Acta Geodaetica et Cartographica Sinica ›› 2021, Vol. 50 ›› Issue (3): 333-342.doi: 10.11947/j.AGCS.2021.20200386

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Data quality assessment of time-varying terrestrial gravity observation in South China

YANG Jinling1,2, CHEN Shi1,3, WANG Linhai1, LU Hongyan1,3, LI Honglei1,3, ZHANG Bei1,3   

  1. 1. Institute of Geophysics, China Earthquake Administration, Beijing 100081, China;
    2. Fujian Earthquake Agency, Fuzhou 350003, China;
    3. Beijing Baijiatuan Earth Science National Observation and Research Station, Beijing 100095, China
  • Received:2020-08-20 Revised:2021-01-15 Published:2021-03-31
  • Supported by:
    The National Key Research and Development Program of China (Nos. 2018YFC0603502;2017YFC1500503);The National Natural Science Foundation of China (Nos. 41774090;U1939205);Science Foundation of Institute of Geophysics, CEA from the Ministry of Science and Technology of China(Nos. DQJB19A0121;DQJB20X09);The Spark Program and Youth Seismic Regime Tracking Project of China Earthquake Administration (Nos. XH18023Y;2020010210)

Abstract: The terrestrial time-varying microgravity observation can be used to study the crustal mass transfer. The uncertainty of the gravity instrument is an important factor that can easily affect the data quality of gravity observations. In this paper, we focus on the time-varying gravity dataset from 2015 to 2018 in South China. Based on Bayesian analysis method, we quantify the related uncertainty sources of the gravity instruments, including the nonlinear drift of relative gravimeter and the change of scale factor of gravimeter. Furthermore, the cross-validation of the absolute gravity in-situ observation in network is applied to assess the gravity data results using this new approach. The results show that the uncertainty caused by the scale factor is larger than that caused by nonlinear drift for the relative gravimeters used in the South China survey network. The magnitude can reach up to 20×10-8 m/s2 for gravity change. Nevertheless, this uncertainty can be effectively reduced by means of the Bayesian method and absolute gravity datum control. This study can be used to assess the data quality of terrestrial gravity observation, to understand the causes of gravity change, and analysis the great earthquake preparation and mass transfer, etc.

Key words: microgravity observation, Bayesian analysis, cross-validation, absolute gravity, scale factor

CLC Number: