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Greenland Ice Mass Change: Identifying the Drivers Behind the Recent Deceleration in Ice Mass Loss

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Abstract

We derive Greenland ice mass changes from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) mascon solutions and thirty Input-Output Method (IOM) combinations, and conduct a comprehensive comparison for the period 2002–2018. Using mascon solutions as constraints, we identify an optimal IOM combination to estimate the linear and quadratic trends for Greenland ice mass change, which enables us to extend the analysis to 2023. The IOM-estimated ice mass loss rate of −257.7 ± 19.8 Gt·yr−1 closely matches estimates from the three mascon solutions (−258.9 ± 13.2, −264.1 ± 12.0, and −271.8 ± 12.0 Gt·yr−1, respectively), provided by the Center for Space Research (CSR), Goddard Space Flight Center (GSFC), and Jet Propulsion Laboratory (JPL). A deceleration in ice mass losses is observed across all datasets, with rates of 3.2 ± 3.8, 4.5 ± 2.2, 3.8 ± 1.9, and 6.5 ± 2.2 Gt·yr−2 for the IOM combination, CSR, GSFC, and JPL mascon solutions, respectively. Partitioning results suggest that surface mass balance (SMB), solid ice discharge (SID), and peripheral glaciers' mass balance (PGMB) contribute about 41%, 50%, and 9%, respectively, to the total loss, with the deceleration mainly originating from SMB. Further decomposition of SMB reveals that runoff anomaly accounts for 136% of SMB-related ice mass loss, with 37% offset by positive precipitation anomaly. The observed deceleration in Greenland ice mass loss that has only been evident in recent years is temporally coherent with the quadratic increase in cumulative snowfall anomaly (4.1 ± 1.6 Gt·yr-2).

Original languageEnglish
Pages (from-to)14854-14869
Number of pages16
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume19
DOIs
Publication statusPublished - 22 Apr 2026

Keywords

  • GRACE
  • Greenland
  • Satellite geodesy
  • Time-series analysis
  • Time-variable gravity

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science

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