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Journal articles on the topic 'GRACE follow-on'

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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Amann, Manfred, Mike Gross, and Hauke Thamm. "The Grace Follow-On Quiet Electrical Power System." E3S Web of Conferences 16 (2017): 13011. http://dx.doi.org/10.1051/e3sconf/20171613011.

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2

Abich, Klaus, Christina Bogan, Claus Braxmaier, Karsten Danzmann, Marina Dehne, Martin Gohlke, Alexander Görth, et al. "GRACE-Follow On Laser Ranging Interferometer: German contribution." Journal of Physics: Conference Series 610 (May 11, 2015): 012010. http://dx.doi.org/10.1088/1742-6596/610/1/012010.

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3

Fleddermann, R., R. L. Ward, M. Elliot, D. M. Wuchenich, F. Gilles, M. Herding, K. Nicklaus, et al. "Testing the GRACE follow-on triple mirror assembly." Classical and Quantum Gravity 31, no. 19 (September 16, 2014): 195004. http://dx.doi.org/10.1088/0264-9381/31/19/195004.

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4

Darbeheshti, Neda, Henry Wegener, Vitali Müller, Majid Naeimi, Gerhard Heinzel, and Martin Hewitson. "Instrument data simulations for GRACE Follow-on: observation and noise models." Earth System Science Data 9, no. 2 (November 17, 2017): 833–48. http://dx.doi.org/10.5194/essd-9-833-2017.

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Abstract. The Gravity Recovery and Climate Experiment (GRACE) mission has yielded data on the Earth's gravity field to monitor temporal changes for more than 15 years. The GRACE twin satellites use microwave ranging with micrometre precision to measure the distance variations between two satellites caused by the Earth's global gravitational field. GRACE Follow-on (GRACE-FO) will be the first satellite mission to use inter-satellite laser interferometry in space. The laser ranging instrument (LRI) will provide two additional measurements compared to the GRACE mission: interferometric inter-satellite ranging with nanometre precision and inter-satellite pointing information. We have designed a set of simulated GRACE-FO data, which include LRI measurements, apart from all other GRACE instrument data needed for the Earth's gravity field recovery. The simulated data files are publicly available via https://doi.org/10.22027/AMDC2 and can be used to derive gravity field solutions like from GRACE data. This paper describes the scientific basis and technical approaches used to simulate the GRACE-FO instrument data.
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5

Lenczuk, Artur, Matthias Weigelt, Wieslaw Kosek, and Jan Mikocki. "Autoregressive Reconstruction of Total Water Storage within GRACE and GRACE Follow-On Gap Period." Energies 15, no. 13 (July 1, 2022): 4827. http://dx.doi.org/10.3390/en15134827.

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For 15 years, the Gravity Recovery and Climate Experiment (GRACE) mission have monitored total water storage (TWS) changes. The GRACE mission ended in October 2017, and 11 months later, the GRACE Follow-On (GRACE-FO) mission was launched in May 2018. Bridging the gap between both missions is essential to obtain continuous mass changes. To fill the gap, we propose a new approach based on a remove–restore technique combined with an autoregressive (AR) prediction. We first make use of the Global Land Data Assimilation System (GLDAS) hydrological model to remove climatology from GRACE/GRACE-FO data. Since the GLDAS mis-models real TWS changes for many regions around the world, we further use least-squares estimation (LSE) to remove remaining residual trends and annual and semi-annual oscillations. The missing 11 months of TWS values are then predicted forward and backward with an AR model. For the forward approach, we use the GRACE TWS values before the gap; for the backward approach, we use the GRACE-FO TWS values after the gap. The efficiency of forward–backward AR prediction is examined for the artificial gap of 11 months that we create in the GRACE TWS changes for the July 2008 to May 2009 period. We obtain average differences between predicted and observed GRACE values of at maximum 5 cm for 80% of areas, with the extreme values observed for the Amazon, Alaska, and South and Northern Asia. We demonstrate that forward–backward AR prediction is better than the standalone GLDAS hydrological model for more than 75% of continental areas. For the natural gap (July 2017–May 2018), the misclosures in backward–forward prediction estimated between forward- and backward-predicted values are equal to 10 cm. This represents an amount of 10–20% of the total TWS signal for 60% of areas. The regional analysis shows that the presented method is able to capture the occurrence of droughts or floods, but does not reflect their magnitudes. Results indicate that the presented remove–restore technique combined with AR prediction can be utilized to reliably predict TWS changes for regional analysis, but the removed climatology must be properly matched to the selected region.
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6

Schütze, Daniel, Gunnar Stede, Vitali Müller, Oliver Gerberding, Tamara Bandikova, Benjamin S. Sheard, Gerhard Heinzel, and Karsten Danzmann. "Laser beam steering for GRACE Follow-On intersatellite interferometry." Optics Express 22, no. 20 (September 25, 2014): 24117. http://dx.doi.org/10.1364/oe.22.024117.

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7

Shang, Peisi, Xiaoli Su, and Zhicai Luo. "Characteristics of the Greenland Ice Sheet Mass Variations Revealed by GRACE/GRACE Follow-On Gravimetry." Remote Sensing 14, no. 18 (September 6, 2022): 4442. http://dx.doi.org/10.3390/rs14184442.

