GOCE gradiometer data calibration

Siemes, Christian; Schlicht, Anja; Haagmans, Roger

doi:10.1007/s00190-019-01271-9

Cited by 16 publications

(19 citation statements)

References 28 publications

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“…These EGG_NOM_1B data are provided by the European Space Agency (ESA) and can be accessed via the link https: //goce-ds.eo.esa.int/oads/access/collection/GOCE_Level_1/tree. We use the gradient data that have been reprocessed according to the work in [18], which can be identified by the file name ending _0202. As can be seen in Figure 2b, the measurement noise in these gradient data is colored, which needs to be considered in the gravity field modeling by an appropriate frequency-dependent weighting.…”

Section: Real Goce Satellite Gravitational Gradiometry Datamentioning

confidence: 99%

“…According to the authors of [17], this perturbation can be removed by introducing a quadratic function of the non-gravitational acceleration in y direction in the conversion from the control voltage measured by the electrostatic gradiometer to the derived acceleration. A detailed description of the improved SGG data calibration method that has been applied in the SGG data reprocessing in 2018/2019 is given by [18]. Figure 2 visualizes the improvements of the spectral properties of the measurement noise included in the V yy component of the GOCE SGG data due to the reprocessing (we only present the noise spectra of the V yy component here, as it shows the strongest improvements among the gradient components).…”

Section: Introductionmentioning

confidence: 99%

“…As time-variable gravity signals have their largest amplitudes in the long-wavelength range, due to the reprocessing, an improved ability of GOCE SGG data to resolve these signals can be anticipated. According to the work in [18], a reduction of noise is especially expected in the northern polar area, which increases the possibility to detect the ice melting trends over Greenland in the reprocessed SGG data. Amplitude spectral density (ASD) of the residuals ∆V yy of the GOCE SGG data before (a) and after (b) the reprocessing according to the work in [18].…”

Section: Introductionmentioning

confidence: 99%

“…According to the work in [18], a reduction of noise is especially expected in the northern polar area, which increases the possibility to detect the ice melting trends over Greenland in the reprocessed SGG data. Amplitude spectral density (ASD) of the residuals ∆V yy of the GOCE SGG data before (a) and after (b) the reprocessing according to the work in [18]. The residuals are computed with respect to the GOCO03s model [19].…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, the GOCE SGG data processed according to the work in [18] are analyzed regarding temporal gravity signals for the first time. The subsequent questions we address in our study both pursue the goals to verify the conclusions given in previous studies that are based on GOCE SGG data prior to the reprocessing in 2018/2019, as well as to investigate the new possibilities due to the reduced noise contained in the reprocessed gradient data:…”

Section: Introductionmentioning

confidence: 99%

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Temporal Gravity Signals in Reprocessed GOCE Gravitational Gradients

et al. 2020

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The reprocessing of the satellite gravitational gradiometry (SGG) data from the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite mission in 2018/2019 considerably reduced the low-frequency noise in the data, leading to reduced noise amplitudes in derived gravity field models at large spatial scales, at which temporal variations of the Earth’s gravity field have their highest amplitudes. This is the motivation to test the reprocessed GOCE SGG data for their ability to resolve time-variable gravity signals. For the gravity field processing, we apply and compare a spherical harmonics (SH) approach and a mass concentration (mascon) approach. Although their global signal-to-noise ratio is <1, SH GOCE SGG-only models resolve the strong regional signals of glacier melting in Greenland and Antarctica, and the 2011 moment magnitude 9.0 earthquake in Japan, providing an estimation of gravity variations independent of Gravity Recovery and Climate Experiment (GRACE) data. The benefit of combined GRACE/GOCE SGG models is evaluated based on the ice mass trend signals in Greenland and Antarctica. While no signal contribution from GOCE SGG data additional to the GRACE models could be observed, we show that the incorporation of GOCE SGG data numerically stabilizes the related normal equation systems.

