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

European Gravity Service for Improved Emergency Management - Status and project highlights

European Gravity Service for Improved Emergency Management - Status and project highlight

European Gravity Service for Improved Emergency Management - Status and project highlights

European Gravity Service for Improved Emergency Management - Status and project highlight

Regularization of the Gravity Field Inversion Process with High-Dimensional Vector Autoregressive Models

Earth’s gravitational field provides invaluable insights into the changing nature of our planet. It reflects mass change caused by geophysical processes like continental hydrology, changes in the cryosphere or mass flux in the ocean. Satellite missions such as the NASA/DLR operated Gravity Recovery and Climate Experiment (GRACE), and its successor GRACE Follow-On (GRACE-FO) continuously monitor these temporal variations of the gravitational attraction. In contrast to other satellite remote sensing datasets, gravity field recovery is based on geophysical inversion which requires a global, homogeneous data coverage. GRACE and GRACE-FO typically reach this global coverage after about 30 days, so short-lived events such as floods, which occur on time frames from hours to weeks, require additional information to be properly resolved. In this contribution we treat Earth’s gravitational field as a stationary random process and model its spatio-temporal correlations in the form of a vector autoregressive (VAR) model. The satellite measurements are combined with this prior information in a Kalman smoother framework to regularize the inversion process, which allows us to estimate daily, global gravity field snapshots. To derive the prior, we analyze geophysical model output which reflects the expected signal content and temporal evolution of the estimated gravity field solutions. The main challenges here are the high dimensionality of the process, with a state vector size in the order of 103 to 104, and the limited amount of model output from which to estimate such a high-dimensional VAR model. We introduce geophysically motivated constraints in the VAR model estimation process to ensure a positive-definite covariance function

GRACE monthly solutions for evaluation of background

These time series are supplementary material to the paper Kvas and Mayer-Gürr: GRACE gravity field recovery with background model uncertainties

Combination Service for Time-variable Gravity Fields (COST-G) — operations

With the release of the combined GRACE monthly gravity field time-series COST-G RL01 the Combination Service for Time-variable Gravity fields (COST-G) of the International Association of Geodesy (IAG) became operational in July 2019. We present the COST-G RL01 time-series and provide validation in terms of orbit fit, ice mass trends, lake altimetry and sea level budget. We identify weak points in the combined monthly gravity fields and discuss possible improvements of the combination strategy for future combinations. While COST-G RL01 is based on sets of re-processed GRACE monthly gravity fields, COST-G also provides combinations of monthly Swarm high-low satellite-to-satellite tracking (hl-SST) gravity fields on an operational basis with a latency of 3 months. Combinations of GRACE-FO monthly gravity fields are in the process of operationalization. We provide a status report and first results of GRACE-FO combinations. Combined GRACE, Swarm and GRACE-FO gravity fields complement each other to provide a long-term time-series of mass variation in the system Earth

GOCO06s — a satellite-only global gravity field model.

GOCO06s is the latest satellite-only global gravity field model computed by the GOCO (Gravity Observation Combination) project. It is based on over a billion observations acquired over 15 years from 19 satellites with different complementary observation principles. This combination of different measurement techniques is key in providing consistently high accuracy and best possible spatial resolution of the Earth's gravity field. The motivation for the new release was the availability of reprocessed observation data for the Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE), updated background models, and substantial improvements in the processing chains of the individual contributions. Due to the long observation period, the model consists not only of a static gravity field, but comprises additionally modeled temporal variations. These are represented by time-variable spherical harmonic coefficients, using a deterministic model for a regularized trend and annual oscillation. The main focus within the GOCO combination process is on the proper handling of the stochastic behavior of the input data. Appropriate noise modeling for the observations used results in realistic accuracy information for the derived gravity field solution. This accuracy information, represented by the full variance–covariance matrix, is extremely useful for further combination with, for example, terrestrial gravity data and is published together with the solution. The primary model data consisting of potential coefficients representing Earth's static gravity field, together with secular and annual variations, are available on the International Centre for Global Earth Models (http://icgem.gfz-potsdam.de/, last access: 11 June 2020). This data set is identified with the following DOI: https://doi.org/10.5880/ICGEM.2019.002 (Kvas et al., 2019b). Supplementary material consisting of the full variance–covariance matrix of the static potential coefficients and estimated co-seismic mass changes is available at https://ifg.tugraz.at/GOCO (last access: 11 June 2020)

Combination Service for Time-variable Gravity Fields (COST-G) — GRACE-FO operational combination

We present the operational GRACE-FO combined time-series of monthly gravity fields of the Combination Service for Time-variable Gravity fields (COST-G) of the International Association of Geodesy (IAG). COST-GGRACE-FORL01operational is combined at AIUB and relies on operational monthly solutions of the COST-G Analysis Centers GFZ, GRGS, IfG, LUH and AIUB and the associated Analysis Centers CSR and JPL. All COST-G Analysis Centers have passed a benchmark test to ensure consistency between the different processing approaches and all of the contributing time-series undergo a strict quality control focusing on the signal content in river basins and polar regions with pronounced changes in ice mass to uncover any regularization that may bias the combination. The combination is performed by variance component estimation on the solution level, the relative monthly weights thus providing valuable and independent insight into the consistency and noise levels of the individual monthly contributions. The combined products then are validated internally in terms of noise, approximated by the non-secular, non-seasonal variability over the oceans. Once they have passed this quality control the combined gravity fields are assessed by an external board of experts who evaluate them in terms of orbit predictions, lake altimetry, river hydrology or oceanography

An improved global gravity field model of the Earth derived from reprocessed GOCE observations with the time-wise approach

ESA's dedicated gravity field mission GOCE (Gravity field and steady-state Ocean Circulation Explorer) successfully completed its science operations in 2013 as the first Earth Explorer mission in orbit. In 2014, the fifth releases of GOCE based global gravity field models of the Earth were published. Already at that time, the entire mission data set was used. Until now, the release 5 models are the highest resolution models of the static Earth's gravity field derived by satellites. On the one hand, high-low satellite-to-satellite tracking observations of GOCE by GPS satellites is used to derive the long wavelength part of the gravity field. On the other hand, observations of the core instrument - a gravitational gradiometer - are sensitive to the medium and short wavelengths of the Earth gravity field. Combining both observation groups provides a global model of the gravity field with a spatial resolution of about 70 km. Recent studies have shown that the quality of the derived level 1B gravity gradients can be significantly improved, if a quadratic term is additionally considered in the calibration procedure. Consequently, ESA funded a reprocessing campaign by the High-level Processing Facility (HPF). Within that framework, global gravity field models are estimated and provided as higher level GOCE products. One approach which can be used for the processing of the GOCE observations is the so called time-wise approach. Within this approach, only GOCE observations are used to estimate the gravity field model in a least-squares sense. The highly correlated gravity gradients in the gradiometer reference frame are used to derive normal equations in terms of global spherical harmonics. A lot of effort is spend on the stochastic modeling of the noise characteristics of the gravity gradients, to deliver in addition to the high quality gravity field a meaningful covariance matrix. The gradiometry normal equations are combined with normal equations determined from high-low satellite to satellite tracking to better capture the long wavelength of the gravity field. Within this contribution, the release six of the official ESA time-wise model is presented. An improved time-wise processing is used, to estimate the new EGM_RIM_RL06 model form the reprocessed GOCE observations. An advanced detection of suspicious data is implemented and used in the estimation of decorrelation filters as well as for gravity field recovery. These decorrelation filters serve as a stochastic model for the gravity gradients in the least squares estimation of the spherical harmonic coefficients which represent the gravity field. Within this contribution, the processing used to derive the new release is summarized. The improvements with respect to the former 5th release are highlighted. The characteristics and the quality level of the new solution is discussed. Finally the model is validated with comparisons to independent data sets. As an outlook, the combination with GRACE models towards a combined GOCO06S is shown

International Combination Service for Time-Variable Gravity Fields (COST-G) : Start of Operational Phase and Future Perspectives

The International Combination Service for Time-variable Gravity Fields (COST-G) is a new Product Center of IAG’s International Gravity Field Service (IGFS). COST-G provides consolidated monthly global gravity fields in terms of spherical harmonic coefficients and thereof derived grids of surface mass changes by combining existing solutions or normal equations from COST-G analysis centers (ACs) and partner analysis centers (PCs). The COST-G ACs adopt different analysis methods but apply agreed-upon consistent processing standards to deliver time-variable gravity field models, e.g. from GRACE/GRACE-FO low-low satellite-to-satellite tracking (ll-SST), GPS high-low satellite-to-satellite tracking (hl-SST) and Satellite Laser Ranging (SLR). The organizational structure of COST-G and results from the first release of combined monthly GRACE solutions covering the entire GRACE time period are discussed in this article. It is shown that by combining solutions and normal equations from different sources COST-G is taking advantage of the statistical properties of the various solutions, which results in a reduced noise level compared to the individual input solutions