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As a major contributor to global mean sea-level rise, the Greenland ice sheet (GrIS) and the patterns of its mass change have attracted wide attention. Based on Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) gravimetry data, we computed monthly non-cumulative mass change time series of the GrIS, which agree with those from the mass budget method confirming the reliability of GRACE-FO-derived mass change. Over the GrIS, mass was mainly gained in winter, followed by spring. It primarily lost mass in summer, with the percentage of summer mass loss versus the corresponding annual mass loss ranging from 61% to 96%. We report that spring mass loss has become more frequent since 2015, and autumn mass gain occurred more frequently after 2014. By separating mass gain from mass loss at the annual timescale, we find that both the mass gain and mass loss showed a slightly increasing trend during 2003–2020, which might be a response to the ongoing Arctic warming. Summer mass variations highly correlated with the summer North Atlantic Oscillation index are dominated by temperature-associated precipitation and meltwater runoff. This study suggests that long-term observations would be necessary to better understand patterns of the GrIS mass variations in future.
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8

Görth, A., J. Sanjuan, M. Gohlke, S. Rasch, K. Abich, C. Braxmaier, and G. Heinzel. "Test environments for the GRACE follow-on laser ranging interferometer." Journal of Physics: Conference Series 716 (May 2016): 012011. http://dx.doi.org/10.1088/1742-6596/716/1/012011.

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9

Wuchenich, Danielle M. R., Christoph Mahrdt, Benjamin S. Sheard, Samuel P. Francis, Robert E. Spero, John Miller, Conor M. Mow-Lowry, et al. "Laser link acquisition demonstration for the GRACE Follow-On mission." Optics Express 22, no. 9 (May 2, 2014): 11351. http://dx.doi.org/10.1364/oe.22.011351.

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10

Loomis, Bryant D., R. S. Nerem, and S. B. Luthcke. "Simulation study of a follow-on gravity mission to GRACE." Journal of Geodesy 86, no. 5 (October 28, 2011): 319–35. http://dx.doi.org/10.1007/s00190-011-0521-8.

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11

Sheard, B. S., G. Heinzel, K. Danzmann, D. A. Shaddock, W. M. Klipstein, and W. M. Folkner. "Intersatellite laser ranging instrument for the GRACE follow-on mission." Journal of Geodesy 86, no. 12 (May 8, 2012): 1083–95. http://dx.doi.org/10.1007/s00190-012-0566-3.

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12

Koch, Igor, Mathias Duwe, Jakob Flury, and Akbar Shabanloui. "Earth’s Time-Variable Gravity from GRACE Follow-On K-Band Range-Rates and Pseudo-Observed Orbits." Remote Sensing 13, no. 9 (May 1, 2021): 1766. http://dx.doi.org/10.3390/rs13091766.

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During its science phase from 2002–2017, the low-low satellite-to-satellite tracking mission Gravity Field Recovery And Climate Experiment (GRACE) provided an insight into Earth’s time-variable gravity (TVG). The unprecedented quality of gravity field solutions from GRACE sensor data improved the understanding of mass changes in Earth’s system considerably. Monthly gravity field solutions as the main products of the GRACE mission, published by several analysis centers (ACs) from Europe, USA and China, became indispensable products for quantifying terrestrial water storage, ice sheet mass balance and sea level change. The successor mission GRACE Follow-On (GRACE-FO) was launched in May 2018 and proceeds observing Earth’s TVG. The Institute of Geodesy (IfE) at Leibniz University Hannover (LUH) is one of the most recent ACs. The purpose of this article is to give a detailed insight into the gravity field recovery processing strategy applied at LUH; to compare the obtained gravity field results to the gravity field solutions of other established ACs; and to compare the GRACE-FO performance to that of the preceding GRACE mission in terms of post-fit residuals. We use the in-house-developed MATLAB-based GRACE-SIGMA software to compute unconstrained solutions based on the generalized orbit determination of 3 h arcs. K-band range-rates (KBRR) and kinematic orbits are used as (pseudo)-observations. A comparison of the obtained solutions to the results of the GRACE-FO Science Data System (SDS) and Combination Service for Time-variable Gravity Fields (COST-G) ACs, reveals a competitive quality of our solutions. While the spectral and spatial noise levels slightly differ, the signal content of the solutions is similar among all ACs. The carried out comparison of GRACE and GRACE-FO KBRR post-fit residuals highlights an improvement of the GRACE-FO K-band ranging system performance. The overall amplitude of GRACE-FO post-fit residuals is about three times smaller, compared to GRACE. GRACE-FO post-fit residuals show less systematics, compared to GRACE. Nevertheless, the power spectral density of GRACE-FO and GRACE post-fit residuals is dominated by similar spikes located at multiples of the orbital and daily frequencies. To our knowledge, the detailed origin of these spikes and their influence on the gravity field recovery quality were not addressed in any study so far and therefore deserve further attention in the future. Presented results are based on 29 monthly gravity field solutions from June 2018 until December 2020. The regularly updated LUH-GRACE-FO-2020 time series of monthly gravity field solutions can be found on the website of the International Centre for Global Earth Models (ICGEM) and in LUH’s research data repository. These operationally published products complement the time series of the already established ACs and allow for a continuous and independent assessment of mass changes in Earth’s system.
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13

Wei, Zheng, Hsu Hou-Tse, Zhong Min, and Yun Mei-Juan. "Accurate and rapid error estimation on global gravitational field from current GRACE and future GRACE Follow-On missions." Chinese Physics B 18, no. 8 (July 31, 2009): 3597–604. http://dx.doi.org/10.1088/1674-1056/18/8/077.

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14

Qu, Wei, Zehui Jin, Qin Zhang, Yuan Gao, Pufang Zhang, and Peinan Chen. "Estimation of Evapotranspiration in the Yellow River Basin from 2002 to 2020 Based on GRACE and GRACE Follow-On Observations." Remote Sensing 14, no. 3 (February 4, 2022): 730. http://dx.doi.org/10.3390/rs14030730.

