GOCE Long-Wavelength Gravity Field Recovery from 1s-Sampled Kinematic Orbits Using the Acceleration Approach

Abstract. In the course of the GOCE satellite mission, the high-low Satellite to Satellite Tracking (SST) observations have to be processed for the determination of the long wavelength part of the Earth’s gravity field. This paper deals with the formulation of the high-low SST observation equations, as well as the methods for gravity field recovery from orbit information. For this purpose, two approaches, i.e. the numerical integration of orbit perturbations, and the evaluation of the energy equation based on the Jacobi integral, are presented and discussed. Special concern is given to the numerical properties of the corresponding normal equations. In a closed-loop simulation, which is based on a realistic orbit GOCE configuration, these methods are compared and assessed. However, here we process a simplified case assuming that non-conservative forces can be perfectly modelled. Assuming presently achievable accuracies of the Precise Orbit Determination (POD), it turns out that the numerical integration approach is still superior, but the energy integral approach may be an interesting alternative processing strategy in the near future.Key words. High-low SST – gravity field – GOCE – variational equations – least squares adjustment

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Long-wavelength lunar gravity field recovery from simulated orbit and inter-satellite tracking data

Advances in Space Research ◽

10.1016/j.asr.2013.08.008 ◽

2013 ◽

Vol 52 (11) ◽

pp. 1919-1928 ◽

Cited By ~ 1

Author(s):

Jianguo Yan ◽

Oliver Baur ◽

Li Fei ◽

Ping Jinsong

Keyword(s):

Gravity Field ◽

Satellite Tracking ◽

Tracking Data ◽

Lunar Gravity ◽

Long Wavelength ◽

Lunar Gravity Field ◽

Gravity Field Recovery

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Earth’s Time-Variable Gravity from GRACE Follow-On K-Band Range-Rates and Pseudo-Observed Orbits

Remote Sensing ◽

10.3390/rs13091766 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1766

Author(s):

Igor Koch ◽

Mathias Duwe ◽

Jakob Flury ◽

Akbar Shabanloui

Keyword(s):

Gravity Field ◽

Time Variable ◽

Time Variable Gravity ◽

Gravity Field Recovery ◽

Variable Gravity ◽

Earth’S System ◽

Grace Mission ◽

Insight Into ◽

K Band

During its science phase from 2002–2017, the low-low satellite-to-satellite tracking mission Gravity Field Recovery And Climate Experiment (GRACE) provided an insight into Earth’s time-variable gravity (TVG). The unprecedented quality of gravity field solutions from GRACE sensor data improved the understanding of mass changes in Earth’s system considerably. Monthly gravity field solutions as the main products of the GRACE mission, published by several analysis centers (ACs) from Europe, USA and China, became indispensable products for quantifying terrestrial water storage, ice sheet mass balance and sea level change. The successor mission GRACE Follow-On (GRACE-FO) was launched in May 2018 and proceeds observing Earth’s TVG. The Institute of Geodesy (IfE) at Leibniz University Hannover (LUH) is one of the most recent ACs. The purpose of this article is to give a detailed insight into the gravity field recovery processing strategy applied at LUH; to compare the obtained gravity field results to the gravity field solutions of other established ACs; and to compare the GRACE-FO performance to that of the preceding GRACE mission in terms of post-fit residuals. We use the in-house-developed MATLAB-based GRACE-SIGMA software to compute unconstrained solutions based on the generalized orbit determination of 3 h arcs. K-band range-rates (KBRR) and kinematic orbits are used as (pseudo)-observations. A comparison of the obtained solutions to the results of the GRACE-FO Science Data System (SDS) and Combination Service for Time-variable Gravity Fields (COST-G) ACs, reveals a competitive quality of our solutions. While the spectral and spatial noise levels slightly differ, the signal content of the solutions is similar among all ACs. The carried out comparison of GRACE and GRACE-FO KBRR post-fit residuals highlights an improvement of the GRACE-FO K-band ranging system performance. The overall amplitude of GRACE-FO post-fit residuals is about three times smaller, compared to GRACE. GRACE-FO post-fit residuals show less systematics, compared to GRACE. Nevertheless, the power spectral density of GRACE-FO and GRACE post-fit residuals is dominated by similar spikes located at multiples of the orbital and daily frequencies. To our knowledge, the detailed origin of these spikes and their influence on the gravity field recovery quality were not addressed in any study so far and therefore deserve further attention in the future. Presented results are based on 29 monthly gravity field solutions from June 2018 until December 2020. The regularly updated LUH-GRACE-FO-2020 time series of monthly gravity field solutions can be found on the website of the International Centre for Global Earth Models (ICGEM) and in LUH’s research data repository. These operationally published products complement the time series of the already established ACs and allow for a continuous and independent assessment of mass changes in Earth’s system.

