Preliminary monthly gravity field models from kinematic orbits of SWARM Satellites

2021 ◽  
Author(s):  
Xingfu Zhang ◽  
Qiujie Chen ◽  
Yunzhong Shen
Keyword(s):  
Gravity Field ◽  
Large Scale ◽  
Earth System ◽  
The Earth ◽  
Swarm Satellites ◽  
Variable Gravity ◽  
Data Gap ◽  
One Year ◽  
Gravity Recovery ◽  
Gravity Field Models

<p>      Although the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE FO) satellite missions play an important role in monitoring global mass changes within the Earth system, there is a data gap of about one year spanning July 2017 to May 2018, which leads to discontinuous gravity observations for monitoring global mass changes. As an alternative mission, the SWARM satellites can provide gravity observations to close this data gap. In this paper, we are dedicated to developing alternative monthly time-variable gravity field solutions from SWARM data. Using kinematic orbits of SWARM from ITSG for the period January 2015 to September 2020, we have generated a preliminary time series of monthly gravity field models named Tongji-Swarm2019 up to degree and order 60. The comparisons between Tongji-Swarm2019 and GRACE/GRACE-FO monthly solutions show that Tongji-Swarm2019 solutions agree with GRACE/GRACE-FO models in terms of large-scale mass change signals over amazon, Greenland and other regions. We can conclude that Tongji-Swarm2019 monthly gravity field models are able to close the gap between GRACE and GRACE FO.</p>

scholarly journals Simulation of the time-variable gravity field by means of coupled geophysical models

2011 ◽  
Vol 4 (1) ◽  
pp. 27-70 ◽  
Author(s):  
Th. Gruber ◽  
J. L. Bamber ◽  
M. F. P. Bierkens ◽  
H. Dobslaw ◽  
M. Murböck ◽  
...  
Keyword(s):  
Time Series ◽  
Gravity Field ◽  
Mass Distribution ◽  
Time Variable ◽  
Data Sets ◽  
Earth System ◽  
Time Variable Gravity ◽  
The Earth ◽  
Gravity Fields ◽  
Variable Gravity

Abstract. Time variable gravity fields, reflecting variations of mass distribution in the system Earth is one of the key parameters to understand the changing Earth. Mass variations are caused either by redistribution of mass in, on or above the Earth's surface or by geophysical processes in the Earth's interior. The first set of observations of monthly variations of the Earth gravity field was provided by the US/German GRACE satellite mission beginning in 2002. This mission is still providing valuable information to the science community. However, as GRACE has outlived its expected lifetime, the geoscience community is currently seeking successor missions in order to maintain the long time series of climate change that was begun by GRACE. Several studies on science requirements and technical feasibility have been conducted in the recent years. These studies required a realistic model of the time variable gravity field in order to perform simulation studies on sensitivity of satellites and their instrumentation. This was the primary reason for the European Space Agency (ESA) to initiate a study on "Monitoring and Modelling individual Sources of Mass Distribution and Transport in the Earth System by Means of Satellites". The goal of this interdisciplinary study was to create as realistic as possible simulated time variable gravity fields based on coupled geophysical models, which could be used in the simulation processes in a controlled environment. For this purpose global atmosphere, ocean, continental hydrology and ice models were used. The coupling was performed by using consistent forcing throughout the models and by including water flow between the different domains of the Earth system. In addition gravity field changes due to solid Earth processes like continuous glacial isostatic adjustment (GIA) and a sudden earthquake with co-seismic and post-seismic signals were modelled. All individual model results were combined and converted to gravity field spherical harmonic series, which is the quantity commonly used to describe the Earth's global gravity field. The result of this study is a twelve-year time-series of 6-hourly time variable gravity field spherical harmonics up to degree and order 180 corresponding to a global spatial resolution of 1 degree in latitude and longitude. In this paper, we outline the input data sets and the process of combining these data sets into a coherent model of temporal gravity field changes. The resulting time series was used in some follow-on studies and is available to anybody interested via a Website.

scholarly journals Applications and Challenges of GRACE and GRACE Follow-On Satellite Gravimetry

2022 ◽  
Author(s):  
Jianli Chen ◽  
Anny Cazenave ◽  
Christoph Dahle ◽  
William Llovel ◽  
Isabelle Panet ◽  
...  
Keyword(s):  
Solid Earth ◽  
Large Scale ◽  
Time Variable ◽  
Global Ocean ◽  
Earth System ◽  
Satellite Gravimetry ◽  
Time Variable Gravity ◽  
The Earth ◽  
Gravity Measurements ◽  
Variable Gravity

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.

scholarly journals Simulation of the time-variable gravity field by means of coupled geophysical models

2011 ◽  
Vol 3 (1) ◽  
pp. 19-35 ◽  
Author(s):  
Th. Gruber ◽  
J. L. Bamber ◽  
M. F. P. Bierkens ◽  
H. Dobslaw ◽  
M. Murböck ◽  
...  
Keyword(s):  
Time Series ◽  
Gravity Field ◽  
Mass Distribution ◽  
Time Variable ◽  
Data Sets ◽  
Earth System ◽  
Time Variable Gravity ◽  
The Earth ◽  
Gravity Fields ◽  
Variable Gravity

Abstract. Time variable gravity fields, reflecting variations of mass distribution in the system Earth is one of the key parameters to understand the changing Earth. Mass variations are caused either by redistribution of mass in, on or above the Earth's surface or by geophysical processes in the Earth's interior. The first set of observations of monthly variations of the Earth gravity field was provided by the US/German GRACE satellite mission beginning in 2002. This mission is still providing valuable information to the science community. However, as GRACE has outlived its expected lifetime, the geoscience community is currently seeking successor missions in order to maintain the long time series of climate change that was begun by GRACE. Several studies on science requirements and technical feasibility have been conducted in the recent years. These studies required a realistic model of the time variable gravity field in order to perform simulation studies on sensitivity of satellites and their instrumentation. This was the primary reason for the European Space Agency (ESA) to initiate a study on ''Monitoring and Modelling individual Sources of Mass Distribution and Transport in the Earth System by Means of Satellites''. The goal of this interdisciplinary study was to create as realistic as possible simulated time variable gravity fields based on coupled geophysical models, which could be used in the simulation processes in a controlled environment. For this purpose global atmosphere, ocean, continental hydrology and ice models were used. The coupling was performed by using consistent forcing throughout the models and by including water flow between the different domains of the Earth system. In addition gravity field changes due to solid Earth processes like continuous glacial isostatic adjustment (GIA) and a sudden earthquake with co-seismic and post-seismic signals were modelled. All individual model results were combined and converted to gravity field spherical harmonic series, which is the quantity commonly used to describe the Earth's global gravity field. The result of this study is a twelve-year time-series of 6-hourly time variable gravity field spherical harmonics up to degree and order 180 corresponding to a global spatial resolution of 1 degree in latitude and longitude. In this paper, we outline the input data sets and the process of combining these data sets into a coherent model of temporal gravity field changes. The resulting time series was used in some follow-on studies and is available to anybody interested.

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.

Dryland Degradation and Expansion: Implications for Mexican Policies from the Earth System Perspective

2020 ◽  
pp. 1-4
Author(s):  
Gabriel Lopez Porras
Keyword(s):  
Climate Change ◽  
Ecosystem Services ◽  
Science Policy ◽  
Land Degradation ◽  
Water Scarcity ◽  
Large Scale ◽  
Earth System ◽  
Sustainable Land Management ◽  
System Perspective ◽  
The Earth

Despite international efforts to stop dryland degradation and expansion, current dryland pathways are predicted to result in large-scale migration, growing poverty and famine, and increasing climate change, land degradation, conflicts and water scarcity. Earth system science has played a key role in analysing dryland problems, and has been even incorporated in global assessments such as the ones made by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. However, policies addressing dryland degradation, like the ‘Mexican programme for the promotion of sustainable land management’, do not embrace an Earth system perspective, so they do not consider the complexity and non-linearity that underlie dryland problems. By exploring how this Mexican programme could integrate the Earth system perspective, this paper discusses how ’Earth system’ policies could better address dryland degradation and expansion in the Anthropocene.

scholarly journals Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP

2020 ◽  
Vol 13 (7) ◽  
pp. 3383-3438 ◽  
Author(s):  
Veronika Eyring ◽  
Lisa Bock ◽  
Axel Lauer ◽  
Mattia Righi ◽  
Manuel Schlund ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Evaluation Tool ◽  
The Earth ◽  
And Performance ◽  
Earth System Models

Abstract. The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.

scholarly journals Accuracy Analysis of Gravity Field Changes from Grace RL06 and RL05 Data Compared to in Situ Gravimetric Measurements in the Context of Choosing Optimal Filtering Type

2020 ◽  
Vol 55 (3) ◽  
pp. 100-117
Author(s):  
Viktor Szabó ◽  
Dorota Marjańska
Keyword(s):  
Gravity Field ◽  
Ocean Circulation ◽  
Gravity Data ◽  
The Other ◽  
Subsurface Water ◽  
Satellite Gravity ◽  
Absolute Gravimetry ◽  
The Earth ◽  
Gravity Measurements ◽  
Gravity Recovery