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Evapotranspiration (ET) plays an important role in the hydrological cycle of river basins. Studying ET in the Yellow River Basin (YRB) is greatly significant for the scientific management of water resources. Here, we made full use of the advantages of the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) gravity satellites for monitoring large-scale hydrological changes to calculate the terrestrial water storage anomaly (TWSA) and terrestrial water flux in the YRB from May 2002 to June 2020. Furthermore, combined with terrestrial water flux, precipitation, and runoff data, ET in the YRB was calculated based on the water budget equation and then compared with other traditional ET products. The mutation of annual mean ET was identified by the Mann–Kendall trend test method, and the seasonal and interannual variations of ET were explored. ET was closely related to precipitation. Annual mean ET exhibited a sudden change in 2011, with an insignificant downward trend from 2003 to 2010, followed by an increasing trend from 2011 to 2019, particularly after 2016. Compared with the traditional ET monitoring methods and products, the ET estimated by GRACE/GRACE-FO observations provides a new way to effectively obtain continuous and reliable ET data in a wide range of river basins.
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15

Bachman, B., G. de Vine, J. Dickson, S. Dubovitsky, J. Liu, W. Klipstein, K. McKenzie, et al. "Flight phasemeter on the Laser Ranging Interferometer on the GRACE Follow-On mission." Journal of Physics: Conference Series 840 (May 2017): 012011. http://dx.doi.org/10.1088/1742-6596/840/1/012011.

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16

Zheng, Wei, and Houze Xu. "Progress in satellite gravity recovery from implemented CHAMP, GRACE and GOCE and future GRACE Follow-On missions." Geodesy and Geodynamics 6, no. 4 (July 2015): 241–47. http://dx.doi.org/10.1016/j.geog.2015.05.005.

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17

Kornfeld, Richard P., Bradford W. Arnold, Michael A. Gross, Neil T. Dahya, William M. Klipstein, Peter F. Gath, and Srinivas Bettadpur. "GRACE-FO: The Gravity Recovery and Climate Experiment Follow-On Mission." Journal of Spacecraft and Rockets 56, no. 3 (May 2019): 931–51. http://dx.doi.org/10.2514/1.a34326.

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18

Schütze, Daniel, Vitali Müller, Gunnar Stede, Benjamin S. Sheard, Gerhard Heinzel, Karsten Danzmann, Andrew J. Sutton, and Daniel A. Shaddock. "Retroreflector for GRACE follow-on: Vertex vs point of minimal coupling." Optics Express 22, no. 8 (April 10, 2014): 9324. http://dx.doi.org/10.1364/oe.22.009324.

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19

Bender, Peter L., and Casey R. Betts. "Ocean calibration approach for data from the GRACE Follow‐On mission." Journal of Geophysical Research: Solid Earth 121, no. 2 (February 2016): 1218–35. http://dx.doi.org/10.1002/2015jb012433.

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20

Śliwińska, Justyna, Małgorzata Wińska, and Jolanta Nastula. "Preliminary Estimation and Validation of Polar Motion Excitation from Different Types of the GRACE and GRACE Follow-On Missions Data." Remote Sensing 12, no. 21 (October 23, 2020): 3490. http://dx.doi.org/10.3390/rs12213490.

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The Gravity Recovery and Climate Experiment (GRACE) mission has provided global observations of temporal variations in the gravity field resulting from mass redistribution at the surface and within the Earth for the period 2002–2017. Although GRACE satellites are not able to realistically detect the second zonal parameter (ΔC20) of geopotential associated with the flattening of the Earth, they can accurately determine variations in degree-2 order-1 (ΔC21, ΔS21) coefficients that are proportional to variations in polar motion. Therefore, GRACE measurements are commonly exploited to interpret polar motion changes due to variations in the global mass redistribution, especially in the continental hydrosphere and cryosphere. Such impacts are usually examined by computing the so-called hydrological polar motion excitation (HAM) and cryospheric polar motion excitation (CAM), often analyzed together as HAM/CAM. The great success of the GRACE mission and the scientific robustness of its data contributed to the launch of its successor, GRACE Follow-On (GRACE-FO), which began in May 2018 and continues to the present. This study presents the first estimates of HAM/CAM computed from GRACE-FO data provided by three data centers: Center for Space Research (CSR), Jet Propulsion Laboratory (JPL), and GeoForschungsZentrum (GFZ). In this paper, the data series is computed using different types of GRACE/GRACE-FO data: ΔC21, ΔS21 coefficients of geopotential, gridded terrestrial water storage anomalies, and mascon solutions. We compare and evaluate different methods of HAM/CAM estimation and examine the compatibility between CSR, JPL, and GFZ data. We also validate different HAM/CAM estimations using precise geodetic measurements and geophysical models. Analysis of data from the first 19 months of GRACE-FO shows that the consistency between GRACE-FO-based HAM/CAM and observed hydrological/cryospheric signals in polar motion is similar to the consistency obtained for the initial period of the GRACE mission, worse than the consistency received for the best GRACE period, and higher than the consistency obtained for the terminal phase of the GRACE mission. In general, the current quality of HAM/CAM from GRACE Follow-On meets expectations. In the following months, after full calibration of the instruments, this accuracy is expected to increase.
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21

Nie, Yufeng, Yunzhong Shen, and Qiujie Chen. "Combination Analysis of Future Polar-Type Gravity Mission and GRACE Follow-On." Remote Sensing 11, no. 2 (January 21, 2019): 200. http://dx.doi.org/10.3390/rs11020200.

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Thanks to the unprecedented success of Gravity Recovery and Climate Experiment (GRACE), its successive mission GRACE Follow-On (GFO) has been in orbit since May 2018 to continue measuring the Earth’s mass transport. In order to possibly enhance GFO in terms of mass transport estimates, four orbit configurations of future polar-type gravity mission (FPG) (with the same payload accuracy and orbit parameters as GRACE, but differing in orbit inclination) are investigated by full-scale simulations in both standalone and jointly with GFO. The results demonstrate that the retrograde orbit modes used in FPG are generally superior to prograde in terms of gravity field estimation in the case of a joint GFO configuration. Considering the FPG’s independent capability, the orbit configurations with 89- and 91-degree inclinations (namely FPG-89 and FPG-91) are further analyzed by joint GFO monthly gravity field models over the period of one-year. Our analyses show that the FPG-91 basically outperforms the FPG-89 in mass change estimates, especially at the medium- and low-latitude regions. Compared to GFO & FPG-89, about 22% noise reduction over the ocean area and 17% over land areas are achieved by the GFO & FPG-91 combined model. Therefore, the FPG-91 is worthy to be recommended for the further orbit design of FPGs.
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22

Wei, Min, Hao Zhou, Zhicai Luo, and Min Dai. "Tracking inter-annual terrestrial water storage variations over Lake Baikal basin from GRACE and GRACE Follow-On missions." Journal of Hydrology: Regional Studies 40 (April 2022): 101004. http://dx.doi.org/10.1016/j.ejrh.2022.101004.