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Section: Real Goce Satellite Gravitational Gradiometry Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Temporal Gravity Signals in Reprocessed GOCE Gravitational Gradients

et al. 2020

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Reprocessed precise science orbits and gravity field recovery for the entire GOCE mission

Arnold

Grombein

Schreiter

et al. 2023

J Geod

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ESA’s Gravity field and steady-state Ocean Circulation Explorer (GOCE) orbited the Earth between 2009 and 2013 for the determination of the static part of Earth’s gravity field. The GPS-derived precise science orbits (PSOs) were operationally generated by the Astronomical Institute of the University of Bern (AIUB). Due to a significantly improved understanding of remaining artifacts after the end of the GOCE mission (especially in the GOCE gradiometry data), ESA initiated a reprocessing of the entire GOCE Level 1b data in 2018. In this framework, AIUB was commissioned to recompute the GOCE reduced-dynamic and kinematic PSOs. In this paper, we report on the employed precise orbit determination methods, with a focus on measures undertaken to mitigate ionosphere-induced artifacts in the kinematic orbits and thereof derived gravity field models. With respect to the PSOs computed during the operational phase of GOCE, the reprocessed PSOs show in average a 8–9% better consistency with GPS data, 31% smaller 3-dimensional reduced-dynamic orbit overlaps, an 8% better 3-dimensional consistency between reduced-dynamic and kinematic orbits, and a 3–7% reduction of satellite laser ranging residuals. In the second part of the paper, we present results from GPS-based gravity field determinations that highlight the strong benefit of the GOCE reprocessed kinematic PSOs. Due to the applied data weighting strategy, a substantially improved quality of gravity field coefficients between degree 10 and 40 is achieved, corresponding to a remarkable reduction of ionosphere-induced artifacts along the geomagnetic equator. For a static gravity field solution covering the entire mission period, geoid height differences with respect to a superior inter-satellite ranging solution are markedly reduced (43% in terms of global RMS, compared to previous GOCE GPS-based gravity fields). Furthermore, we demonstrate that the reprocessed GOCE PSOs allow to recover long-wavelength time-variable gravity field signals (up to degree 10), comparable to information derived from GPS data of dedicated satellite missions. To this end, it is essential to take into account the GOCE common-mode accelerometer data in the gravity field recovery.

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An Improved Model of the Earth’s Static Gravity Field Solely Derived from Reprocessed GOCE Data

2021

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After it was found that the gravity gradients observed by the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite could be significantly improved by an advanced calibration, a reprocessing project for the entire mission data set was initiated by ESA and performed by the GOCE High-level processing facility (GOCE HPF). One part of the activity was delivering the gravity field solutions, where the improved level 1b and level 2 data serve as an input for global gravity field recovery. One well-established approach for the analysis of GOCE observations is the so-called time-wise approach. Basic characteristics of the GOCE time-wise solutions is that only GOCE observations are included to remain independent of any other gravity field observables and that emphasis is put on the stochastic modeling of the observations’ uncertainties. As a consequence, the time-wise solutions provide a GOCE-only model and a realistic uncertainty description of the model in terms of the full covariance matrix of the model coefficients. Within this contribution, we review the GOCE time-wise approach and discuss the impact of the improved data and modeling applied in the computation of the new GO_CONS_EGM_TIM_RL06 solution. The model reflects the Earth’s static gravity field as observed by the GOCE satellite during its operation. As nearly all global gravity field models, it is represented as a spherical harmonic expansion, with maximum degree 300. The characteristics of the model and the contributing data are presented, and the internal consistency is demonstrated. The updated solution nicely meets the official GOCE mission requirements with a global mean accuracy of about 2 cm in terms of geoid height and 0.6 mGal in terms of gravity anomalies at ESA’s target spatial resolution of 100 km. Compared to its RL05 predecessor, three kinds of improvements are shown, i.e., (1) the mean global accuracy increases by 10–25%, (2) a more realistic uncertainty description and (3) a local reduction of systematic errors in the order of centimeters.

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GOCE gradiometer data calibration

Cited by 16 publications

References 28 publications

Temporal Gravity Signals in Reprocessed GOCE Gravitational Gradients

Temporal Gravity Signals in Reprocessed GOCE Gravitational Gradients

Reprocessed precise science orbits and gravity field recovery for the entire GOCE mission

An Improved Model of the Earth’s Static Gravity Field Solely Derived from Reprocessed GOCE Data

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