Combination Service for Time-variable Gravity Field Solutions (COST-G) – GRACE-FO operational combination

2020 ◽  
Author(s):  
Ulrich Meyer ◽  
Martin Lasser ◽  
Adrian Jäggi ◽  
Frank Flechtner ◽  
Christoph Dahle ◽  
...  

<p lang="en-US">We present the operational GRACE-FO combined time-series of monthly gravity fields of the Combination Service for Time-variable Gravity fields (COST-G) of the International Association of Geodesy (IAG). COST-G_GRACE-FO_RL01_operational is combined at AIUB and relies on operational monthly solutions of the COST-G Analysis Centers GFZ, GRGS, IfG, LUH and AIUB and the associated Analysis Centers CSR and JPL. All COST-G Analysis Centers have passed a benchmark test to ensure consistency between the different processing approaches and all of the contributing time-series undergo a strict quality control focusing on the signal content in river basins and polar regions with pronounced changes in ice mass to uncover any regularization that may bias the combination.</p> <p lang="en-US">The combination is performed by variance component estimation on the solution level, the relative monthly weights thus providing valuable and independent insight into the consistency and noise levels of the individual monthly contributions. The combined products then are validated internally in terms of noise, approximated by the non-secular, non-seasonal variability over the oceans. Once they have passed this quality control the combined gravity fields are assessed by an external board of experts who evaluate them in terms of orbit predictions, lake altimetry, river hydrology or oceanography.</p>

2021 ◽  
Author(s):  
Ulrich Meyer ◽  
Martin Lasser ◽  
Adrian Jäggi ◽  
Christoph Dahle ◽  
Frank Flechtner ◽  
...  

<p>The Combination Service for Time-variable Gravity Fields (COST-G) of the International Association of Geodesy (IAG) provides combined monthly gravity fields of its associated and partner Analysis Centers (ACs). In November 2020, the combination of monthly GRACE-FO gravity fields started its operational mode, providing consolidated L2 (spherical harmonics) and L3 (gridded and post- processed) products with a latency of currently 3 months. We present an overview and quality assessment of the available products.</p><p>COST-G aims at the extension of its service to include further GRACE and GRACE-FO analysis centers. In January 2020 a collaboration with representatives of five Chinese ACs was initiated, who provided GRACE time-series according to the COST-G requirements. We present the results of a test combination with the Chinese AC models, including comparison and quality assessment of all contributing time-series and validation of the combined gravity fields.</p>


2020 ◽  
Author(s):  
Ulrich Meyer ◽  
Adrian Jäggi ◽  
Frank Flechtner ◽  
Christoph Dahle ◽  
Torsten Mayer-Gürr ◽  
...  

<p><span>With the release of the combined GRACE monthly gravity field time-series COST-G RL01 the Combination Service for Time-variable Gravity fields (COST-G) of the International Association of Geodesy (IAG) became operational in July 2019. We present the COST-G RL01 time-series and provide validation in terms of orbit fit, ice mass trends, lake altimetry and sea level budget. We identify weak points in the combined monthly gravity fields and discuss possible improvements of the combination strategy for future combinations.</span></p><p><span>While COST-G RL01 is based on sets of re-processed GRACE monthly gravity fields, COST-G also provides combinations of monthly Swarm high-low satellite-to-satellite tracking (hl-SST) gravity fields on an operational basis with a latency of 3 months. Combinations of GRACE-FO monthly gravity fields are in the process of operationalization. We provide a status report and first results of GRACE-FO combinations. Combined GRACE, Swarm and GRACE-FO gravity fields complement each other to provide a long-term time-series of mass variation in the system Earth. </span></p>


2011 ◽  
Vol 4 (1) ◽  
pp. 27-70 ◽  
Author(s):  
Th. Gruber ◽  
J. L. Bamber ◽  
M. F. P. Bierkens ◽  
H. Dobslaw ◽  
M. Murböck ◽  
...  

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.


Solid Earth ◽  
2018 ◽  
Vol 9 (2) ◽  
pp. 323-339 ◽  
Author(s):  
Christina Lück ◽  
Jürgen Kusche ◽  
Roelof Rietbroek ◽  
Anno Löcher

