WHU‐GRACE‐GPD01s: A Series of Constrained Monthly Gravity Field Solutions Derived From GRACE‐Based Geopotential Differences

Zhong, Bo; Li, Xianpao; Chen, Jianli; Li, Qiong

doi:10.1029/2022ea002699

Cited by 6 publications

(3 citation statements)

References 67 publications

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“…In Table 2, regardless of the filtering strategies employed, Tongji-Acc RL06 generally exhibits comparable mean annual amplitudes as the other three models. As in previous studies, the annual amplitudes calculated based on the CSR RL06 in the Amazon and Murray River Basins are 20.0 cm and 2.1 cm, respectively, aligning with the findings of this paper [69]. In Table 3, the trend estimates from Tongji-Acc RL06 are in good agreement with those from the other three models as well.…”

Section: Mass Variation Signal In River Basin and Land-ice Areassupporting

confidence: 89%

“…Particularly, when using P4M6 decorrelation filtering and 300 km Gaussian smoothing, the trends over the Gulf of Alaska and Greenland are estimated to be −2.9 ± 0.2 cm/year and −6.8 ± 0.3 cm/year for Tongji-Acc RL06, respectively. The result of −6.8 ± 0.3 cm/year for Greenland demonstrates a strong consistency with the trend estimate of −6.7 ± 0.2 cm/year by Zhong et al (2023) [69]. Considering the significant noise characteristics in desert areas [70,71], we selected the Sahara Desert and the Karakum Desert as two examples for analyzing the noise in different gravity field solutions.…”

Section: Mass Variation Signal In River Basin and Land-ice Areassupporting

confidence: 55%

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An Improved Acceleration Approach by Utilizing K-Band Range Rate Observations

Shen,

Chen,

Shen

2023

Remote Sensing

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During gravity field modeling, the conventional acceleration approach rarely incorporates KBR inter-satellite range rate data from the GRACE mission. To propose an improved acceleration method, this study introduces initial orbital position and velocity vectors to be estimated along with a combination of Cowell, KSG, and Adams integrators. In addition to achieving a full-rank design matrix regarding orbit corrections when constructing observation equations, the proposed method is capable of utilizing range rate observations for gravity field estimation. To verify the reliability of this approach, GRACE data from April 2002 to December 2016 was used to calculate a time series of monthly gravity solutions up to a degree and order of 96, referred to as Tongji-Acc RL06 in this paper. The computed time series are compared with the official models (i.e., CSR RL06, GFZ RL06, and JPL RL06) in terms of geoid degree variances, signal contents over distinct areas, and noise levels in desert regions. The investigations lead to the following conclusions: (a) the geoid degree variances indicate that Tongji-Acc RL06 exhibits comparable signal levels (approximately below 20 degrees) to the other three models while demonstrating lower noise at higher degrees (above 40 degrees); (b) the analysis over the globe, typical river basins, and land–ice regions illustrates that the solutions derived using the proposed acceleration method agree well with the official models based on the dynamic approach; (c) especially over the two large-scale river basins (i.e., Amazon and Zambezi) and another two small-scale river basins (i.e., Tennessee and Irrawaddy), Tongji-Acc RL06 significantly improves the SNR values; and (d) in the cases of the Sahara and Karakum deserts, Tongji-Acc RL06 achieves noise reductions of over 55.8% and 61.5% relative to CSR RL06, respectively. In general, the signal and noise analyses demonstrate that the proposed acceleration-based approach can effectively extract gravity field signals from KBR inter-satellite range rate observations with improved SNR, while significantly reducing the high-frequency noise.

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Section: Mass Variation Signal In River Basin and Land-ice Areassupporting

confidence: 89%

Section: Mass Variation Signal In River Basin and Land-ice Areassupporting

confidence: 55%

An Improved Acceleration Approach by Utilizing K-Band Range Rate Observations

Shen,

Chen,

Shen

2023

Remote Sensing

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“…The new generation of GRACE observation data products: Mascon products which are provided by the Center for Space Research at University of Texas (CSR), NASA Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). These Mascon products are solved in a couple of ways, which include the regularization methods for the monthly gravity field solutions (one type is the post-processing (Klees et al, 2008;Swenson and Wahr, 2011) and the other is solving along with the least-squares estimation (Chen et al, 2021;Zhong et al, 2023). Firstly, the commonly used Gaussian smoothing with a certain radius was proposed by Wahr et al (1998), whose smoothing kernel function was constructed based on the degrees of SH coefficients.…”

Section: Introductionmentioning

confidence: 99%

Terrestrial water storage changes over 25 global river basins extracted by local mean decomposition from GRACE Monthly Gravity Field solutions

Huan¹

2023

Acta Geodynamica Et Geomaterialia

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The strong striping and high-frequency noise existed in Gravity Recovery and Climate Experiment (GRACE) solutions drowned the real geophysical signals, which need other signal extraction methods. Considering the advantages of local mean decomposition (LMD) in extracting geophysical signals from noisy time series, we adopt it to filter the noise and estimate the terrestrial water storage (TWS) changes over 25 global main river basins from the time series of 14-year (2002.04~2016.08) Release 06 (RL06) monthly gravity field models provided by Center for Space Research (CSR), together with the empirical mode decomposition (EMD) as a comparison. To evaluate the efficiency of eliminating noise by LMD and EMD, the ratios of the latitude weighted RMS over the land and ocean signals are adopted. The results show that all RMS ratios of land relative to ocean signals derived by LMD are higher than EMD with the mean values 3.4458 and 3.3302, respectively. Moreover, relative to the Global Land Data Assimilation System (GLDAS) Noah model, the extracted TWS changes by LMD approach have smaller root mean squared errors than EMD over 25 global river basins. Therefore, it is reasonable to conclude that LMD approach outperforms EMD in extracting TWS changes and filtering out the strong noise existed in GRACE monthly gravity field solutions.

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Evaluating the weekly changes in terrestrial water storage estimated by two different inversion strategies in the Amazon River Basin

Zhong,

Li,

et al. 2023

Geodesy and Geodynamics

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WHU‐GRACE‐GPD01s: A Series of Constrained Monthly Gravity Field Solutions Derived From GRACE‐Based Geopotential Differences

Cited by 6 publications

References 67 publications

An Improved Acceleration Approach by Utilizing K-Band Range Rate Observations

An Improved Acceleration Approach by Utilizing K-Band Range Rate Observations

Terrestrial water storage changes over 25 global river basins extracted by local mean decomposition from GRACE Monthly Gravity Field solutions

Evaluating the weekly changes in terrestrial water storage estimated by two different inversion strategies in the Amazon River Basin

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