lakes and rivers, as well as changes in sea level and ocean currents provides an integrated global view of how Earth’s water cycle and energy balance are evolving.

In this presentation we will update the community on the current GRACE-FO mission status and near-term plans, including instrument and flight system performance (i.e., satellite health status and outlook, performance of precise inter-satellite ranging from the K/Ka band and Laser Ranging Interferometers, and accelerometry as processed at Jet Propulsion Laboratory (JPL), the official Level-1 data analysis center). We will discuss the GRACE-FO science data quality, reprocessing plans, and highlight recent science results, discoveries, and applications. Finally, we will conclude with a short outlook towards achieving continuity with future mass change missions.

How to cite: Flechtner, F., Landerer, F., Save, H., Mccullough, C., Dahle, C., Bettadpur, S., Watkins, M., Snopek, K., and Gaston, R.: GRACE-FO Science Results and Mission Status, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3672, https://doi.org/10.5194/egusphere-egu22-3672, 2022.

The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission, launched in May 2018, continues the time-variable gravity field time series first established by the GRACE mission in 2002. This paper will provide the assessment of the different gravity field and mass anomaly products produced at the Center for Space Research (CSR). This paper will present the error characterization of the official CSR RL06 solutions and its evolution along with uncertainty quantification.  This paper will present the results of the assessments relative to both the expectations from GRACE performance and relative to expectations of signals in independent datasets. This paper will provide introduction to multiple experimental mass anomaly products produced at CSR and will summarize the improvements planned for the future. 

How to cite: Save, H., Bettadpur, S., Nagel, P., Pie, N., Poole, S., Tamisiea, M., and Kang, Z.: GRACE-FO RL06 Level-2 Gravity Fields and Mascon Solutions from CSR: Assessments and Future Plans, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11161, https://doi.org/10.5194/egusphere-egu22-11161, 2022.

GFZ, as part of the GRACE/GRACE-FO Science Data System, is one of the official Level-2 processing centers routinely providing monthly gravity models. These models are used by a wide variety of geoscientists to infer mass changes mainly at the Earth’s surface. While the current release 6 (RL06) is still operationally processed, plans and internal tests for a reprocessed GFZ RL07 time series are already in progress.

In this context, recent developments have been made within the Research Unit (RU) NEROGRAV (New Refined Observations of Climate Change from Spaceborne Gravity Missions), funded for 3 years by the German Research Foundation DFG. The central hypothesis of this RU 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.” Two of the individual projects within the RU closely interact on optimized space-time parameterization (reducing non-tidal temporal aliasing error effects) and stochastic modeling regarding instrument data (accelerometer and inter-satellite ranging observations) as well as background models (e.g. by the utilization of covariance information for ocean tides).

This presentation provides an overview of the developed advanced processing strategies, and their individual and combined impact on GFZ’s Level-2 products compared to current GFZ RL06 solutions.

How to cite: Hauk, M., Murböck, M., Panafidina, N., Dahle, C., Wilms, J., Flechtner, F., and König, R.: Advanced processing strategies for an improved GFZ GRACE/GRACE-FO Level-2 data release, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5372, https://doi.org/10.5194/egusphere-egu22-5372, 2022.

The Institute of Geodesy of the Graz University of Technology has a successful record in producing GRACE/GRACE-FO gravity fields using an in-house developed software, the Gravity Recovery Object Oriented Programming System (GROOPS). The ITSG-Grace2018 gravity field model is the latest release of the ITSG sequence covering the complete GRACE/GRACE-FO time-span. The new release will be based on planned Level-1B Release 05 data and the AOD1B Release 07 dealiasing product. It will include a static field, unconstrained monthly, as well as Kalman smoothed daily solutions.

Updates and improvements over the previous release are summerized as follows: (a) We revisit the Level-1A processing of transplant accelerometer data and co-estimate their unmodeled linear accelerations due to thruster activities; (b) We improve the estimation of subdaily high-frequency mass variations by increasing both temporal and spatial resolutions; (c) Taking advantage of the available GRACE-FO LRI measurements, we introduce combined KBR and LRI gravity field solutions based on a stochastic modeling that determines proper weighting between KBR and LRI observations.

This contribution will highlight the selected parts of the processing chain and their effect on the estimated gravity field solutions.

How to cite: Mayer-Guerr, T., Behzadpour, S., Kvas, A., Krauss, S., Strasser, S., and Süsser-Rechberger, B.: Towards a new ITSG-Grace release: updated data products and improvements within the processing chain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7585, https://doi.org/10.5194/egusphere-egu22-7585, 2022.