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23

Lai, Yu, Bao Zhang, Yibin Yao, Lin Liu, Xiao Yan, Yulin He, and Shuyuan Ou. "Reconstructing the data gap between GRACE and GRACE follow-on at the basin scale using artificial neural network." Science of The Total Environment 823 (June 2022): 153770. http://dx.doi.org/10.1016/j.scitotenv.2022.153770.

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24

Wegener, Henry, Vitali Müller, Gerhard Heinzel, and Malte Misfeldt. "Tilt-to-Length Coupling in the GRACE Follow-On Laser Ranging Interferometer." Journal of Spacecraft and Rockets 57, no. 6 (November 2020): 1362–72. http://dx.doi.org/10.2514/1.a34790.

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25

Schütze, Daniel. "Measuring Earth: Current status of the GRACE Follow-On Laser Ranging Interferometer." Journal of Physics: Conference Series 716 (May 2016): 012005. http://dx.doi.org/10.1088/1742-6596/716/1/012005.

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26

Sanjuan, Josep, Martin Gohlke, Stefan Rasch, Klaus Abich, Alexander Görth, Gerhard Heinzel, and Claus Braxmaier. "Interspacecraft link simulator for the laser ranging interferometer onboard GRACE Follow-On." Applied Optics 54, no. 22 (July 22, 2015): 6682. http://dx.doi.org/10.1364/ao.54.006682.

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27

Wang, Fengwei, Yunzhong Shen, Qiujie Chen, and Wei Wang. "Bridging the gap between GRACE and GRACE follow-on monthly gravity field solutions using improved multichannel singular spectrum analysis." Journal of Hydrology 594 (March 2021): 125972. http://dx.doi.org/10.1016/j.jhydrol.2021.125972.

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28

Xu, Ming, Xiaoyun Wan, Runjing Chen, Yunlong Wu, and Wenbing Wang. "Evaluation of GRACE/GRACE Follow-On Time-Variable Gravity Field Models for Earthquake Detection above Mw8.0s in Spectral Domain." Remote Sensing 13, no. 16 (August 5, 2021): 3075. http://dx.doi.org/10.3390/rs13163075.

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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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Delforge, Damien, Olivier de Viron, Fabien Durand, and Véronique Dehant. "The Global Patterns of Interannual and Intraseasonal Mass Variations in the Oceans from GRACE and GRACE Follow-On Records." Remote Sensing 14, no. 8 (April 12, 2022): 1861. http://dx.doi.org/10.3390/rs14081861.

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We decompose the monthly global ocean bottom pressure (OBP) from GRACE(-FO) mass concentration solutions, with trends and seasonal harmonics removed from the signal, to extract 23 significant regional modes of variability. The 23 modes are analyzed and discussed considering sea-level anomalies (SLA), wind stress curl (WSC), and major climate indices. A total of two-thirds of the patterns correspond to extratropical regions and are substantially documented in other global or regional studies. Over the equatorial band, the identified modes are unprecedented, with an amplitude ranging between 0.5 and 1 cm. With smaller amplitude than extratropical patterns, they appear to be less correlated with the local SLA or WSC; yet they present significantly coherent dynamics. The Pacific Ocean modes show significant correlations with the Pacific decadal oscillation (PDO) and El Niño southern oscillation (ENSO).
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Xiong, Jinghua, Jiabo Yin, Shenglian Guo, and Louise Slater. "Continuity of terrestrial water storage variability and trends across mainland China monitored by the GRACE and GRACE-Follow on satellites." Journal of Hydrology 599 (August 2021): 126308. http://dx.doi.org/10.1016/j.jhydrol.2021.126308.

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31

Goswami, Sujata, Samuel P. Francis, Tamara Bandikova, and Robert E. Spero. "Analysis of GRACE Follow-On Laser Ranging Interferometer Derived Inter-Satellite Pointing Angles." IEEE Sensors Journal 21, no. 17 (September 1, 2021): 19209–21. http://dx.doi.org/10.1109/jsen.2021.3090790.

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32

Numata, K., and J. Camp. "Precision laser development for interferometric space missions NGO, SGO, and GRACE Follow-On." Journal of Physics: Conference Series 363 (June 1, 2012): 012054. http://dx.doi.org/10.1088/1742-6596/363/1/012054.

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33

Qu, Wei, Yaxi Han, Zhong Lu, Dongdong An, Qin Zhang, and Yuan Gao. "Co-Seismic and Post-Seismic Temporal and Spatial Gravity Changes of the 2010 Mw 8.8 Maule Chile Earthquake Observed by GRACE and GRACE Follow-on." Remote Sensing 12, no. 17 (August 26, 2020): 2768. http://dx.doi.org/10.3390/rs12172768.

