Multiresolution wavelet analysis applied to GRACE range-rate residuals

For further improvements of gravity field mod- els based on Gravity Recovery and Climate Experiment (GRACE) observations, it is necessary to identify the error sources within the recovery process. Observation residuals obtained during the gravity field recovery contain most of the measurement and modeling errors and thus can be con- sidered a realization of actual errors. In this work, we investigate the ability of wavelets to help in identifying specific error sources in GRACE range-rate residuals. The multiresolution analysis (MRA) using discrete wavelet transform (DWT) is applied to decompose the resid- ual signal into different scales with corresponding frequency bands. Temporal, spatial, and orbit-related features of each scale are then extracted for further investigations. The wavelet analysis has proven to be a practical tool to find the main error contributors. Besides the previously known sources such as K-band ranging (KBR) system noise and systematic attitude variations, this method clearly shows effects which the classic spectral analysis is hardly able or unable to represent. These effects include long-term signa- tures due to satellite eclipse crossings and dominant ocean tide errors

COST-G: towards a new GRACE and GRACE-FO combination

The combination service for time-variable gravity fields (COST-G) provides the full time-series of monthly GRACE gravity fields: COST-G GRACE RL01, combined in reprocessing mode, and a steadily growing time-series of monthly GRACE-FO gravity fields: COST-G GRACE-FO RL01 OP, combined on an operational basis. Both time-series are currently considered for re-combination. In case of GRACE, new high-quality time-series from Chinese analysis centers are available for combination. In case of GRACE-FO, a revision of the weighting scheme, developed in the frame of the Horizon2020 project Global Gravity-based Groundwater Product (G3P), and the availability of reprocessed GRACE-FO time-series from AIUB, CSR, GFZ, and JPL, lead to a significant improvement of the combined gravity fields. We present the preliminary re-combined GRACE and GRACE-FO time-series and quantify the differences with respect to the COST-G RL01 series in terms of signal and noise content

The second release of COST-G GRACE-FO combined monthly gravity fields

The Combination Service for Time-variable Gravity fields (COST-G) provides monthly gravity fields of the GRACE, GRACE-FO and Swarm satellite missions, which are derived by combination of the individual time-series of the analysis centers around the world. The GRACE-FO combination has been operationalized and further developed in the frame of the Horizon 2020 project Global Gravity-based Groundwater Product (G3P). A significant reduction of noise could be achieved by the adaption of the weighting scheme, the inclusion of the new AIUB-GRACE-FO-RL02 time-series, which makes use of empirical noise modelling techniques, and the use of an alternative accelerometer transplant product, which improved the determination of the C30 gravity field coefficient, important for the derivation of ice mass change in polar regions. We present the new time-series of combined GRACE-FO monthly gravity fields and compare it in terms of signal and noise content to the original RL01 combination

A machine learning approach to recover GRACE-B accelerometer data

In gravimetry satellite missions GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (GRACE Follow-On), accelerometer measurements from both satellites are necessary for the gravity field recovery. The accelerometer provides accurate measurements of the non-gravitational forces acting on the spacecraft, such as atmospheric drag, solar radiation pressure and albedo. These measurements are required to separate any non-gravitational effect from the sought-after gravitational perturbations on the spacecraft motion. Therefore, the quality of accelerometer data, denoted as ACC products, significantly affects the quality of gravity field models. Near the end of the GRACE mission, due to the reduced battery capacity, the on-board accelerometer of the GRACE-B was turned off and its measurements were replaced by synthetic accelerometer data, called transplant data. The transplant data are generated by a series of adjustments to the GRACE-A ACC data. A similar approach was also employed for the GRACE-FO mission, when the GRACE-D ACC data degraded and were required to be replaced with synthetic data as well. Using the transplant data in both missions is one of the main challenges of providing high-quality gravity field models. We investigate the feasibility of Machine Learning (ML) algorithms for the recovery of GRACE-B ACC based on GRACE-A measurements and orbital data such as shadow factor and β angle. Taking advantage of ~14 years of GRACE-B measurements, this work aims to develop a model which can predict the missing accelerometer data under different orbital conditions. Two different architectures are implemented to forecast GRACE-B accelerometer data: Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM). The performance is evaluated using the Root Mean Square Error (RMSE) and by comparing the predicted data with the calibrated real data in the evaluated period. Furthermore, the ML-based ACC products will be compared to the transplant products and their impact on the gravity field will be discussed

Gravitational Changes of the Earth's Free Oscillation From Earthquakes: Theory and Feasibility Study Using GRACE InterSatellite Tracking

GRACE satellites have detected regionalscale preseismic, coseismic, and postseismic gravity changes associated with great earthquakes during the GRACE era (20022017). Earthquakes also excite globalscale transient gravity changes associated with free oscillations that may be discerned for a few days. In this study, we examine such global gravity changes due to Earth's free oscillations and quantify how they affect GRACE measurements. We employ the normal mode formalism to synthesize the global gravity changes after the 2004 Sumatra earthquake and simulate the (gravitational) free oscillation signals manifested in the GRACE Kband ranging (KBR) measurements. Using the Kaula orbit perturbation theory, we show how GRACE intersatellite distances are perturbed through a complex coupling of eigenfrequencies of the normal modes with the Earth's rotation rate and the GRACE satellites' orbital frequency. It is found that a few gravest normal modes can generate rangerate perturbations as large as 0.2 m/s, which are comparable to actual errors of GRACE KBR ranging and accelerometer instruments. Wavelet timefrequency analysis of the GRACE KBR residual data in December 2004 reveals the existence of a significant transient signal after the 2004 Sumatra earthquake. This transient signal is characterized by a frequency of ~0.022 mHz that could be potentially associated with the largest excitation due to the football mode of the Earth's free oscillation. However, the results are also affected by lowfrequency noise of the GRACE accelerometers. Improved spaceborne gravitational instrumentation may open new opportunities to study the Earth's interior and earthquakes independently from global seismological analysis

Consolidated and validated monthly gravity field combinations of the GRACE, Swarm and GRACE-FO satellite missions

The satellite missions GRACE and GRACE-FO, dedicated to the observation of the time-variable Earth gravity field, provide invaluable insight into continental total water storage, continental ice mass change and ocean mass change at spatial scales of 200-400 km and monthly time-resolution, covering the time-period 2002 to present. The Combination Service for Time-Variable Gravity Fields (COST-G) of the International Association of Geodesy (IAG) collects the monthly gravity fields of its associated or partner Analysis Centers (ACs) and performs a weighted combination to provide a consolidated time-series of monthly gravity fields at Level-2 (spherical harmonic coefficients) and user-friendly Level-3 (post-processed global grids) products. Gaps in the GRACE or GRACE-FO time-series may be bridged by monthly gravity fields derived from orbits of the Swarm satellites, dedicated to the observation of the Earth magnetic field, at the cost of significantly reduced spatial resolution. COST-G performs quality control and harmonization of the contributing GRACE, GRACE-FO or Swarm time-series. The combined gravity fields undergo consistency checks and internal validation by the COST-G validation centers at GFZ and GRGS. An independent board of experts in hydrological, oceanic and cryosphere applications irregularly performs external validations. A combined re-processed GRACE time-series COST-G GRACE RL01 is available at the International Center for Global Earth Models ICGEM (L2-products) or the Gravity Information Service GRAVIS (L3-products), both operated by GFZ. The operational GRACE-FO time-series is updated regularly with a latency of less than 3 months, Swarm gravity fields are operationally combined in a quarterly processing scheme