Dataset for publication: "Three decades of GNSS-derived geocenter motion: disentangling geophysical signal from systematic errors"

This dataset contains two combined geocenter time series solutions (V3M and V7D) that serve as supplementary data to the article "Three decades of GNSS-derived geocenter motion: disentangling geophysical signal from systematic errors" currently under review in Advances in Space Research. The solutions are derived from a comprehensive analysis of ten International GNSS Service (IGS) Analysis Centers spanning three decades (1994-2025). Dataset Components: V3M Solution: Combined geocenter series using 3-month sliding window for variance component estimation V7D Solution: Combined geocenter series using 7-day sliding window for variance component estimation Data Structure: GPS Week: GPS week number Day of GPS Week: Day within the GPS week (0-6) MJD: Modified Julian Date ISO Date: Date in ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ) X, Y, Z: Geocenter coordinates in millimeters XE, YE, ZE: Formal errors for X, Y, Z components in millimeters Methodology: The combined solutions are produced using Förstner's variance component estimation method, which optimally weights contributions from individual IGS Analysis Centers (COD, ESA, GFZ, GRG, JPL, MIT, NGS, TUG, ULR, WHU). Key Features: Spans three processing periods: IGS Repro3, IGS Repro3 extension, and operational IGS20 products Includes GPS, GLONASS, and Galileo constellation data Demonstrates strong agreement with independent techniques (SLR, LEO) at seasonal timescales (correlations >0.8) Provides parameter-level combination alternative to normal equation-based approaches Coordinate System: Solutions referenced to IGSR3 TRF (1994-2022) and IGS20 TRF (2022-2025) Units: Coordinates and uncertainties in millimeters (mm) Temporal Resolution: Daily estimates with different combination window lengths This dataset supports research in geodesy, geophysics, Earth system science, and reference frame applications, particularly for studies requiring high-quality geocenter motion estimates with reduced systematic errors. Note: This dataset accompanies a manuscript currently under peer review and provides the combined geocenter solutions analyzed in the research paper.