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The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (GRACE-FO) satellites are important for studying regional gravitational field changes caused by strong earthquakes. In this study, we chose Chile, one of Earth’s most active seismic zones to explore the co-seismic and post-seismic gravitational field changes of the 2010 Mw 8.8 Maule earthquake based on longer-term GRACE and the newest GRACE-FO data. We calculated the first-order co-seismic gravity gradient changes (GGCs) and probed the geodynamic characteristics of the earthquake. The earthquake caused significant positive gravity change on the footwall and negative gravity changes on the hanging wall of the seismogenic fault. The time series of gravity changes at typical points all clearly revealed an abrupt change caused by the earthquake. The first-order northern co-seismic GGCs had a strong suppressive effect on the north-south strip error. GRACE-FO results showed that the latest post-seismic gravity changes had obvious inherited development characteristics, and that the west coast of Chile maybe still affected by the post-seismic effect. The cumulative gravity changes simulated based on viscoelastic dislocation model is approximately consistent with the longer-term GRACE and the newest GRACE-FO observations. Our results provide important reference for understanding temporal and spatial gravity variations associated with the co-seismic and post-seismic processes of the 2010 Maule earthquake.
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34

Ellmer, Matthias, and Torsten Mayer-Gürr. "High precision dynamic orbit integration for spaceborne gravimetry in view of GRACE Follow-on." Advances in Space Research 60, no. 1 (July 2017): 1–13. http://dx.doi.org/10.1016/j.asr.2017.04.015.

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35

Misfeldt, Malte, Vitali Müller, Laura Müller, Henry Wegener, and Gerhard Heinzel. "Scale Factor Determination for the GRACE Follow-On Laser Ranging Interferometer Including Thermal Coupling." Remote Sensing 15, no. 3 (January 18, 2023): 570. http://dx.doi.org/10.3390/rs15030570.

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The GRACE follow-on satellites carry the very first interspacecraft LRI. After more than four years in orbit, the LRI outperforms the sensitivity of the conventional MWI. However, in the current data processing scheme, the LRI product still needs the MWI data to determine the unknown absolute laser frequency, representing the “ruler” for converting the raw phase measurements into a physical displacement in meters. In this paper, we derive formulas for precisely performing that conversion from the phase measurement into a range, accounting for a varying carrier frequency. Furthermore, the dominant errors due to knowledge uncertainty of the carrier frequency as well as uncorrected time biases are derived. In the second part, we address the dependency of the LRI on the MWI in the currently employed cross-calibration scheme and present three different models for the LRI laser frequency, two of which are largely independent of the MWI. Furthermore, we analyze the contribution of thermal variations on the scale factor estimates and the LRI-MWI residuals. A linear model called Thermal Coupling (TC) is derived, which significantly reduces the differences between LRI and MWI to a level where the MWI observations limit the comparison.
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Wei, Linyong, Shanhu Jiang, Liliang Ren, Hongbing Tan, Wanquan Ta, Yi Liu, Xiaoli Yang, Linqi Zhang, and Zheng Duan. "Spatiotemporal changes of terrestrial water storage and possible causes in the closed Qaidam Basin, China using GRACE and GRACE Follow-On data." Journal of Hydrology 598 (July 2021): 126274. http://dx.doi.org/10.1016/j.jhydrol.2021.126274.

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37

Guo, Yi, Fuping Gan, Baikun Yan, Juan Bai, Feng Wang, Ruirui Jiang, Naichen Xing, and Qi Liu. "Evaluation of Groundwater Storage Depletion Using GRACE/GRACE Follow-On Data with Land Surface Models and Its Driving Factors in Haihe River Basin, China." Sustainability 14, no. 3 (January 19, 2022): 1108. http://dx.doi.org/10.3390/su14031108.

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Groundwater storage (GWS) in the Haihe River Basin (HRB), which is one of the most densely populated and largest agricultural areas in China, is of great importance for the ecosystem environment and socio-economic development. In recent years, large-scale overexploitation of groundwater in HRB has made it one of the global hotspots of GWS depletion. In this study, monthly GWS variations in HRB from 2003 to 2020 were estimated using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) data in combination with three land surface models (LSMs) from the Global Land Data Assimilation System (GLDAS). The results show the following: (1) HRB suffered extensive GWS depletion from 2003 to 2020, which has been aggravated since 2014, with a mean rate of 1.88 cm·yr−1, which is equivalent to a volume of 6 billion m3·yr−1. The GWS depletion is more serious in the plain zone (−2.36 cm·yr−1) than in the mountainous zone (−1.63 cm·yr−1). (2) Climate changes are excluded from the reasons for GWS depletion due to annual precipitation and evaporation being close to normal throughout the period. In addition, GWS changes show a low correlation with meteorological factors. (3) The consumption of groundwater for irrigation and land use/cover changes have been confirmed to be the dominant factors for GWS depletion in HRB. (4) The effects of inter-basin water transfer projects cannot be obviously observed using the GRACE and GRACE-FO; more inter-basin water transfers are needed for recovering the GWS in HRB. Therefore, it is imperative to control groundwater exploitation and develop a more economical agricultural irrigation structure for the sustainability of groundwater resources in HRB.
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38

Mohajerani, Yara, David Shean, Anthony Arendt, and Tyler C. Sutterley. "Automated Dynamic Mascon Generation for GRACE and GRACE-FO Harmonic Processing." Remote Sensing 13, no. 16 (August 7, 2021): 3134. http://dx.doi.org/10.3390/rs13163134.