Currently a reprocessing of the LUH GRACE monthly gravity field solutions is carried out at our institute. The new processing chain utilizes updated background models, parametrization and outlier detection. This processing chain is consistent with the approach currently applied for our operational GRACE-FO time series. In this contribution, we present our gravity field recovery strategy. The reprocessed time series is compared to the previous LUH GRACE series as well as to the most recent series of other GRACE analysis centers. We present a comparison of the noise behavior (in terms of residual signal over the oceans), signal content (river basin amplitudes, regional mass trends) and low degree coefficients. In addition, post-fit range-rate residuals are inspected.

How to cite: Koch, I., Duwe, M., and Flury, J.: Reprocessing of LUH GRACE solutions – current status, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11396, https://doi.org/10.5194/egusphere-egu22-11396, 2022.

Temporal gravity field modelling from GRACE Follow-On deals with several noise sources polluting the observations and the system of equations, be it actual measurement noise or mis-modellings in the underlying background models. One way to collect such deficiencies is to co-estimate additional pseudo-stochastic parameters in the least-squares adjustment which are meant to absorb any kind of noise while retaining the signal in the gravity field and orbit parameters. In the Celestial Mechanics Approach (CMA) such pseudo-stochastic parameters are typically piece-wise constant accelerations set up in regular intervals of e.g., 15 min, and an empirically determined constraint is added to confine the impact of the additional quantities. As the stochastic behaviour of these parameters is unknown because they reflect an accumulation of a variety of noise sources, Variance Component Estimation (VCE) is a well established tool to assign a stochastic model to the pseudo-stochastic orbit parameters driven by the observations.
In the simplest case the magnitude of the constraints of the pseudo-stochastic orbit parameters can be determined fully automatically.

We present results for GRACE Follow-On gravity field recovery when extending the CMA by stochastic models for the piece-wise constant accelerations computed with VCE and provide noise and signal assessment applying the quality control tools routinely used in the frame of the Combination Service for Time-variable gravity fields (COST-G).

How to cite: Lasser, M., Meyer, U., Arnold, D., and Jäggi, A.: Variance component estimation for co-estimated noise parameters in GRACE Follow-On gravity field recovery, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7931, https://doi.org/10.5194/egusphere-egu22-7931, 2022.

Continuous efforts have been made by different GRACE data analysis centers to improve the quality of monthly gravity field solutions, where one of the key issues concerns the treatment of noise in the parameter estimation process. In the broader context, the noise is not limited to the imperfection of sensor measurements only but also includes unmodelled and/or mismodelled parts of the satellite dynamics. In this contribution, we revisit four widely used strategies to reduce the influence of noise in GRACE gravity field recovery, which are: the estimation of high-frequency (constrained) empirical accelerations (ACC for short); the estimation of K-band range-rate empirical parameters (KBR); the utilization of fully populated covariance matrix for data weighting (COV), and the time series model-based filtering technique (FILT). In their ways to deal with the noise, the ACC and KBR strategies can be grouped into the method of empirical parameterization, while the COV and FILT strategies belong to the treatment of stochastic modelling. From a theoretical aspect, we regard the ACC and COV strategies as special cases of the least-squares collocation (LSC); the ACC and KBR strategies can be directly linked by the linear perturbation theory, while the COV and FILT strategies resemble different spectral estimation methods. Furthermore, we use numerical simulations to evaluate the performances of the four strategies, which show that the ACC, COV and FILT are more effective in mitigating noise than the KBR strategy. In the spectral domain, the stochastic modelling-based strategies (COV and FILT) have the full-spectrum capability to treat noise, while empirical parameters adopted in the ACC and KBR strategies work as high-pass filters. Consequently, stochastic modelling can lead to more consistent formal error estimates than empirical parameterization, especially for high-degree spherical harmonic coefficients.

How to cite: Nie, Y., Shen, Y., Pail, R., and Chen, Q.: Treatment of Noise in GRACE Gravity Field Recovery: A Comparison between Empirical Parameterization and Stochastic Modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1604, https://doi.org/10.5194/egusphere-egu22-1604, 2022.

The project „Time-variable gravity and mass redistribution from synergistic use of GRACE-FO and Chinese gravity satellites“ aims at establishing improved time-variable gravity field models. This work is a joint initiative of the National Natural Science Foundation of China (NSFC) and the German Research Foundation (DFG).

