Data Publications

A GOCE only gravity model GOSG01S based on the SGG and SST observations

hasData_Center_Short_Name
  • Deutsches GeoForschungsZentrum GFZ
hasDataset_Online_Resource
hasDataset_Release_Date
  • 2018
hasDataset_Title
  • A GOCE only gravity model GOSG01S based on the SGG and SST observations
hasEntry_ID
  • 10.5880/icgem.2018.002
hasKeyword
  • ICGEM
  • GOCE
  • Geodesy
  • GOSG01S
hasSummary
  • We compile the GOCE-only satellite model GOSG01S complete to spherical harmonic degree of 220 using Satellite Gravity Gradiometry (SGG) data and the Satellite-to-Satellite Tracking (SST) observations along the GOCE orbit based on applying a least-squares analysis. The diagonal components (Vxx, Vyy, Vzz) of the gravitational gradient tensor are used to form the system of observation equations with the band-pass ARMA filter. The point-wise acceleration observations (ax, ay, az) along the orbit are used to form the system of observation equations up to the maximum spherical harmonic degree/order 130. The GOCE related satellite gravity models GOSG01S, GOTIM05S, GODIR05S, GOTIM04S, GODIR04S, GOSPW04S, JYY_GOCE02S, EIGEN-6C2 and EGM2008 are also validated by using GPS-leveling data in China and USA. According to the truncation at degree 200, the statistic results show that all GGMs have very similar differences at GPS-leveling points in USA, and all GOCE related gravity models have better performance than EGM2008 in China. This new model was developed by School of Geodesy and Geomatics (SGG) of Wuhan University (WHU) and Institute of Geodesy of University of Stuttgart. More details about the gravity field model GOSG01S is given in our paper “A GOCE only gravity model GOSG01S and the validation of GOCE related satellite gravity models ” (Xu X, Zhao Y, Reubelt T, et al. Geodesy and Geodynamics. 2017, 8(4): 260-272. http://dx.doi.org/10.1016/j.geog.2017.03.013). This work is supported by the National Key Basic Research Program of China (973 program, grant no.: 2013CB733301), the Major International (Regional) Joint Research Project (grant no.: 41210006).
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