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author:

Zhu, Fengshun (Zhu, Fengshun.) [1] | Guo, Jinyun (Guo, Jinyun.) [2] | Sun, Yu (Sun, Yu.) [3] | Li, Zhen (Li, Zhen.) [4] | Yuan, Jiajia (Yuan, Jiajia.) [5] | Sun, Heping (Sun, Heping.) [6]

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Abstract:

The Gravity Recovery and Climate Experiment (GRACE) gravity satellites can only detect low-resolution marine gravity change. This study proposes to use satellite altimetry data to construct high-resolution marine gravity change rate (MGCR) model. The marine gravity field change is mainly caused by the seawater mass migration. Based on the spherical harmonic function (SHF) method and mass loading theory, a spherical harmonic synthesis formula is constructed to calculate MGCR. This idea is utilized to establish MGCR model in Arabian Sea (AS). First, the multisatellite altimeter data from 1993 to 2019 are grouped, preprocessed, and utilized to establish mean sea-level models; then, the long-term altimetry sea-level change rate (SLCR) is estimated. Second, the altimetry SLCR subtracts the effects of Steric and Glacial Isostatic Adjustment (GIA) to obtain the SLCR model caused by mass migration (AS-MM-SLCR). Finally, we perform spherical harmonic analysis on AS-MM-SLCR and apply the spherical harmonic synthesis formula to estimate MGCR model on 5′ × 5′ grids (AS-SHF-MGCR). AS-SHF-MGCR has higher resolution than GRACE-MGCR, compensating for inability of GRACE to detect small-scale marine gravity changes; the MGCR mean of AS-SHF-MGCR is 0.13μ Gal/year, which indicates the long-term rising trend of marine gravity in AS. This letter proposes a method for calculating the MGCR using satellite altimetry, which offers a novel approach for marine time-varying gravity research. © 2004-2012 IEEE.

Keyword:

Aneroid altimeters Geodetic satellites Gravitation Harmonic analysis Harmonic functions Sea level Spheres

Community:

  • [ 1 ] [Zhu, Fengshun]Chinese Academy of Sciences, State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology, Wuhan; 430071, China
  • [ 2 ] [Zhu, Fengshun]University of Chinese Academy of Sciences, College of Earth and Planetary Sciences, Beijing; 100049, China
  • [ 3 ] [Guo, Jinyun]Shandong University of Science and Technology, College of Geodesy and Geomatics, Qingdao; 266590, China
  • [ 4 ] [Sun, Yu]Fuzhou University, Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou; 350108, China
  • [ 5 ] [Li, Zhen]Shandong University of Science and Technology, College of Geodesy and Geomatics, Qingdao; 266590, China
  • [ 6 ] [Yuan, Jiajia]Anhui University of Science and Technology, School of Geomatics, Huainan; 232001, China
  • [ 7 ] [Sun, Heping]Chinese Academy of Sciences, State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology, Wuhan; 430071, China
  • [ 8 ] [Sun, Heping]University of Chinese Academy of Sciences, College of Earth and Planetary Sciences, Beijing; 100049, China

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IEEE Geoscience and Remote Sensing Letters

ISSN: 1545-598X

Year: 2024

Volume: 21

4 . 0 0 0

JCR@2023

CAS Journal Grade:3

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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