Gravity field estimation from the existing GRACE and GRACE-FO missions will be improved, e.g. by optimizing dealiasing signals, refining the noise modeling, accelerometer calibration and optimizing anisotropic filtering techniques. Furthermore, the possibilities of a combination with the upcoming Chinese gravity field mission TianQin-2 will be explored and optimal orbit parameters for TianQin-2 will be determined.

One focus area is the East China Sea. Here, we will isolate the ocean mass change signal over this study region and apply a joint inversion framework to close the regional sea level budget. The contribution of sediment discharge will be accounted for by evaluating oceanic velocities from an ocean model using a Lagrangian approach.

Groundwater storage (GWS) variations will be closely investigated over the North China Plain. First, GWS is calculated by evaluating GRACE(-FO) gravity solutions. For this aim, non-GWS compartments will be removed using global and regional models. An error-estimation considers the uncertainty of measurement errors, post-processing of the gravity field solutions and model errors. Secondly, GWS will directly be inferred from hydrological models. Observations from monitoring wells and GPS stations will be used as independent additional observations.

In this contribution, we will introduce our project and its objectives in more detail. Furthermore, we will show preliminary results regarding ocean mass change in the East China Sea and GWS variations over the North China Plain.

How to cite: Lück, C., Kusche, J., Feng, W., Shen, Y., Chen, Q., and Wang, C.: Time-variable gravity and mass redistribution from synergistic use of GRACE-FO and Chinese gravity satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7848, https://doi.org/10.5194/egusphere-egu22-7848, 2022.

The Gravity Recovery and Climate Experiment (GRACE) was a space mission from 2002-2017. While the two identical satellites were orbiting the Earth one after the other, the inter-satellite distance variations caused by the Earth's mass distribution were measured. This data can be used to determine the structure of the Earth's gravity field and observe its time-varying component, such as melting ice caps or water storage on land.  In order to continue these useful data streams, a GRACE Follow-On mission was launched in 2018. This successor hosts a novel instrument called the Laser Ranging Interferometer (LRI) for measuring the distance variations with higher precision than the conventional Microwave Instrument (MWI).

The raw measurements of the LRI need to be converted into an intermediate data product before the gravity field recovery can start. The official LRI1B data product is provided by the Science Data System (SDS) based on multiple processing steps. Here, we present an alternative LRI1B data set, that allows investigating different processing strategies and algorithms which might improve the data quality. For instance, our processing uses a different deglitching algorithm for detecting and removing phase jumps,  which are caused by thruster activation of the satellites. Furthermore, we indicate special events like phase jumps, sun-blindings and momentum-transfer-events likely caused by micrometeorites in the quality flag. Additionally, the light time correction used for conversion of the biased range into an instantaneous range is computed differently for the AEI-LRI1B product. Comparing the versions of SDS and AEI allows us to verify and validate the correctness of the officially provided LRI1B of SDS.

How to cite: Müller, L., Müller, V., Misfeldt, M., Wegener, H., Hauk, M., and Heinzel, G.: Derivation of an alternative GRACE Follow-On LRI1B data product, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6109, https://doi.org/10.5194/egusphere-egu22-6109, 2022.

The purpose of this study is to diagnose how the magnetic disturbances and the flow of the vertical currents can be identified from the non-gravitational acceleration measurements of GRACE C. Whereas the non-gravitational measurements are routinely used for the gravity field modelling, they can be used for the study of the upper atmosphere. Thus, separating the dominant forces of Solar Radiation Pressure (SRP) and the drag acting on the satellite is crucial in the calibration of the accelerometers and in understanding how the non-gravitational forces affect the satellite. In our analysis, we use an alternative weighted 1B dataset (ACW1B) of non-gravitational accelerations, which comprises the standard deviations of each measurement derived from the 1A data (10 Hz) using a weighted Gaussian filter with a cut-off frequency of 35mHz. Subsequently, we extract the atmospheric drag and the SRP, acting on the GRACE C satellite, directly from the accelerometer measurements. The weighted residual series along the three axes of the Science Reference Frame are analyzed based on their latitudinal, longitudinal, and local time variations and are compared with the field-aligned currents (FAC) dataset derived from the magnetic observations of GRACE C, provided by GFZ. We analyze the residual series in Magnetic Local Time (MLT) during the periods of combined Solstices, Equinoxes and on monthly basis in different frequency bands. In the higher frequency bands (f > 0.02 Hz) high correlation between the accelerometer residual series and the FACs is revealed, especially in the radial direction. The measurements in the along-track direction are the most disturbed during the geomagnetic storms, while in the radial direction we can distinctly identify the disturbances caused by the Earth Radiation pressure in the lower frequency bands. In the cross-track direction, the residual series reveal a strong signal in the equatorial region due to thruster activations. High dependency on Magnetic Local Time along the three axes of the accelerometer and consistent monthly differences between the ascending and descending tracks are investigated and presented.

