Satellite gravimetry and applications of temporal changes of gravity field

AbstractSince Kepler, Newton and Huygens in the seventeenth century, geodesy has been concerned with determining the figure, orientation and gravitational field of the Earth. With the beginning of the space age in 1957, a new branch of geodesy was created, satellite geodesy. Only with satellites did geodesy become truly global. Oceans were no longer obstacles and the Earth as a whole could be observed and measured in consistent series of measurements. Of particular interest is the determination of the spatial structures and finally the temporal changes of the Earth's gravitational field. The knowledge of the gravitational field represents the natural bridge to the study of the physics of the Earth's interior, the circulation of our oceans and, more recently, the climate. Today, key findings on climate change are derived from the temporal changes in the gravitational field: on ice mass loss in Greenland and Antarctica, sea level rise and generally on changes in the global water cycle. This has only become possible with dedicated gravity satellite missions opening a method known as satellite gravimetry. In the first forty years of space age, satellite gravimetry was based on the analysis of the orbital motion of satellites. Due to the uneven distribution of observatories over the globe, the initially inaccurate measuring methods and the inadequacies of the evaluation models, the reconstruction of global models of the Earth's gravitational field was a great challenge. The transition from passive satellites for gravity field determination to satellites equipped with special sensor technology, which was initiated in the last decade of the twentieth century, brought decisive progress. In the chronological sequence of the launch of such new satellites, the history, mission objectives and measuring principles of the missions CHAMP, GRACE and GOCE flown since 2000 are outlined and essential scientific results of the individual missions are highlighted. The special features of the GRACE Follow-On Mission, which was launched in 2018, and the plans for a next generation of gravity field missions are also discussed.

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The research unit NEROGRAV: first results on stochastic modeling for gravity field determination with real GRACE and GRACE-FO data

10.5194/gstm2020-65 ◽

2020 ◽

Author(s):

Natalia Panafidina ◽

Michael Murböck ◽

Christoph Dahle ◽

Karl Hans Neumayer ◽

Frank Flechtner ◽

...

Keyword(s):

Data Processing ◽

Gravity Field ◽

Stochastic Modeling ◽

Real Data ◽

Research Unit ◽

Model Errors ◽

Satellite Gravimetry ◽

Gravity Field Determination ◽

Stochastic Properties ◽

Background Models

The central hypothesis of the Research Unit (RU) NEROGRAV reads: only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-term consistency of mass transport series from satellite gravimetry can be significantly increased; and only in that case the potential of future technological sensor developments can be fully exploited. Two of the individual projects (IPs) within the RU work on stochastic modeling for GRACE and GRACE-FO gravity field determination. TU M&#252;nchen and TU Berlin are responsible for IP4 (OSTPAG: optimized space-time parameterization for GRACE and GRACE-FO data analysis), where besides optimal parameterization the focus is on the stochastic modeling of the key observations, i.e. GRACE and GRACE-FO inter-satellite ranging and accelerometer observations, in a simulation (TU M&#252;nchen) and real data (TU Berlin) environment. IP5 (ISTORE: improved stochastic modeling in GRACE/GRACE-FO real data processing), which GFZ is responsible for, works on the optimal utilization of the stochastic properties of the main GRACE and GRACE-FO observation types and the main background models. This presentation gives first insights into the TU Berlin and GFZ results of these two IPs which are both related on stochastic modeling for real data processing based on GFZ GRACE and GRACE-FO RL06 processing. We present analysis of ranging observations and corresponding residuals of three test years of GRACE and GRACE-FO real data in the time and frequency domain. Based on the residual analysis we show results of the effects of different filter matrices, which take into account the stochastic properties of the ranging observations in order to decorrelate them. The stochastic modeling of the background models in IP5 starts with Monte-Carlo simulations on background model errors of atmospheric and oceanic mass variations. Different representations of variance-covariance matrices of this model information are tested as input for real GRACE data processing and their effect on gravity field determination are analyzed.