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Commonly used mass-concentration (mascon) solutions estimated from Level-1B Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On data, provided by processing centers such as the Jet Propulsion Laboratory (JPL) or the Goddard Space Flight Center (GSFC), do not give users control over the placement of mascons or inversion assumptions, such as regularization. While a few studies have focused on regional or global mascon optimization from spherical harmonics data, a global optimization based on the geometry of geophysical signal as a standardized product with user-defined points has not been addressed. Finding the optimal configuration with enough coverage to account for far-field leakage is not a trivial task and is often approached in an ad-hoc manner, if at all. Here, we present an automated approach to defining non-uniform, global mascon solutions that focus on a region of interest specified by the user, while maintaining few global degrees of freedom to minimize noise and leakage. We showcase our approach in High Mountain Asia (HMA) and Alaska, and compare the results with global uniform mascon solutions from range-rate data. We show that the custom mascon solutions can lead to improved regional trends due to a more careful sampling of geophysically distinct regions. In addition, the custom mascon solutions exhibit different seasonal variation compared to the regularized solutions. Our open-source pipeline will allow the community to quickly and efficiently develop optimized global mascon solutions for an arbitrary point or polygon anywhere on the surface of the Earth.
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39

Wei, ZHENG, HSU Hou-Tse, ZHONG Min, and YUN Mei-Juan. "Precise Recovery of the Earth's Gravitational Field by Grace Follow-On Satellite Gravity Gradiometry Method." Chinese Journal of Geophysics 57, no. 3 (May 2014): 269–79. http://dx.doi.org/10.1002/cjg2.20102.

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40

Nigatu, Zemede M., Dongming Fan, Wei You, and Assefa M. Melesse. "Hydroclimatic Extremes Evaluation Using GRACE/GRACE-FO and Multidecadal Climatic Variables over the Nile River Basin." Remote Sensing 13, no. 4 (February 11, 2021): 651. http://dx.doi.org/10.3390/rs13040651.

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Hydroclimatic extremes such as droughts and floods triggered by human-induced climate change are causing severe damage in the Nile River Basin (NRB). These hydroclimatic extremes are not well studied in a holistic approach in NRB. In this study, the Gravity Recovery and Climate Experiment (GRACE) mission and its Follow on mission (GRACE-FO) derived indices and other standardized hydroclimatic indices are computed for developing monitoring and evaluation methods of flood and drought. We evaluated extreme hydroclimatic conditions by using GRACE/GRACE-FO derived indices such as water storage deficits Index (WSDI); and standardized hydroclimatic indices (i.e., Palmer Drought Severity Index (PDSI) and others). This study showed that during 1950–2019, eight major floods and ten droughts events were identified based on standardized-indices and GRACE/GRACE-FO-derived indices. Standardized-indices mostly underestimated the drought and flood severity level compared to GRACE/GRACE-FO derived indices. Among standardized indices PDSI show highest correlation (r2 = 0.72) with WSDI. GRACE-/GRACE-FO-derived indices can capture all major flood and drought events; hence, it may be an ideal substitute for data-scarce hydro-meteorological sites. Therefore, the proposed framework can serve as a useful tool for flood and drought monitoring and a better understanding of extreme hydroclimatic conditions in NRB and other similar climatic regions.
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41

He, Meilin, Wenbin Shen, Jiashuang Jiao, and Yuanjin Pan. "The Interannual Fluctuations in Mass Changes and Hydrological Elasticity on the Tibetan Plateau from Geodetic Measurements." Remote Sensing 13, no. 21 (October 24, 2021): 4277. http://dx.doi.org/10.3390/rs13214277.

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The mass balance of water storage on the Tibetan Plateau (TP) is a complex dynamic system that has responded to recent global warming due to the special regional characteristics and geographical environment on the TP. In this study, we present global positioning system (GPS), gravity recovery and climate experiment (GRACE) and follow-on (FO) observations obtained during the 2002–2020 period to identify hydrological changes on the TP. The spatial long-term trends in the GRACE/GRACE-FO data show continuous glacier mass losses around the Himalayas and accumulated mass on the inner TP due to the increased water mass in lakes. The singular spectrum analysis (SSA) was applied for interpolation of the data gap with GRACE/GRACE-FO. We evaluated the correlation between the vertical displacements obtained from 214 continuous GPS stations and GRACE/GRACE-FO-modeled water mass loads and found a high correlation, with spatial variabilities associated with the seasonal terrestrial water storage (TWS) pattern. The common-mode component obtained from continuous GPS coordinates was decomposed using principal component analysis (PCA) and presented different periodic signals related to interannual fluctuations in hydrology and the dynamics of the inner Earth. Moreover, the various characteristics of precipitation and temperature revealed similar interannual fluctuations to those of the El Niño/Southern Oscillation. We conclude that the GPS-inferred interannual fluctuations and the corresponding GRACE/GRACE-FO-modeled hydrological loads reflect climate responses. These findings shed light on the complex role of the spatiotemporal climate and water mass balance on the TP since the beginning of the 21st century.
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42

Sutterley, Tyler C., and Isabella Velicogna. "Improved Estimates of Geocenter Variability from Time-Variable Gravity and Ocean Model Outputs." Remote Sensing 11, no. 18 (September 10, 2019): 2108. http://dx.doi.org/10.3390/rs11182108.

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Geocenter variations relate the motion of the Earth’s center of mass with respect to its center of figure, and represent global-scale redistributions of the Earth’s mass. We investigate different techniques for estimating of geocenter motion from combinations of time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On missions, and bottom pressure outputs from ocean models. Here, we provide self-consistent estimates of geocenter variability incorporating the effects of self-attraction and loading, and investigate the effect of uncertainties in atmospheric and oceanic variation. The effects of self-attraction and loading from changes in land water storage and ice mass change affect both the seasonality and long-term trend in geocenter position. Omitting the redistribution of sea level affects the average annual amplitudes of the x, y, and z components by 0.2, 0.1, and 0.3 mm, respectively, and affects geocenter trend estimates by 0.02, 0.04 and 0.05 mm/yr for the the x, y, and z components, respectively. Geocenter estimates from the GRACE Follow-On mission are consistent with estimates from the original GRACE mission.
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43

Tangdamrongsub, Natthachet, and Michal Šprlák. "The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation." Remote Sensing 13, no. 2 (January 12, 2021): 235. http://dx.doi.org/10.3390/rs13020235.