How to cite: Tzamali, M. and Pagiatakis, S.: Non-gravitational accelerations and magnetic disturbances: What can be observed from the residual series of accelerometers on GRACE C?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8955, https://doi.org/10.5194/egusphere-egu22-8955, 2022.

In the frame of the CubeGrav project, funded by the German Research Foundation, Cube-satellite networks for geodetic Earth observation are investigated on the example of the monitoring of Earth’s gravity field. Satellite gravity missions are an important element of Earth observation from space, because geodynamic processes are frequently related to mass variations and mass transport in the Earth system. As changes in gravity are directly related to mass variability, satellite missions observing the Earth’s time-varying gravity field are a unique tool for observing mass redistribution among the Earth’s system components, including global changes in the water cycle, the cryosphere, and the oceans. The basis for next generation gravity missions (NGGMs) is based on the success of the single satellite missions CHAMP and GOCE as well as the dual-satellite missions GRACE and GRACE-FO launched so far, which are all conventional satellites.   
In particular, feasibility as well as economic efficiency play a significant role for future missions, with a focus on increasing spatio-temporal resolution while reducing error effects. The latter include the aliasing of the time-varying gravity fields due to the under-sampling of the geophysical signals and the uncertainties in geophysical background models. The most promising concept for a future gravity field mission from the studies investigated is a dual-pair mission consisting of a polar satellite pair and an inclined (approx. 70°) satellite pair. Since the costs for a realization of the Bender constellation are very high, this contribution presents results of the CubeGrav project and focuses on alternative concepts in the form of different constellations and formations of small satellites. The latter includes both satellite pairs and chains consisting of trailing satellites. The aim is to provide a cost-effective alternative to the previous gravity field satellites while simultaneously increasing the spatiotemporal resolution and minimizing the above-mentioned error effects.

In numerical closed-loop simulations, the impact of different satellite formations and constellations will be investigated for the retrieval of monthly gravity fields. The configurations differ in the orbital setup including the number of orbital planes and key orbit parameters like altitude and inclination. The ground track coverage of the selected orbits will be analysed since an improved spatial sampling with specific sub-cycles is beneficial for estimating short-temporal gravity fields which will be co-parametrized in the overall solution approach. Due to the large number of observations, it is possible to retrieve sub-daily gravity fields down to quarter-day resolution, which exceeds the capabilities of the existing gravity mission like GRACE or GRACE-FO by far. These (sub-)daily gravity field solutions can also improve the overall monthly gravity product, which will be proven for several satellite constellations and formations. All in all, the opportunities and limits of multiple satellites pairs and chains of trailing satellites for achieving the highest possible spatial and temporal resolution shall be analysed in detail.

How to cite: Pfaffenzeller, N. and Pail, R.: Potential and limits of small satellite networks for temporal gravity field retrieval in the frame of the CubeGrav Project, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5005, https://doi.org/10.5194/egusphere-egu22-5005, 2022.

The GPS data collected by the Swarm satellites form the basis for monthly global gravity field models that are complete and uninterrupted since late 2013, thus already covering a period of eight years. A nice aspect is that this time series covers the gap between the GRACE and GRACE-FO missions, as well as any other short gaps in their time series, with a spatial resolution of roughly 1500 km.

The Astronomical Institute of the University of Bern, the Astronomical Institute of the Czech Academy of Sciences, the Delft University of Technology, the Institute of Geodesy of the Graz University of Technology, and the School of Earth Sciences of the Ohio State University have teamed up to routinely provide these monthly models, with the support of the European Space Agency and the International Combination Servicefor Time-variable Gravity Fields (COST-G). The models are published every 3 months at ESA’s Swarm Data Access server (https://swarm-diss.eo.esa.int) as well at the International Centre for Global Earth Models (http://icgem.gfz-potsdam.de/series/02_COST-G/Swarm). Our gravity field models do not rely on any other source of gravimetric data nor any a priori information in for example the form of temporal and spatial correlations. The strength of our approach is that each institute exploits different gravity inversion strategies, thus producing independent solutions, which are combined at the solution level using weights derived with Variance Component Estimation.

