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The main objective of the GOCO ("Gravity Observation Combination") project is to compute high-accuracy and high-resolution static global gravity field models based on data of the dedicated satellite gravity missions CHAMP, GRACE, and GOCE, SLR data, and kinematic orbits from different Low Earth Orbiters. In this contribution we present the latest release GOCO06s. The motivation for this new release lies in various improvements within the processing chain as well as the availability of reprocessed observation data for GRACE and GOCE and updated background models. The main focus in the GOCO combination process is on the proper handling of the stochastic behaviour of the data. Therefore, the resulting accuracy information in terms of a full variance covariance matrix is quite realistic and also published with the solution. GOCO06s consists not only of a static gravity field, but the temporal variations are modelled as well. These are represented as regularized trend and annual signal. [ABSTRACT FROM AUTHOR]

In both GRACE (Gravity Recovery and Climate Experiment) and GFO (GRACE Follow-On) missions, the twin satellites are equipped with three-axis accelerometers, measuring the non-gravitational forces. Close to the end of the GRACE mission, the accelerometer onboard GRACE-B was switched off due to the reduced battery capacity and its measurements were replaced by synthetic accelerometer data, the so-called transplanted data. The transplanted data was derived from the GRACE-A accelerometer measurements, by applying time and attitude correction. Furthermore, the residual linear accelerations due to thruster firings on GRACE-B were added, proven to improve the data quality in gravity field recovery. Coincidentally, after one month in orbit, the GFO-B accelerometer data also degraded which raise demand for synthetic data in the current mission as well.In this work, we will present an approach to recover the transplanted data by (a) implementing the state-of-the-art non-gravitational force models and (b) applying additional corrections based on extracted features of the available measurement signals in a machine learning approach. The results will be validated with the GRACE Level-1b (RL03) accelerometer data transplant. [ABSTRACT FROM AUTHOR]

The satellite missions GRACE and GRACE Follow-On have undoubtedly been the most important sources to observe mass transport on global scales. Within the Combination Service for Time-Variable Gravity Fields (COST-G), gravity field solutions from various processing centers are being combined to improve the signal-to-noise ratio and further increase the spatial resolution. The time series of monthly gravity field solutions suffer from a data gap of about one year between the two missions GRACE and GRACE Follow-On among several smaller data gaps. We present an intermediate technique bridging the gap between the two missions allowing (1) for a continued and uninterrupted time series of mass observations and (2) to compare, cross-validate and link the two time series. We focus on the combination of high-low satellite-to-satellite tracking (HL-SST) of low-Earth orbiting satellites by GPS in combination with satellite laser ranging (SLR), where SLR contributes to the very low degrees and HL-SST is able to provide the higher spatial resolution at an lower overall precision compared to GRACE-like solutions. We present a complete series covering the period from 2003 to 2022 filling the gaps of GRACE and between the missions. The achieved spatial resolution is approximately 700 km at a monthly temporal resolutions throughout the time period of interest. For the purpose of demonstrating possible applications, we estimate the low degree glacial isostatic adjustment signal in Fennoscandia and North America. In both cases, the location, the signal strength and extend of the signal coincide well with GRACE/GRACE-FO solutions achieving 99.5% and 86.5% correlation, respectively., (© The Author(s) 2024.)

Changes in terrestrial water storage as observed by the satellite gravity mission GRACE (Gravity Recovery and Climate Experiment) represent a new and completely independent way to constrain the net flux imbalance in atmospheric reanalyses. In this study daily GRACE gravity field changes are used for the first time to investigate high-frequency hydro-meteorological fluxes over the continents. Band-pass filtered water fluxes are derived from GRACE water storage time series by first applying a numerical differentiation filter and subsequent high-pass filtering to isolate fluxes at periods between 5 and 30 days corresponding to typical time-scales of weather system persistence at moderate latitudes. By comparison with the latest atmospheric reanalysis ERA5 of the European Centre for Medium-Range Weather Forecasts (ECWMF) we show that daily GRACE gravity field models contain realistic high-frequency water flux information. Furthermore, GRACE-derived water fluxes can clearly identify improvements realized within ERA5 over its direct predecessor ERA-Interim particularly in equatorial and temperate climate zones. The documented improvements are in good agreement with rain gauge validation, but GRACE also identifies three distinct regions (Sahel Zone, Okavango Catchment, Kimberley Plateau) with a slight degradation of net-fluxes in ERA5 with respect to ERA-Interim, thereby highlighting the potentially added value of non-standard daily GRACE gravity series for hydro-meteorological monitoring purposes.