Gravity field models from kinematic orbits of CHAMP, GRACE and GOCE satellites

Bezděk, Aleš; Sebera, Josef; Klokočník, Jaroslav; Kostelecký, Jan

doi:10.1016/j.asr.2013.11.031

Cited by 30 publications

(23 citation statements)

References 46 publications

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“…We estimated the drag coefficient of each satellite by means of the long-term change in the orbital elements in order to consider realistic values. Further details of our approach can be found in Bezděk (2010); Bezděk et al (2014Bezděk et al ( , 2016Bezděk et al ( , 2017.…”

Section: Non-gravitational Accelerationsmentioning

confidence: 99%

Multi-approach gravity field models from Swarm GPS data

Encarnação

Visser

Arnold

et al. 2019

Preprint

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Abstract. Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE and GOCE satellite missions, the geophysical community has identified the need for the continued monitoring of the time-variable component with the purpose of estimating the hydrological and glaciological yearly cycles and long-term trends. Currently, the GRACE-FO satellites are the sole dedicated provider of these data, while previously the GRACE mission fulfilled that role for 15 years. There is a data gap spanning from July 2017 to May 2018 between the end of the GRACE mission and start the of GRACE-FO, while the Swarm satellites have collected gravimetric data with their GPS receivers since December 2013. We present high-quality gravity field models from Swarm data that constitute an alternative and independent source of gravimetric data, which could help alleviate the consequences of the 10-month gap between GRACE and GRACE-FO, as well as the short gaps in the existing GRACE and GRACE-FO monthly time series. The geodetic community has realized that the combination of different gravity field solutions is superior to any individual model and set up a Combination Service of Time-variable Gravity Fields (COST-G) under the umbrella of the International Gravity Field Service (IGFS), part of the International Association of Geodesy (IAG). We exploit this fact and deliver to the highest quality monthly-independent gravity field models, resulting from the combination of four different gravity field estimation approaches. All solutions are unconstrained and estimated independently from month to month. We tested the added value of including Kinematic Baselines (KBs) in our estimation of Gravity Field Models (GFMs) and conclude that there is no significant improvement. The non-gravitational accelerations measured by the accelerometer on-board Swarm-C were also included in our processing to determine if this would improve the quality of the GFMs, but observed that is only the case when the amplitude of the non-gravitational accelerations is higher than during the current quiet period in solar activity. Using GRACE data for comparison, we demonstrate that the geophysical signal in the Swarm gravity field models is largely restricted to Spherical Harmonic degrees below 12. A 750 km smoothing radius is suitable to retrieve the temporal variations of Earth’s gravity field over land areas since mid-2015 with roughly 4 cm Equivalent Water Height (EWH) agreement with respect to a GRACE-derived parametric model. Over ocean areas, we illustrate that a more intense smoothing with 3000 km radius is necessary to resolve large scale gravity variations, which agree with the aforementioned parametric model under 2 cm EWH, while at these spatial scales the model represents variations with amplitudes between 2 and 3.5 cm EWH. The agreement with GRACE and GRACE-FO over nine selected large basins under analyses is 1.19 cm, 0.60 cm/year and 0.75 in terms of temporal mean, trend and correlation coefficient, respectively.

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Section: Non-gravitational Accelerationsmentioning

confidence: 99%

Multi-approach gravity field models from Swarm GPS data

Encarnação

Visser

Arnold

et al. 2019

Preprint

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“…Alternative data sets used in this study are models based on GRACE and Swarm satellite orbits, developed by ASU CAS [7,9], accessed from http://www.asu.cas.cz/~{}bezdek/vyzkum/geopotencial/ index.php.…”

Section: Gravity Field Models Obtained From Kinematic Orbits Of the Lmentioning

confidence: 99%

“…Surprisingly, these good results were not found for the Swarm ABC ITSG solutions. The reason for these differences may be the fact that both institutes used different approaches during computation of their gravity field models, namely the acceleration approach [7] for CAS solution and the short-arc approach [54] for ITSG solutions. The series computed from Jason 2, MetOp-A, and MetOp-B data revealed much higher STDs of χ 1 and χ 2 than reference data and other missions.…”

Section: Time Series and Trendsmentioning

confidence: 99%

Determining and Evaluating the Hydrological Signal in Polar Motion Excitation from Gravity Field Models Obtained from Kinematic Orbits of LEO Satellites

Śliwińska

Nastula

2019

Remote Sensing

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This study evaluates the gravity field solutions based on high-low satellite-to-satellite tracking (hl-SST) of low-Earth-orbit (LEO) satellites: GRACE, Swarm, TerraSAR-X, TanDEM-X, MetOp-A, MetOp-B, and Jason 2, by converting them into hydrological polar motion excitation functions (or hydrological angular momentum (HAM)). The resulting HAM series are compared with the residuals of observed polar motion excitation (geodetic residuals, GAO) derived from precise geodetic measurements, and the HAM obtained from the GRACE ITSG 2018 solution. The findings indicate a large impact of orbital altitude and inclination on the accuracy of derived HAM. The HAM series obtained from Swarm data are found to be the most consistent with GAO. Visible differences are found in HAM obtained from GRACE and Swarm orbits and provided by different processing centres. The main reasons for such differences are likely to be different processing approaches and background models. The findings of this study provide important information on alternative data sets that may be used to provide continuous polar motion excitation observations, of which the Swarm solution provided by the Astronomical Institute, Czech Academy of Sciences, is the most accurate. However, further analysis is needed to determine which processing algorithms are most appropriate to obtain the best correspondence with GAO.

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“…In case of combination of the first and second derivatives (the last row in Table 2), we can see the solution keeps the sensitivity of the former. Holmes and Featherstone (2002) using the acceleration approach (Bezděk et al 2012).…”

Section: Effect Of the Normal For Other Functionalsmentioning

confidence: 99%

Short guide to direct gravitational field modelling with Hotine’s equations

Sebera

Wagner

Bezděk

et al. 2012

J Geod

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This paper presents a unified approach to the least squares spherical harmonic analysis of the acceleration vector and Eötvös tensor (gravitational gradients) in an arbitrary orientation. The Jacobian matrices are based on Hotine's equations that hold in the Earth-fixed Cartesian frame and do not need any derivatives of the associated Legendre functions. The implementation was confirmed through closedloop tests in which the simulated input is inverted in the least square sense using the rotated Hotine's equations. The precision achieved is at the level of rounding error with RMS about 10 −12 −10 −14 m in terms of the height anomaly. The second validation of the linear model is done with help from the standard ellipsoidal correction for the gravity disturbance that can be computed with an analytic expression as well as with the rotated equations. Although the analytic expression for this correction is only of a limited accuracy at the submillimeter level, it was used for an independent validation. Finally, the equivalent of the ellipsoidal correction, called the effect of the normal, has been numerically obtained also for other gravitational functionals and some of their combinations. Most of the numerical investigations are provided up to spherical harmonic degree 70, with degree 80 for the computation time comparison using real GRACE data. The relevant Matlab source codes for the design matrices are provided.

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Gravity field models from kinematic orbits of CHAMP, GRACE and GOCE satellites

Cited by 30 publications

References 46 publications

Multi-approach gravity field models from Swarm GPS data

Multi-approach gravity field models from Swarm GPS data

Determining and Evaluating the Hydrological Signal in Polar Motion Excitation from Gravity Field Models Obtained from Kinematic Orbits of LEO Satellites

Short guide to direct gravitational field modelling with Hotine’s equations

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