Considering a reference parametric model derived from GRACE/GRACE-FO data, our models traditionally agree at the level of roughly 4 cm Equivalent Water Height (EWH). Since early 2020, developments in the processing of the kinematic orbits have improved this figure to 3 cm. A particularity of the Swarm gravity field models is that the deep ocean areas are ~30-50% noisier than land areas, with the underlying reason yet unknown. At the spatial resolution of Swarm, the time series of large water storage basins show a temporal correlation of 0.75 when compared with GRACE models, and their trends agree within 1 cm/year in terms of EWH.

How to cite: Teixeira da Encarnacao, J., Arnold, D., Bezdek, A., Dahle, C., Guo, J., van den IJssel, J., Jaeggi, A., Klokocnik, J., Krauss, S., Mayer-Guerr, T., Meyer, U., Sebera, J., Shum, C., Visser, P., and Zhang, Y.: Eight years of temporal gravity changes observed by the Swarm satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11782, https://doi.org/10.5194/egusphere-egu22-11782, 2022.

GRACE observations revealed that rapid mass loss in the West Antarctic Ice Sheet (WAIS) abruptly paused in 2015, followed by a much lower rate of mass loss ( 21.3±5.7 Gt‧yr^-1) until the decommissioning of GRACE in 2017. The critical 1-year GRACE inter-mission data gap raises the question of whether the reduced mass loss rate persists. The Swarm gravimetry data, which have a lower resolution, show good agreement with GRACE/GRACE-FO observations during the overlapping period, i.e. high correlation (0.78) and consistent trend estimates. Swarm data efficiently bridge the GRACE/GRACE-FO data gap and reveal that WAIS has returned to the rapid mass loss state (  161.5±48.4  Gt‧yr^-1) that prevailed prior to 2015 during the GRACE inter-mission data gap. The changes in precipitation patterns, driven by the climate cycles, further explain and confirm the dramatic shifts in the WAIS mass loss regime implied by the Swarm observations.

How to cite: Zhang, C., Shum, C.-K., Bezděk, A., Bevis, M., Teixeira da Encarnação, J., Tapley, B., Zhang, Y., Su, X., and Shen, Q.: Climate-driven rapid mass loss in West Antarctica revealed by Swarm gravimetry in the absence of GRACE, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2032, https://doi.org/10.5194/egusphere-egu22-2032, 2022.

Besides gravity field information derived from ultra-precise inter-satellite ranging of dedicated missions like GRACE and GRACE-FO, the analysis of GPS tracking data collected by various Low Earth orbiting (LEO) satellites can provide alternative and mostly uninterrupted time series of large-scale time-variable gravity field signals. For this purpose, the GPS data may be used to derive kinematic LEO orbit positions that can subsequently be utilized as pseudo-observations for gravity field recovery.

In this study, we focus on the use of the GPS data obtained by the Copernicus Sentinel-1, -2, and -3 missions. Each of these missions consists of a constellation of two LEO satellites operating on sun-synchronous orbits with inclinations of about 98° and at different altitudes ranging from about 700 to 800 km. Besides mission-specific instruments, the Sentinel satellites are equipped with high-quality dual-frequency GPS receivers providing a data sampling rate of 10s (Sentinel-1, -2) or 1s (Sentinel-3). At the Astronomical Institute of the University of Bern (AIUB), GPS-based precise orbit determination is routinely performed for the Sentinel satellites. We make use of the kinematic LEO orbit positions to perform gravity field recovery with the Celestial Mechanics approach. In the presentation, we will provide details on the quality and sensitivity of Sentinel-based gravity field models and analyze their contribution to a combined gravity field time series derived from Swarm and GRACE-FO GPS data.

How to cite: Grombein, T., Lasser, M., Arnold, D., Meyer, U., and Jäggi, A.: Assessment of gravity field models derived from Sentinel GPS data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5202, https://doi.org/10.5194/egusphere-egu22-5202, 2022.

GRACE has been undoubtedly one of the most important sources to observe mass transport at global and regional scales. Within the COST-G project, GRACE and GRACE-Follow On gravity field solutions from various processing centers are being combined to further increase the spatial and temporal resolution. However, the GRACE and GRACE-Follow On time series suffer from a data gap of about one year. Thus, there is a need for an intermediate technique that will bridge the gap between the two missions and will allow 1) for a continued and uninterrupted time series of mass observations and 2) to compare, cross-validate and link the two time series. Here, we present a complete series that covers the gap period between the end of the GRACE mission in 2017 and the first available solutions of GRACE-Follow On in 2018. We will focus on the combination of high-low satellite-to-satellite tracking (hlSST) of low-Earth orbiting satellites by GNSS in combination with SLR. SLR is known to provide highest quality time-variable gravity for the very low degrees (2-5) and hlSST is able to provide a higher spatial resolution at a lower precision in the very low degrees. We discuss also the achievable spatial and temporal resolutions and possible applications in GIA and in interseasonal variation analysis. 

