A combination of Time-Variable Gravity Field Solutions from Multi-Satellite Datasets (1993-2024) via Constrained Collocation Model

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Authors: Lin Zhang, Yunzhong Shen, Nico Sneeuw, Peyman Saemian, Kunpu Ji, Qing Chen, Fengwei Wang
Cited by: 0

Abstract

This dataset provides monthly, gapless, filter-free gravity field solutions from January 1993 to December 2024. The solutions are derived by merging multiple satellite missions (GRACE, SLR, and LEO satellites) using a collocation criterion constrained by Tikhonov regularization, without relying on hydrological or climate models, and achieve higher accuracy than existing gravity field reconstruction methods (e.g., machine learning, EOF, and VCE). Evaluations of sea-level budget closure and water balance at global and basin scales demonstrate substantial improvements. The results agree well with IMBIE estimates of ice-sheet mass change in Antarctica and Greenland, supporting the dataset’s suitability for monitoring Earth’s water and ice systems.

Fields of Study & Subjects

Geophysics and Gravity Measurements GNSS positioning and interference Soil Moisture and Remote Sensing

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
30 January 2026
Language
EN
Document type
Dataset