The Effect of Pseudo-Stochastic Orbit Parameters on GRACE Monthly Gravity Fields: Insights from Lumped Coefficients

2015 ◽  
pp. 177-183 ◽  
Author(s):  
U. Meyer ◽  
C. Dahle ◽  
N. Sneeuw ◽  
A. Jäggi ◽  
G. Beutler ◽  
...  
Keyword(s):  
Gravity Fields

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

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.

Minimum time transfers of a low-thrust rocket in strong gravity fields

2003 ◽  
Vol 52 (8) ◽  
pp. 601-611 ◽  
Author(s):  
Boris M. Kiforenko ◽  
Zoya V. Pasechnik ◽  
Svitlana B. Kyrychenko ◽  
Igor Yu. Vasiliev
Keyword(s):  
Minimum Time ◽  
Low Thrust ◽  
Strong Gravity ◽  
Gravity Fields

A method to determine regional lunar gravity fields from earth-based satellite tracking data

2005 ◽  
Vol 53 (13) ◽  
pp. 1331-1340 ◽  
Author(s):  
S. Goossens ◽  
P.N.A.M. Visser ◽  
B.A.C. Ambrosius
Keyword(s):  
Satellite Tracking ◽  
Tracking Data ◽  
Lunar Gravity ◽  
Gravity Fields

Inhomogeneities in the internal structure of Mars and the Moon from data on their gravity fields

2010 ◽  
Vol 26 (2) ◽  
pp. 76-85
Author(s):  
A. L. Tserklevych ◽  
O. S. Zayats ◽  
P. M. Zazulyak ◽  
M. M. Fys
Keyword(s):  
Internal Structure ◽  
The Moon ◽  
Gravity Fields

scholarly journals On the accuracy of gravity fields obtained with Newton integrals on a hollow sphere

2020 ◽  
Author(s):  
Ludovic Jeanniot ◽  
Cedric Thieulot ◽  
Bart Root ◽  
John Naliboff ◽  
Wim Spakman
Keyword(s):  
Plate Tectonics ◽  
Mass Density ◽  
Plate Boundary ◽  
Spherical Geometry ◽  
Gravity Anomalies ◽  
Scaling Factor ◽  
Density Model ◽  
Satellite Gravity ◽  
Early Results ◽  
Gravity Fields

<p>The mass-density distribution of the Earth drives mantle convection and plate tectonics but is poorly known. We aim to predict gravity fields as a constraint for geodynamical modelling. In order to compute synthetic Earth gravity one must define a spherical geometry filled with a density model. Density models for the whole mantle down to the CMB come from tomographic models which therefore require converting speed waves velocities to density using a scaling factor.</p><p>We use a discretised integration method to compute globally gravity acceleration, gravity anomalies, potential and gradients, in the state of the art finite element code ASPECT.</p><p>Three density models are tested separately: a density field obtained from SL2013 and S40RTS tomographic models for the deep mantle, and the density model CRUST1.0 for the thin upper lithosphere layer. We combine these 3 datasets into one to create a composite model which is compared to the global seismic model LLNL-G3D-JPS of Simmons et al. (2015). We test the sensitivity of gravity prediction on the use of various conversion scaling factors of shear wave velocity to density. We find that the scaling factor profile also has a major impact on gravity prediction.</p><p>Finally, we present early results of the gravity field prediction for two local areas, the Indian-Tibet plate boundary and the Mediterranean Sea. Gravity predictions are compared to satellite gravity.</p>

A Multi-Scale Scratch Analysis Method for Quantitative Interpretation of Regional Gravity Fields

2015 ◽  
Vol 58 (1) ◽  
pp. 41-53 ◽  
Author(s):  
YANG Wen-Cai ◽  
SUN Yan-Yun ◽  
HOU Zun-Ze ◽  
YU Chang-Qing
Keyword(s):  
Quantitative Interpretation ◽  
Analysis Method ◽  
Multi Scale ◽  
Gravity Fields ◽  
Regional Gravity
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