Supporting large-scale hydrogeological monitoring and modelling by time-variable gravity data

AbstractTime-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions have opened up a new avenue of opportunities for studying large-scale mass redistribution and transport in the Earth system. Over the past 19 years, GRACE/GRACE-FO time-variable gravity measurements have been widely used to study mass variations in different components of the Earth system, including the hydrosphere, ocean, cryosphere, and solid Earth, and significantly improved our understanding of long-term variability of the climate system. We carry out a comprehensive review of GRACE/GRACE-FO satellite gravimetry, time-variable gravity fields, data processing methods, and major applications in several different fields, including terrestrial water storage change, global ocean mass variation, ice sheets and glaciers mass balance, and deformation of the solid Earth. We discuss in detail several major challenges we need to face when using GRACE/GRACE-FO time-variable gravity measurements to study mass changes, and how we should address them. We also discuss the potential of satellite gravimetry in detecting gravitational changes that are believed to originate from the deep Earth. The extended record of GRACE/GRACE-FO gravity series, with expected continuous improvements in the coming years, will lead to a broader range of applications and improve our understanding of both climate change and the Earth system.

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Regional acceleration in ice mass loss from Greenland and Antarctica using GRACE time-variable gravity data

Geophysical Research Letters ◽

10.1002/2014gl061052 ◽

2014 ◽

Vol 41 (22) ◽

pp. 8130-8137 ◽

Cited By ~ 180

Author(s):

I. Velicogna ◽

T. C. Sutterley ◽

M. R. van den Broeke

Keyword(s):

Mass Loss ◽

Gravity Data ◽

Time Variable ◽

Time Variable Gravity ◽

Variable Gravity

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Retrieval of Large-Scale Hydrological Signals in Africa from GRACE Time-Variable Gravity Fields

Pure and Applied Geophysics ◽

10.1007/s00024-011-0416-x ◽

2011 ◽

Vol 169 (8) ◽

pp. 1373-1390 ◽

Cited By ~ 7

Author(s):

Jean-Paul Boy ◽

Jacques Hinderer ◽

Caroline de Linage

Keyword(s):

Large Scale ◽

Time Variable ◽

Time Variable Gravity ◽

Gravity Fields ◽

Variable Gravity

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Spherical and ellipsoidal surface mass change from GRACE time-variable gravity data

10.5194/egusphere-egu2020-13258 ◽

2020 ◽

Author(s):

Michal Šprlák ◽

Khosro Ghobadi-Far ◽

Shin-Chan Han ◽

Pavel Novák

Keyword(s):

Gravity Field ◽

Gravitational Potential ◽

Gravity Data ◽

Time Variable ◽

Mass Change ◽

Spherical Approximation ◽

Surface Mass ◽

Time Variable Gravity ◽

The Earth ◽

Variable Gravity

The problem of estimating mass redistribution from temporal variations of the Earth&#8217;s gravity field, such as those observed by GRACE, is non-unique. By approximating the Earth&#8217;s surface by a sphere, surface mass change can be uniquely determined from time-variable gravity data. Conventionally, the spherical approach of Wahr et al. (1998) is employed for computing the surface mass change caused, for example, by terrestrial water and glaciers. The accuracy of the GRACE Level 2 time-variable gravity data has improved due to updated background geophysical models or enhanced data processing. Moreover, time series analysis of &#8764;15 years of GRACE observations allows for determining inter-annual and seasonal changes with a significantly higher accuracy than individual monthly fields. Thus, the improved time-variable gravity data might not tolerate the spherical approximation introduced by Wahr et al. (1998).A spheroid (an ellipsoid of revolution) represents a closer approximation of the Earth than a sphere, particularly in polar regions. Motivated by this fact, we develop a rigorous method for determining surface mass change on a spheroid. Our mathematical treatment is fully ellipsoidal as we concisely use Jacobi ellipsoidal coordinates and exploit the corresponding series expansions of the gravitational potential and of the surface mass. We provide a unique one-to-one relationship between the ellipsoidal spectrum of the surface mass and the ellipsoidal spectrum of the gravitational potential. This ellipsoidal spectral formula is more general and embeds the spherical approach by Wahr et al. (1998) as a special case. We also quantify the differences between the spherical and ellipsoidal approximations numerically by calculating the surface mass change rate in Antarctica and Greenland.&#160;References:Wahr J, Molenaar M, Bryan F (1998) Time variability of the Earth&#8217;s gravity field: Hydrological and oceanic effects and their possible detection using GRACE. Journal of Geophysical Research: Solid Earth, 103(B12), 30205-30229.

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Faculty Opinions recommendation of Measurements of time-variable gravity show mass loss in Antarctica.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1031925.371802 ◽

2006 ◽

Author(s):

Adrien Finzi

Keyword(s):

Mass Loss ◽

Time Variable ◽

Time Variable Gravity ◽

Variable Gravity

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Evaluation of GRACE/GRACE Follow-On Time-Variable Gravity Field Models for Earthquake Detection above Mw8.0s in Spectral Domain

Remote Sensing ◽

10.3390/rs13163075 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3075

Author(s):

Ming Xu ◽

Xiaoyun Wan ◽

Runjing Chen ◽

Yunlong Wu ◽

Wenbing Wang

Keyword(s):

Signal To Noise Ratio ◽

Time Variable ◽

Model Errors ◽

Signal To Noise ◽

Time Variable Gravity ◽

Earthquake Detection ◽

Gravity Fields ◽

Variable Gravity ◽

Gravity Recovery ◽

Gravity Field Models

This study compares the Gravity Recovery And Climate Experiment (GRACE)/GRACE Follow-On (GFO) errors with the coseismic gravity variations generated by earthquakes above Mw8.0s that occurred during April 2002~June 2017 and evaluates the influence of monthly model errors on the coseismic signal detection. The results show that the precision of GFO monthly models is approximately 38% higher than that of the GRACE monthly model and all the detected earthquakes have signal-to-noise ratio (SNR) larger than 1.8. The study concludes that the precision of the time-variable gravity fields should be improved by at least one order in order to detect all the coseismic gravity signals of earthquakes with M ≥ 8.0. By comparing the spectral intensity distribution of the GFO stack errors and the 2019 Mw8.0 Peru earthquake, it is found that the precision of the current GFO monthly model meets the requirement to detect the coseismic signal of the earthquake. However, due to the limited time length of the observations and the interference of the hydrological signal, the coseismic signals are, in practice, difficult to extract currently.

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