How to cite: Weigelt, M., Jäggi, A., Meyer, U., Arnold, D., Meyer-Gürr, T., Vishwakarma, B. D., Devaraju, B., Steffen, H., Sosnica, K., and Ebadi, S.: Bridging the gap between GRACE and GRACE-Follow On by the combination of HLSST and SLR, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5820, https://doi.org/10.5194/egusphere-egu22-5820, 2022.

GRACE and GRACE-Follow On gravity field solutions form an unprecedented time series of time-variable gravity field which is indispensable for geosciences, water and climate monitoring. However, the GRACE and GRACE-Follow On time series suffer from a data gap of about one year. Thus, there is a need for an intermediate technique that will bridge the gap between the two missions and will allow 1) for a continued and uninterrupted time series of mass observations and 2) to compare, cross-validate and link the two time series. The most promising method for the long-wavelength part of the gravity field is a combination of high-low satellite-to-satellite tracking (hlSST) of low-Earth orbiting satellites by GNSS in combination with satellite laser ranging (SLR), where SLR is known to provide the highest quality time-variable gravity for the very low degrees (2-5) and hlSST is able to provide a higher spatial resolution at a lower precision in the very low degrees. In this contribution, we discuss the importance of the SLR contribution to the combined solution showing that a hlSST solution is underperforming and a considerable improvement and stabilization for the low degrees can be achieved by the inclusion of SLR for the very low degrees. We also shed light on different combination techniques on the normal equation level with and without variance component estimation and discuss their advantages and difficulties in the implementation.

How to cite: Ebadi, S., Weigelt, M., Jäggi, A., Meyer, U., Arnold, D., and Mayer-Gürr, T.: Contribution of SLR to combined hlSST+SLR solutions for bridging the gap between GRACE and GRACE-Follow On, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6526, https://doi.org/10.5194/egusphere-egu22-6526, 2022.

Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission and its successor (Follow-On) (FO) monitored the temporal variations of Earth's gravity field at monthly timescales and provided data to assess natural and anthropogenic drivers of water storage variability. Yet, missing solutions within and between the missions disrupt the continuity of observations and weaken the interpretation of changes in the Earth's mass movements. Most approaches used to impute the missing solutions rely on external data, either from a separate satellite (e.g., SWARM), or Global Positioning System, or adopting hydrological and climate data within statistical learning frameworks. Such approaches jeopardize the uniqueness of GRACE-GRACE FO observations and introduce a level of uncertainty from the external data. In addition, the missing solutions are commonly imputed over land only, but not for the ocean or the ice sheets. Further, the reconstructed signals are recovered as single value without uncertainty estimates.

The objective of this research was to impute missing solutions within and between the two missions using GRACE data alone within a Bayesian framework. We decomposed the geophysical signal in GRACE-GRACE (FO) data into its temporal components and modeled each component to infer their posterior distribution over monitored and missing dates. The geophysical signal in GRACE missions is structured as a trend, interannual, annual, and semi-annual cycles. Using informative priors on the ranges of signal intercepts, slopes, frequencies, variability, and amplitudes and assuming these parameters follow a normal distribution, we approximated the posterior distribution of each component using four chains of Markov Chain Monte Carlo. We used 4000 samples for each chain  (518x10⁶ iterations globally) and ensured equilibrium sampling and posteriors convergence over the parameters. Medians of posterior distributions of all components were then added back to reconstruct the signal, and uncertainty was derived at 95% credible interval. Finally, to maintain the same level of variability as the original data, model residuals were added back over the monitored times only. We reconstructed 229 solutions for the period 04/2002 -04/2020 using 188  mascons solutions released by the University of Texas at Austin, Center for Space Research at a 1-degree scale and for 30 hydrological basins.  

Results reveal that the reconstructed data explain most of the total variability in original data with median ^r-square of 0.99 at basin scale. However, the explained variability decreases to median 78% at grid scale. We noticed that model performance is good for most of the land/ocean and ice sheet surfaces with ^r-square over 0.8, except in regions where the signal was already weak (e.g., Sahara desert) or where sub-annual fluctuations mostly dominate the signal (e.g., southern Indian and Pacific Oceans and northern Atlantic Ocean). We attribute this low performance to the model parameterizations. However, the variability in GRACE data is maintained in these regions when the residuals are added back. The implemented framework does not rely on or require external information and uses GRACE data only. The predictive posterior distributions can be adopted for nowcasting and integrated into near-real-time applications (e.g., data assimilation), which minimizes the GRACE data latency.  