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The vertical motion of the Earth’s surface is dominated by the hydrologic cycle on a seasonal scale. Accurate land deformation measurements can provide constructive insight into the regional geophysical process. Although the Global Positioning System (GPS) delivers relatively accurate measurements, GPS networks are not uniformly distributed across the globe, posing a challenge to obtaining accurate deformation information in data-sparse regions, e.g., Central South-East Asia (CSEA). Model simulations and gravity data (from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO)) have been successfully used to improve the spatial coverage. While combining model estimates and GRACE/GRACE-FO data via the GRACE/GRACE-FO data assimilation (DA) framework can potentially improve the accuracy and resolution of deformation estimates, the approach has rarely been considered or investigated thus far. This study assesses the performance of vertical displacement estimates from GRACE/GRACE-FO, the PCRaster Global Water Balance (PCR-GLOBWB) hydrology model, and the GRACE/GRACE-FO DA approach (assimilating GRACE/GRACE-FO into PCR-GLOBWB) in CSEA, where measurements from six GPS sites are available for validation. The results show that GRACE/GRACE-FO, PCR-GLOBWB, and GRACE/GRACE-FO DA accurately capture regional-scale hydrologic- and flood-induced vertical displacements, with the correlation value and RMS reduction relative to GPS measurements up to 0.89 and 53%, respectively. The analyses also confirm the GRACE/GRACE-FO DA’s effectiveness in providing vertical displacement estimates consistent with GRACE/GRACE-FO data while maintaining high-spatial details of the PCR-GLOBWB model, highlighting the benefits of GRACE/GRACE-FO DA in data-sparse regions.
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44

Xie, Jingkai, Yue-Ping Xu, Hongjie Yu, Yan Huang, and Yuxue Guo. "Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data." Hydrology and Earth System Sciences 26, no. 22 (November 25, 2022): 5933–54. http://dx.doi.org/10.5194/hess-26-5933-2022.

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Abstract. Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-on (GRACE-FO) satellite provide terrestrial water storage anomaly (TWSA) estimates globally that can be used to monitor flood in various regions at monthly intervals. However, the coarse temporal resolution of GRACE and GRACE-FO satellite data has been limiting their applications at finer temporal scales. In this study, TWSA estimates have been reconstructed and then temporally downscaled into daily values based on three different learning-based models, namely a multi-layer perceptron (MLP) model, a long-short term memory (LSTM) model and a multiple linear regression (MLR) model. Furthermore, a new index incorporating temporally downscaled TWSA estimates combined with daily average precipitation anomalies is proposed to monitor the severe flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The results indicated that (1) the MLP model shows the best performance in reconstructing the monthly TWSA with root mean square error (RMSE) = 10.9 mm per month and Nash–Sutcliffe efficiency (NSE) = 0.89 during the validation period; (2) the MLP model can be useful in temporally downscaling monthly TWSA estimates into daily values; (3) the proposed normalized daily flood potential index (NDFPI) facilitates robust and reliable characterization of severe flood events at sub-monthly timescales; (4) the flood events can be monitored by the proposed NDFPI earlier than traditional streamflow observations with respect to the YRB and its individual subbasins. All these findings can provide new opportunities for applying GRACE and GRACE-FO satellite data to investigations of sub-monthly signals and have important implications for flood hazard prevention and mitigation in the study region.
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45

Yang, Xu, Xiaoqian Zhu, Libin Weng, and Shenggao Yang. "A New Exospheric Temperature Model Based on CHAMP and GRACE Measurements." Remote Sensing 14, no. 20 (October 17, 2022): 5198. http://dx.doi.org/10.3390/rs14205198.

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In this study, the effective exospheric temperature, derived from CHAMP and GRACE density measurements during 2002–2010, was utilized to develop a new exospheric temperature model (ETM) with the aid of the NRLMSIS 2.0 empirical model. We characterized the dominant modes of global exospheric temperature using the principal component analysis (PCA) method, and the first five derived empirical orthogonal functions (EOFs) captured 98.2% of the total variability. The obtained mean field, first five EOFs and the corresponding amplitudes were applied to build ETM using the polynomial method. The ETM and NRLMSIS 2.0 models were independently validated by the SWARM-C and GRACE Follow-On (GRACE-FO) density measurements. ETM can reproduce thermospheric density much better than the NRLMSIS 2.0 model, and the Root Mean Square Errors (RMSE) of ETM predictions were approximately 26.45% and 26.17% for the SWARM-C and GRACE-FO tests, respectively, while they were 39.52% and 44.41% for the NRLMSIS 2.0 model. In addition, ETM can accurately capture the equatorial thermospheric anomaly feature, seasonal variation and hemispheric asymmetry in the thermosphere.
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46

Godah, Walyeldeen, Jagat Dwipendra Ray, Malgorzata Szelachowska, and Jan Krynski. "The Use of National CORS Networks for Determining Temporal Mass Variations within the Earth’s System and for Improving GRACE/GRACE-FO Solutions." Remote Sensing 12, no. 20 (October 15, 2020): 3359. http://dx.doi.org/10.3390/rs12203359.

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Temporal mass variations within the Earth’s system can be detected on a regional/global scale using GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On (GRACE-FO) satellite missions’ data, while GNSS (Global Navigation Satellite System) data can be used to detect those variations on a local scale. The aim of this study is to investigate the usefulness of national GNSS CORS (Continuously Operating Reference Stations) networks for the determination of those temporal mass variations and for improving GRACE/GRACE-FO solutions. The area of Poland was chosen as a study area. Temporal variations of equivalent water thickness ΔEWT and vertical deformations of the Earth’s surface Δh were determined at the sites of the ASG-EUPOS (Active Geodetic Network of the European Position Determination System) CORS network using GRACE/GRACE-FO-based GGMs and GNSS data. Moreover, combined solutions of ΔEWT were developed by combining ΔEWT obtained from GNSS data with the corresponding ones determined from GRACE satellite mission data. Strong correlations (correlation coefficients ranging from 0.6 to 0.9) between detrended Δh determined from GRACE/GRACE-FO satellite mission data and the corresponding ones from GNSS data were observed at 93% of the GNSS stations investigated. Furthermore, for the determination of temporal mass variations, GNSS data from CORS network stations provide valuable information complementary to GRACE satellite mission data.
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47

Scudiero, Fernando, Luca Arcari, Luca Cacciotti, Elena De Vito, Rossella Marcucci, Ilaria Passaseo, Luca Rosario Limite, et al. "Prognostic relevance of GRACE risk score in Takotsubo syndrome." European Heart Journal: Acute Cardiovascular Care 9, no. 7 (October 23, 2019): 721–28. http://dx.doi.org/10.1177/2048872619882363.