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Modelling temporal changes in the gravity field in the Nankai Trough subduction zone, Japan

10.1002/essoar.10508046.1 ◽

2021 ◽

Author(s):

Siri Catherine Vassvåg ◽

Kuvvet Atakan ◽

Martha Økland Lien ◽

Shuichi Kodaira ◽

Toshiya Fujiwara

Keyword(s):

Gravity Field ◽

Subduction Zone ◽

Nankai Trough ◽

Temporal Changes

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The use of «native» wavelet transform for determining lateral density variation of the Volgo-Uralian subcraton

Proceedings of OilGasScientificResearchProjects Institute SOCAR ◽

10.5510/ogp2021si200565 ◽

2021 ◽

pp. 135-140

Author(s):

I. N. Ognev ◽

◽

E. V. Utemov ◽

D. K. Nurgaliev ◽

◽

...

Keyword(s):

Wavelet Transform ◽

Gravity Field ◽

Regional Scale ◽

Density Variation ◽

Gravity Modeling ◽

Regional Models ◽

Residual Gravity ◽

Satellite Gravimetry ◽

Scale Models ◽

Residual Gravity Anomaly

In the last two decades in conjunction with the development of satellite gravimetry, the techniques of regional-scale inverse and forward gravity modeling started to be more actively incorporated in the construction of crustal and lithospheric scale models. Such regional models are usually built as a set of layers and bodies with constant densities. This approach often leads to a certain difference between the initially used measured gravity field and a gravity field that is produced by the model. One of the examples of this kind of models is a recent lithospheric model of the Volgo-Uralian subcraton. In the current study, we are applying the method of «native» wavelet transform to the residual gravity anomaly for defining the possible lateral density variations within the lithospheric layers of Volgo-Uralia. Keywords: wavelet transform; gravity field inversion; forward gravity modeling; Volgo-Uralian subcraton; satellite gravimetry.

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The research unit NEROGRAV: first results on stochastic modeling for gravity field determination with real GRACE and GRACE-FO data

10.5194/egusphere-egu2020-8622 ◽

2020 ◽

Author(s):

Michael Murböck ◽

Panafidina Natalia ◽

Dahle Christoph ◽

Neumayer Karl-Hans ◽

Flechtner Frank ◽

...

Keyword(s):

Data Processing ◽

Gravity Field ◽

Stochastic Modeling ◽

Real Data ◽

Research Unit ◽

Model Errors ◽

Satellite Gravimetry ◽

Gravity Field Determination ◽

Stochastic Properties ◽

Background Models

The central hypothesis of the Research Unit (RU) NEROGRAV (New Refined Observations of Climate Change from Spaceborne Gravity Missions), funded for three years by the German Research Foundation DFG, reads: only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-term consistency of mass transport series from satellite gravimetry can be significantly increased; and only in that case the potential of future technological sensor developments can be fully exploited. Two of the individual projects (IPs) within the RU work on stochastic modeling for GRACE and GRACE-FO gravity field determination. TU M&#252;nchen and TU Berlin are responsible for IP4 (OSTPAG: optimized space-time parameterization for GRACE and GRACE-FO data analysis), where besides optimal parameterization the focus is on the stochastic modeling of the key observations, i.e. GRACE and GRACE-FO inter-satellite ranging and accelerometer observations, in a simulation (TU M&#252;nchen) and real data (TU Berlin) environment. IP5 (ISTORE: improved stochastic modeling in GRACE/GRACE-FO real data processing), which GFZ is responsible for, works on the optimal utilization of the stochastic properties of the main GRACE and GRACE-FO observation types and the main background models.This presentation gives first insights into the TU Berlin and GFZ results of these two IPs which are both related on stochastic modeling for real data processing based on GFZ GRACE and GRACE-FO RL06 processing. We present the analyses of K-band inter-satellite range observations and corresponding residuals of three test years of GRACE and GRACE-FO real data in the time and frequency domain. Based on the residual analysis we show results of the effects of different filter matrices, which take into account the stochastic properties of the range observations in order to decorrelate them. The stochastic modeling of the background models starts with Monte-Carlo simulations on background model errors of atmospheric and oceanic mass variations. Different representations of variance-covariance matrices of this model information are tested as input for real GRACE data processing and their effect on gravity field determination are analyzed.

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