How to cite: Rateb, A., R. Scanlon, B., Sun, A., and Save, H.: Inferring Missing Solutions within and between GRACE and GRACE-FO Missions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3215, https://doi.org/10.5194/egusphere-egu22-3215, 2022.

Documenting the preparation phase of giant earthquakes and retrieving pre-seismic signals of upcoming events is a crucial challenge. Over the short term, various deformation transients have been detected before large subduction events, emphasizing in particular the role of the slab pull in driving plate motions (e.g., Bouchon et al., 2016 ; Bedford et al., 2020). Among them, we previously evidenced an anomalous gravity gradient signal during the months before the March 2011 Tohoku earthquake, likely originating from the solid Earth (Panet et al., 2018). We showed that it could reflect a broad deformation of the subducted slab prior to the event, generating the giant earthquake as the deformation propagated from depth to surface.

Taking the example of the 2011 Tohoku earthquake, we conduct here a systematic and global retrospective analysis of time series of GRACE-reconstructed gravity gradients truncated in February 2011. Our aim is to test whether the gravity gradient variations preceeding the earthquake can be identified as singular and potentially originating from the solid Earth in an automated way and without knowledge on the upcoming event. First, we enhance the angular resolution of the gravity gradients in order to extract signals closely aligned with a chosen plate boundary orientation. Along this preferred orientation, we extract fast temporal variations at the sub-annual timescales of geodetic, gravitational and seismic signals reported before the event in previous studies. To evaluate the significance of the obtained gravity gradient anomalies, we design a method to extract coherent signals between different GRACE gravity field models and assess their sensitivity to the dealiasing ocean model. We present and discuss the results of these analyses applied to different sets of GRACE gravity models: the GRGS03, GRGS04 and CSR06 solutions, as well as their respective ocean dealiasing models. Beyond the case of the Tohoku earthquake, our approach can be applied to the systematic monitoring of the Pacific subduction belt, to detect gravity variations potentially linked with sudden changes in slab motions in-depth these plate boundaries.

References

Bedford, J. R., et al. (2020). Months-long thousand-kilometre-scale wobbling before great subduction earthquakes, Nature 580, 628-635.

Bouchon, M., et al.  (2016). Potential slab deformation and plunge prior to the Tohoku, Iquique and Maule earthquakes, Nature Geoscience 9, 380-383.

Panet, I., et al. (2018). Migrating pattern of deformation prior to the Tohoku-Oki earthquake revealed by GRACE data, Nature Geoscience 11, 367-373.

How to cite: Panet, I., Narteau, C., Lemoine, J.-M., Bonvalot, S., and Remy, D.: Robustness and singularity of pre-seismic signals in GRACE gravity solutions: application to the 2011 Tohoku Mw9.0 Earthquake, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5508, https://doi.org/10.5194/egusphere-egu22-5508, 2022.

The control on megathrust earthquake generation exerted by deeper subduction processes remains poorly understood and still insufficiently documented. Here, we use the 2003-2014 space-time variations of the Earth’s gravity gradients derived from the GRACE geoids in order to probe aseismic mass variations at depth and their possible interactions with intraplate seismicity along the Chilean margin. We work with three different datasets of GRACE geoid models over a large region surrounding the rupture zone of the Mw 8.8 2010 Maule earthquake. In order to separate signals associated with mass sources of differents sizes, shapes or orientations, we reconstruct each month the Earth’s gravity gradients at different spatial scales from these geoid models. Our analysis emphasizes a highly anomalous, large-amplitude gravity gradients signal that appears three months prior to the earthquake North of the epicentral zone, and progressively increases until the megathrustal rupture, in all three datasets. We show that this large signal cannot be caused by a shallow hydrological source nor by GRACE striping artefacts and dealiasing models. Instead, we conclude that its most likely origin is in mass redistributions within the solid Earth on the continental side of the subduction zone. These anomalous gravity gradient variations could be explained by a deep extensional deformation of the slab around 150-km depth along the Nazca Plate subduction direction, driving large-scale fluid motion in the subduction zone and into the overriding lithosphere. Our results highlight the importance of observations of the Earth’s time-varying gravity field from satellites to probe aseismic mass redistributions in-depth major plate boundaries . The detection of such mass redistributions at depth by GRACE and their interactions with interplate seismicity opens a new field of research to better characterize and understand the dynamics of the seismic cycle at megathrusts.