Abstract. Measuring the spatiotemporal variation of ocean mass allows for partitioning of volumetric sea level change, sampled by radar altimeters, into mass-driven and steric parts. The latter is related to ocean heat change and the current Earth's energy imbalance. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission has provided monthly snapshots of the Earth's time-variable gravity field, from which one can derive ocean mass variability. However, GRACE has reached the end of its lifetime with data degradation and several gaps occurred during the last years, and there will be a prolonged gap until the launch of the follow-on mission GRACE-FO. Therefore, efforts focus on generating a long and consistent ocean mass time series by analyzing kinematic orbits from other low-flying satellites, i.e. extending the GRACE time series. Here we utilize data from the European Space Agency's (ESA) Swarm Earth Explorer satellites to derive and investigate ocean mass variations. For this aim, we use the integral equation approach with short arcs (Mayer-Gürr, 2006) to compute more than 500 time-variable gravity fields with different parameterizations from kinematic orbits. We investigate the potential to bridge the gap between the GRACE and the GRACE-FO mission and to substitute missing monthly solutions with Swarm results of significantly lower resolution. Our monthly Swarm solutions have a root mean square error (RMSE) of 4.0 mm with respect to GRACE, whereas directly estimating constant, trend, annual, and semiannual (CTAS) signal terms leads to an RMSE of only 1.7 mm. Concerning monthly gaps, our CTAS Swarm solution appears better than interpolating existing GRACE data in 13.5 % of all cases, when artificially removing one solution. In the case of an 18-month artificial gap, 80.0 % of all CTAS Swarm solutions were found closer to the observed GRACE data compared to interpolated GRACE data. Furthermore, we show that precise modeling of non-gravitational forces acting on the Swarm satellites is the key for reaching these accuracies. Our results have implications for sea level budget studies, but they may also guide further research in gravity field analysis schemes, including satellites not dedicated to gravity field studies.


2011 ◽  
Vol 3 (1) ◽  
pp. 19-35 ◽  
Author(s):  
Th. Gruber ◽  
J. L. Bamber ◽  
M. F. P. Bierkens ◽  
H. Dobslaw ◽  
M. Murböck ◽  
...  

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.


2021 ◽  
Vol 13 (16) ◽  
pp. 3075
Author(s):  
Ming Xu ◽  
Xiaoyun Wan ◽  
Runjing Chen ◽  
Yunlong Wu ◽  
Wenbing Wang

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.


2017 ◽  
Author(s):  
Christina Lück ◽  
Jürgen Kusche ◽  
Roelof Rietbroek ◽  
Anno Löcher

Abstract. Measuring the spatiotemporal variation of ocean mass allows one to partition volumetric sea level change, sampled by radar altimeters, into a mass-driven and a steric part, the latter being related to ocean heat change and the current Earth’s energy imbalance. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission provides estimates of the Earth’s time-variable gravity field, from which one can derive ocean mass variability. However, GRACE has reached the end of its lifetime with data degradation and several gaps during the last years, and there will be a prolonged gap until the launch of the follow-on mission GRACE-FO. Therefore, efforts focus on generating a long and consistent ocean mass time series by analyzing kinematic orbits from other low-flying satellites; i.e. extending the GRACE time series. Here we utilize data from the European Space Agency’s (ESA) Swarm Earth Explorer satellites to derive and investigate ocean mass variations. We investigate the potential to bridge the gap between the GRACE missions and to substitute missing monthly solutions. Our monthly Swarm solutions have a root mean square error (RMSE) of 4.0 mm with respect to GRACE, whereas directly estimating trend, annual and semiannual signal terms leads to an RMSE of only 1.7 mm. Concerning monthly gaps, our Swarm solution appears better than interpolating existing GRACE data in 13.5 % of all cases, for 80.0 % of all investigated cases of an 18-months-gap, Swarm ocean mass was found closer to the observed GRACE data compared to interpolated GRACE data. Furthermore, we show that precise modelling of non-gravitational forces acting on the Swarm satellites is the key for reaching these accuracies. Our results have implications for sea level budget studies, but they may also guide further research in gravity field analysis schemes, including non-dedicated satellites.


2020 ◽  
Vol 12 (10) ◽  
pp. 1639 ◽  
Author(s):  
Ehsan Forootan ◽  
Maike Schumacher ◽  
Nooshin Mehrnegar ◽  
Aleš Bezděk ◽  
Matthieu J. Talpe ◽  
...  

Observing global terrestrial water storage changes (TWSCs) from (inter-)seasonal to (multi-)decade time-scales is very important to understand the Earth as a system under natural and anthropogenic climate change. The primary goal of the Gravity Recovery And Climate Experiment (GRACE) satellite mission (2002–2017) and its follow-on mission (GRACE-FO, 2018–onward) is to provide time-variable gravity fields, which can be converted to TWSCs with ∼ 300 km spatial resolution; however, the one year data gap between GRACE and GRACE-FO represents a critical discontinuity, which cannot be replaced by alternative data or model with the same quality. To fill this gap, we applied time-variable gravity fields (2013–onward) from the Swarm Earth explorer mission with low spatial resolution of ∼ 1500 km. A novel iterative reconstruction approach was formulated based on the independent component analysis (ICA) that combines the GRACE and Swarm fields. The reconstructed TWSC fields of 2003–2018 were compared with a commonly applied reconstruction technique and GRACE-FO TWSC fields, whose results indicate a considerable noise reduction and long-term consistency improvement of the iterative ICA reconstruction technique. They were applied to evaluate trends and seasonal mass changes (of 2003–2018) within the world’s 33 largest river basins.


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