AbstractGlobal satellite gravity measurements provide unique information regarding gravity field distribution and its variability on the Earth. The main cause of gravity changes is the mass transportation within the Earth, appearing as, e.g. dynamic fluctuations in hydrology, glaciology, oceanology, meteorology and the lithosphere. This phenomenon has become more comprehensible thanks to the dedicated gravimetric missions such as Gravity Recovery and Climate Experiment (GRACE), Challenging Minisatellite Payload (CHAMP) and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE). From among these missions, GRACE seems to be the most dominating source of gravity data, sharing a unique set of observations from over 15 years. The results of this experiment are often of interest to geodesists and geophysicists due to its high compatibility with the other methods of gravity measurements, especially absolute gravimetry. Direct validation of gravity field solutions is crucial as it can provide conclusions concerning forecasts of subsurface water changes. The aim of this work is to present the issue of selection of filtration parameters for monthly gravity field solutions in RL06 and RL05 releases and then to compare them to a time series of absolute gravimetric data conducted in quasi-monthly measurements in Astro-Geodetic Observatory in Józefosław (Poland). The other purpose of this study is to estimate the accuracy of GRACE temporal solutions in comparison with absolute terrestrial gravimetry data and making an attempt to indicate the significance of differences between solutions using various types of filtration (DDK, Gaussian) from selected research centres.

scholarly journals Evaluation of Gravity Data Derived from Global Gravity Field Models Using Terrestrial Gravity Data in Enugu State, Nigeria

2018 ◽  
Vol 8 (1) ◽  
pp. 145-153 ◽  
Author(s):  
O.I. Apeh ◽  
E.C. Moka ◽  
V.N. Uzodinma
Keyword(s):  
Gravity Field ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Mean Square ◽  
Bouguer Gravity ◽  
Bouguer Anomalies ◽  
The Earth ◽  
Global Gravity ◽  
Enugu State ◽  
Gravity Field Models

Abstract Spherical harmonic expansion is a commonly applied mathematical representation of the earth’s gravity field. This representation is implied by the potential coeffcients determined by using elements/parameters of the field observed on the surface of the earth and/or in space outside the earth in the spherical harmonic expansion of the field. International Centre for Gravity Earth Models (ICGEM) publishes, from time to time, Global Gravity Field Models (GGMs) that have been developed. These GGMs need evaluation with terrestrial data of different locations to ascertain their accuracy for application in those locations. In this study, Bouguer gravity anomalies derived from a total of eleven (11) recent GGMs, using sixty sample points, were evaluated by means of Root-Mean-Square difference and correlation coeficient. The Root-Mean-Square differences of the computed Bouguer anomalies from ICGEMwebsite compared to their positionally corresponding terrestrial Bouguer anomalies range from 9.530mgal to 37.113mgal. Additionally, the correlation coe_cients of the structure of the signal of the terrestrial and GGM-derived Bouguer anomalies range from 0.480 to 0.879. It was observed that GECO derived Bouguer gravity anomalies have the best signal structure relationship with the terrestrial data than the other ten GGMs. We also discovered that EIGEN-6C4 and GECO derived Bouguer anomalies have enormous potential to be used as supplements to the terrestrial Bouguer anomalies for Enugu State, Nigeria.

scholarly journals SLR, GRACE and Swarm Gravity Field Determination and Combination

2019 ◽  
Vol 11 (8) ◽  
pp. 956 ◽  
Author(s):  
Ulrich Meyer ◽  
Krzysztof Sosnica ◽  
Daniel Arnold ◽  
Christoph Dahle ◽  
Daniela Thaller ◽  
...  
Keyword(s):  
Mass Transport ◽  
Gravity Field ◽  
Large Scale ◽  
Mass Gain ◽  
Normal Equation ◽  
Polar Regions ◽  
Swarm Satellites ◽  
Gravity Fields ◽  
Long Time ◽  
Gravity Field Determination

Satellite gravimetry allows for determining large scale mass transport in the system Earth and to quantify ice mass change in polar regions. We provide, evaluate and compare a long time-series of monthly gravity field solutions derived either by satellite laser ranging (SLR) to geodetic satellites, by GPS and K-band observations of the GRACE mission, or by GPS observations of the three Swarm satellites. While GRACE provides gravity signal at the highest spatial resolution, SLR sheds light on mass transport in polar regions at larger scales also in the pre- and post-GRACE era. To bridge the gap between GRACE and GRACE Follow-On, we also derive monthly gravity fields using Swarm data and perform a combination with SLR. To correctly take all correlations into account, this combination is performed on the normal equation level. Validating the Swarm/SLR combination against GRACE during the overlapping period January 2015 to June 2016, the best fit is achieved when down-weighting Swarm compared to the weights determined by variance component estimation. While between 2014 and 2017 SLR alone slightly overestimates mass loss in Greenland compared to GRACE, the combined gravity fields match significantly better in the overlapping time period and the RMS of the differences is reduced by almost 100 Gt. After 2017, both SLR and Swarm indicate moderate mass gain in Greenland.

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