How to cite: Bouih, M., Panet, I., Remy, D., Longuevergne, L., and Bonvalot, S.: Deep mass redistribution prior to the Maule earthquake revealed by GRACE satellite gravity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3679, https://doi.org/10.5194/egusphere-egu22-3679, 2022.

In this contribution, we estimate the global mean mass sea-level (GMMSL) rise spanning January 1993 to December 2016 by using the Tongji-Grace2018 and Tongji-LEO2021 monthly gravity field solutions. In the post-processing, Tongji-Grace2018 and Tongji-Leo2021 solutions are filtered with P4M6 decorrelation plus Gauss 300km filtering, Tongji-Leo2021 solutions are filtered with Gaussian 1000km filtering, the C₂₀ and degree-1 coefficients are replaced with those from the GRACE technique note 13 and 14 for Tongji-Grace2018 solutions, and with those from satellite laser ranging for Tongji-LEO2021 solutions, the post-glacial isostatic adjustments are corrected with ICE6G-D model, and a 300km buffer zone is used due to leakage error. Moreover, the GMMSL is averaged with the open oceans within the latitude of ±66°, the Caspian Sea, Black Sea and the Mediterranean Sea are excluded. The derived GMMSL rise from Tongji-LEO2021 and Tongji-Grace2018 solutions is 1.67±0.08 mm/yr from 1993.01 to 2016.12, consistent with 1.73±0.08 mm/year from Altimetry minus Steric. When the same missing months as gravity field solutions are removed, the GMMSL rise from Altimetry minus Steric is 1.68±0.08 mm/yr from 1993.01 to 2016.12, much close to that from Tongji-LEO2021 and Tongji-Grace2018 solutions.

How to cite: Shen, Y., Chen, Q., Wang, F., Zhang, X., and Nie, Y.: Global Mean Mass Sea-Level Rise From 1993 to 2016 Derived by Tongji Monthly Gravity Field Solutions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1864, https://doi.org/10.5194/egusphere-egu22-1864, 2022.

GRACE mission data is used to derive variations in terrestrial water storage in order to evaluate approaches to the water balance. The data in the span of the GRACE and GRACE Follow-On missions is analyzed, and long-term behavior of a variety of basins is characterized. Terrestrial water storage variations are calculated via a combination of flux quantities from land surface models and atmospheric reanalyses using two common water balance approaches as well as a third approach using a novel algorithm for basin boundary discretization. Results are used to evaluate the new approach and form an understanding of its limitations, in relation to both the model data ingested as well as the characteristics of the regions in question.  From the results, we observe significant variations in model performance over diverse geography and climatic conditions, such as diminished accuracy in atmospheric reanalyses under the effect of long term drought. These observations suggest utility as a diagnostic to assess and inform improvement in the studied models.

How to cite: Krichman, B., Bettadpur, S., and Pekker, T.: Assessment of Land Surface and Atmospheric Model Mass Flux Using Water Balance Techniques and GRACE/GRACE-FO Data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13016, https://doi.org/10.5194/egusphere-egu22-13016, 2022.

Gravity gradient observations of GOCE (Gravity field and steady-state Ocean Circulation Explorer) provide important data support for the recovery of the short-wavelength part of the static gravity field, in which the influence of time-varying gravity signals should be reduced first. In this contribution, we carried out the following investigations on the static gravity field recovered from GOCE level 1b gravity gradient observations: (1) We updated the background models and according to the IERS2010 convention to remove the time-varying signals in the gravity gradient observations, and analyzed their influence on the subsequent static gravity field recovery; (2) We set up the 300 degrees and order(d/o) GOCE gravity gradient normal equations by the direct method with the reprocessed GOCE Level 1b gravity gradient observations; (3) In order to effectively treat the influence of polar gap, we combined the 300 d/o of the GOCE gravity gradient normal equation with 180 d/o Tongji-Grace02s normal equation and the Kaula’s regularization constraints; (4) GNSS/Leveling data, quasi-geoid model and DTU marine gravity anomaly are used to validate the accuracy of our combined solution, which shows that the accuracy of it is comparable to the state-of-art GOCO06s model.

How to cite: Chen, J., Zhang, X., Chen, Q., Shen, Y., and Nie, Y.: Static Gravity Field Recovery and Accuracy Analysis Based on Reprocessed GOCE Level 1b Gravity Gradient Observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6771, https://doi.org/10.5194/egusphere-egu22-6771, 2022.