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Background: Takotsubo syndrome is an increasingly recognised cardiac condition that clinically mimics an acute coronary syndrome, but data regarding its prognosis remain controversial. It is currently unknown whether acute coronary syndrome risk scores could effectively be applied to Takotsubo syndrome patients. This study aims to assess whether the Global Registry of Acute Coronary Events (GRACE) score can predict clinical outcome in Takotsubo syndrome and to compare the prognosis with matched acute coronary syndrome patients. Methods: A total of 561 Takotsubo syndrome patients was included in this prospective registry. According to the GRACE score, the population was divided into quartiles. The primary endpoint was all-cause mortality and the secondary endpoints were cardiocerebrovascular events (a composite of all-cause mortality, cardiovascular death, recurrence of Takotsubo syndrome and stroke). Results: The median GRACE risk score was 139±27. Takotsubo syndrome patients with a higher GRACE risk score mostly have a higher rate of physical triggers and lower left ventricular ejection fraction on admission. During long-term follow-up, all-cause mortality rates were 5%, 11%, 12% and 22%, respectively, in the first, second, third and fourth quartile ( P<0.001). After multivariate analysis, the GRACE risk score was found to be a strong predictor of all-cause mortality (odds ratio (OR) 1.68, 95% confidence interval (CI) 1.28–2.20; P=0.001) and cardiocerebrovascular events (OR 1.63, 95% CI 1.26–2.11; P=0.001). Moreover, all-cause mortality in Takotsubo syndrome patients was comparable with the matched acute coronary syndrome cohort. Conclusion: In Takotsubo syndrome, the GRACE risk score allows us to predict all-cause mortality and cardiocerebrovascular events at long-term follow-up.
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48

Bezděk, Aleš, Josef Sebera, João Teixeira da Encarnação, and Jaroslav Klokočník. "Time-variable gravity fields derived from GPS tracking of Swarm." Geophysical Journal International 205, no. 3 (March 7, 2016): 1665–69. http://dx.doi.org/10.1093/gji/ggw094.

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Abstract Since 2002 Gravity Recovery and Climate Experiment (GRACE) provides monthly gravity fields from K-band ranging (KBR) between two GRACE satellites. These KBR gravity monthlies have enabled the global observation of time-varying Earth mass signal at a regional scale (about 400 km resolution). Apart from KBR, monthly gravity solutions can be computed from onboard GPS data. The newly reprocessed GPS monthlies from 13 yr of GRACE data are shown to yield correct time-variable gravity signal (seasonality, trends, interannual variations) at a spatial resolution of 1300 km (harmonic degree 15). We show that GPS fields from new Swarm mission are of similar quality as GRACE GPS monthlies. Thus, Swarm GPS monthlies represent new and independent source of information on time-variable gravity, and, although with lower resolution and accuracy, they can be used for its monitoring, particularly if GRACE KBR/GPS data become unavailable before GRACE Follow-On is launched (2017 August).
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Koch, Alexander, Josep Sanjuan, Martin Gohlke, Christoph Mahrdt, Nils Brause, Claus Braxmaier, and Gerhard Heinzel. "Line of sight calibration for the laser ranging interferometer on-board the GRACE Follow-On mission: on-ground experimental validation." Optics Express 26, no. 20 (September 19, 2018): 25892. http://dx.doi.org/10.1364/oe.26.025892.

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50

Śliwińska, Justyna, Małgorzata Wińska, and Jolanta Nastula. "Exploiting the Combined GRACE/GRACE-FO Solutions to Determine Gravimetric Excitations of Polar Motion." Remote Sensing 14, no. 24 (December 12, 2022): 6292. http://dx.doi.org/10.3390/rs14246292.

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Observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions can be used to estimate gravimetric excitation of polar motion (PM), which reflects the contribution of mass changes in continental hydrosphere and cryosphere to PM variation. Many solutions for Earth’s gravity field variations have been developed by institutes around the world based on GRACE/GRACE-FO data; however, it remains inconclusive which of them is the most reliable for the determination of PM excitation. In this study, we present a combined series of GRACE/GRACE-FO-based gravimetric excitation of PM computed using the three-cornered-hat (TCH) method, wherein the internal noise level in a combined solution is reduced to a minimum. We compare the combined series with results obtained from the combined GRACE/GRACE-FO solution provided by COST-G (International Combination Service for Time-variable Gravity Fields) and from the single solution elaborated by the Center for Space Research (CSR). All the gravimetric excitation series are evaluated by comparison with the sum of hydrological and cryospheric signals in geodetically observed PM excitation (called GAO). The results show that by minimizing the internal noise level in the combined excitation series using the TCH method, we can receive higher consistency with GAO than in the case of COST-G and CSR solutions, especially for the non-seasonal oscillations. For this spectral band, we obtained correlations between GAO and the best-combined series as high as 0.65 and 0.72 for the χ1 and χ2 equatorial components of PM excitation, respectively. The corresponding values for seasonal oscillation were 0.91 for χ1 and 0.89 for χ2. The combined series developed in this study explain up to 68% and 60% of overall GAO variability for χ1 and χ2, respectively.
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