Método alternativo para mejorar los modelos de campo gravitacional al incorporar información del satélite explorador de la circulación oceánica y de gravedad

Translated title of the contribution: An alternative method to improve gravity field models by incorporating goce gradient data

Xiaoyun Wan, Jiangjun Ran

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
100 Downloads (Pure)

Abstract

The aim of this paper is to present an alternative method that can be used to improve existing gravity field models via the application of gradient data from Gravity field and Ocean Circulation Explorer (GOCE). First, the proposed algorithm used to construct the observation equation is presented. Then methods for noise processing in both time and space domains aimed at reducing noises are introduced. As an example, the European Improved Gravity model of the Earth by New techniques (EIGEN5C) is modified with gradient observations over the whole lifetime of the GOCE, leading to a new gravity field model named as EGMGOCE (Earth Gravitational Model of GOCE). The results show that the cumulative geoid difference between EGMGOCE and EGM08 is reduced by 4 centimeters compared with that between EIGEN5C and Earth Gravitational Model 2008 (EGM08) up to 200 degrees. The large geoid differences between EGMGOCE and EIGEN5C mainly exist in Africa, South America, Antarctica and Himalaya, which indicates the contribution from GOCE. Compared to the newest GOCE gravity field model resolved by direct method from European Space Agency (ESA), the cumulative geoid difference is reduced by 7 centimeters up to 200 degrees.
Translated title of the contributionAn alternative method to improve gravity field models by incorporating goce gradient data
Original languageSpanish
Pages (from-to)187 - 193
Number of pages7
JournalEarth Sciences Research Journal
Volume22
Issue number3
DOIs
Publication statusPublished - 2019

Keywords

  • Gravity gradients
  • Model modification
  • Noise processing
  • Radial gravity gradient

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