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GRACETOOLS—GRACE Gravity Field Recovery Tools

Geosciences ◽

10.3390/geosciences8090350 ◽

2018 ◽

Vol 8 (9) ◽

pp. 350 ◽

Cited By ~ 1

Author(s):

Neda Darbeheshti ◽

Florian Wöske ◽

Matthias Weigelt ◽

Christopher Mccullough ◽

Hu Wu

Keyword(s):

Open Source ◽

Gravity Field ◽

Transition Matrix ◽

State Transition ◽

Satellite Observations ◽

Gravity Field Recovery ◽

Grace Data ◽

Range Rate ◽

Analysis Platform ◽

Recovery Tools

This paper introduces GRACETOOLS, the first open source gravity field recovery tool using GRACE type satellite observations. Our aim is to initiate an open source GRACE data analysis platform, where the existing algorithms and codes for working with GRACE data are shared and improved. We describe the first release of GRACETOOLS that includes solving variational equations for gravity field recovery using GRACE range rate observations. All mathematical models are presented in a matrix format, with emphasis on state transition matrix, followed by details of the batch least squares algorithm. At the end, we demonstrate how GRACETOOLS works with simulated GRACE type observations. The first release of GRACETOOLS consist of all MATLAB M-files and is publicly available at Supplementary Materials.

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Combining the deep Earth and lithospheric gravity field to study the density structure of the upper mantle

10.5194/egusphere-egu21-2950 ◽

2021 ◽

Author(s):

Bart Root ◽

Javier Fullea ◽

Jörg Ebbing ◽

Zdenek Martinec

Keyword(s):

Gravity Field ◽

Shear Wave ◽

Wave Velocity ◽

Shear Wave Velocity ◽

Field Data ◽

Wavelength Region ◽

Density Structure ◽

Long Wavelength ◽

Global Gravity ◽

Deep Earth

Global gravity field data obtained by dedicated satellite missions is used to study the density distribution of the lithosphere. Different multi-data joint inversions are using this dataset together with other geophysical data to determine the physical characteristics of the lithosphere. The gravitational signal from the deep Earth is usually removed by high-pass filtering of the model and data, or by appropriately selecting insensitive gravity components in the inversion. However, this will remove any long-wavelength signal inherent to lithosphere. A clear choice on the best-suited approach to remove the sub-lithospheric gravity signal is missing.&#160;Another alternative is to forward model the gravitational signal of these deep situated mass anomalies and subtract it from the observed data, before the inversion. Global tomography provides shear-wave velocity distribution of the mantle, which can be transformed into density anomalies. There are difficulties in constructing a density model from this data. Tomography relies on regularisation which smoothens the image of the mantle anomalies. Also, the shear-wave anomalies need to be converted to density anomalies, with uncertain conversion factors related to temperature and composition. Understanding the sensitivity of these effects could help determining the interaction of the deep Earth and the lithosphere.In our study the density anomalies of the mantle, as well as the effect of CMB undulations, are forward modelled into their gravitational potential field, such that they can be subtracted from gravity observations. The reduction in magnitude of the density anomalies due to the regularisation of the global tomography models is taken into account. The long-wavelength region of the density estimates is less affected by the regularisation and can be used to fix the mean conversion factor to transform shear wave velocity to density. We present different modelling approaches to add the remaining dynamic topography effect in lithosphere models. This results in new solutions of the density structure of the lithosphere that both explain seismic observations and gravimetric measurements. The introduction of these dynamic forces is a step forward in understanding how to properly use global gravity field data in joint inversions of lithosphere models.

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GRACE Follow-On Gravity Field Recovery from Combined Laser Ranging Interferometer and Microwave Ranging System Measurements

10.5194/egusphere-egu21-9415 ◽

2021 ◽

Author(s):

Saniya Behzadpour ◽

Andreas Kvas ◽

Torsten Mayer-Gürr

Keyword(s):

Gravity Field ◽

Laser Ranging ◽

Measurement Technology ◽

Additional Measurement ◽

Covariance Functions ◽

Gravity Field Recovery ◽

Global Gravity ◽

Least Squares Adjustment ◽

Noise Covariance ◽

Component Estimation

Besides a K-Band Ranging System (KBR), GRACE-FO carries a Laser Ranging Interferometer (LRI) as a technology demonstration to provide measurements of inter-satellite range changes. This additional measurement technology provides supplementary observations, which allow for cross-instrument diagnostics with the KBR system and, to some extent, the separation of ranging noise from other sources such as noise in the on-board accelerometer (ACC) measurements.The aim of this study is to incorporate the two ranging systems (LRI and KBR) observations in ITSG-Grace2018 gravity field recovery. The two observation groups are combined in an iterative least-squares adjustment with variance component estimation used to determine the unknown noise covariance functions for KBR, LRI, and ACC measurements. We further compare the gravity field solutions obtained from the combined solutions to KBR-only results and discuss the differences with a focus on the global gravity field and LRI calibration parameters.

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