2026-08-09T16:31:16Zhttp://doidb.wdc-terra.org/oaip/oai

oai:doidb.wdc-terra.org:77852026-06-10T10:24:38ZDOIDBDOIDB.ICGEM

false4DOIDB.ICGEM 10.5880/icgem.2023.002 Xu, Xinyu Xinyu Xu 0000-0003-1614-1900 School of Geodesy and Geomatics, Wuhan University, Wuhan, China Li, Jiancheng Jiancheng Li School of Geodesy and Geomatics, Wuhan University, Wuhan, China Zhao, Yongqi Yongqi Zhao 0000-0002-3484-950X School of Geodesy and Geomatics, Wuhan University, Wuhan, China Wei, Hui Hui Wei 0000-0003-4695-5710 School of Geodesy and Geomatics, Wuhan University, Wuhan, China GFZ Data Services 2023 GOSG02S GOCE ICGEM global gravity field model geodesy Xu, Xinyu Xinyu Xu 0000-0003-1614-1900 School of Geodesy and Geomatics, Wuhan University, Wuhan, China Xu, Xinyu Xinyu Xu 0000-0003-1614-1900 School of Geodesy and Geomatics, Wuhan University, Wuhan, China Li, Jiancheng Jiancheng Li School of Geodesy and Geomatics, Wuhan University, Wuhan, China Zhao, Yongqi Yongqi Zhao 0000-0002-3484-950X School of Geodesy and Geomatics, Wuhan University, Wuhan, China Wei, Hui Hui Wei 0000-0003-4695-5710 School of Geodesy and Geomatics, Wuhan University, Wuhan, China Xu, Xinyu School of Geodesy and Geomatics, Wuhan University, Wuhan, China Model http://www.geophy.cn//article/doi/10.6038/cjg2022Q0615 http://icgem.gfz-potsdam.de/ CC BY 4.0 GOSG02S is a static gravity field model complete to spherical harmonic degree and order of 300 derived by using the Satellite Gravity Gradiometry (SGG) data and the Satellite-to-Satellite Tracking (SST) observations along the GOCE orbit based on least-squares analysis.

Input data:

-- GOCE SGG data: EGG_NOM_2 (GGT: Vxx, Vyy, Vzz and Vxz) in GRF (9/10/2009-20/10/2013)
-- GOCE SST data: SST_PKI_2, SST_PCV_2, SST_PRD_2 (9/10/2009-20/10/2013)
-- Attitude: EGG_NOM_2 (IAQ), SST_PRM_2 (PRM)
-- Non-conservative force: Common mode ACC (GG_CCD_1i)
-- Background model: tidal model (solid etc.), third-body acceleration, relativistic corrections, ...
-- GOSG02S is a GOCE only satellite gravity model, since no priori gravity information was used in modelling procedure.


Data progress strategies:

-- Data preprocessing

- Gross outlier elimination and interpolation (only for the data gaps less than 40s).
- Splitting data into subsections for gaps > 40s

-- The normal equation from SST data
- Point-wise acceleration approach (PAA)
- Extended Differentiation Filter (low-pass)
- Max degree: up to 130
- Data: PKI, PCV, CCD

-- The normal equation from SGG data
- Direct LS method
- Max degree: up to 300
- Data: GGT, PRD, IAQ, PRM
- Band-pass filter: used to deal with colored-noise of GGT observations (pass band 0.005-0.100Hz )
- Forming the normal equations according to subsections
- Spherical harmonic base function transformation instead of transforming GGT from GRF to LNRF

-- Combination of SGG and SST
- Max degree: up to 300
- The VCE technique is used to estimate the relative weights for Vxx, Vyy, Vzz and Vxz
- Tikhonov Regularization Technique (TRT) is only applied to near (zonal) terms (m<20, n<=200) and high degree terms (n>200)
- Strictly inverse the normal matrix based on OpenMP