Improved GRACE regional mass balance estimates of the Greenland ice sheet cross-validated with the input–output method

• Published in: The Cryosphere
• Main Authors: Xu, Zheng, Schrama, Ernst J. O., van der Wal, Wouter, van den Broeke, Michiel, Enderlin, Ellyn M.
• Format: Text
• Language: English
• Published: 2018
• Subjects: Greenland; Ice Sheet
• Online Access: https://doi.org/10.5194/tc-10-895-2016; https://tc.copernicus.org/articles/10/895/2016/

In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass change of the Greenland ice sheet (GrIS) and neighboring glaciated regions using a least squares inversion approach. We also consider results from the input–output method (IOM). The IOM quantifies the difference between the mass input and output of the GrIS by studying the surface mass balance (SMB) and the ice discharge ( D ). We use the Regional Atmospheric Climate Model version 2.3 (RACMO2.3) to model the SMB and derive the ice discharge from 12 years of high-precision ice velocity and thickness surveys. We use a simulation model to quantify and correct for GRACE approximation errors in mass change between different subregions of the GrIS, and investigate the reliability of pre-1990s ice discharge estimates, which are based on the modeled runoff. We find that the difference between the IOM and our improved GRACE mass change estimates is reduced in terms of the long-term mass change when using a reference discharge derived from runoff estimates in several subareas. In most regions our GRACE and IOM solutions are consistent with other studies, but differences remain in the northwestern GrIS. We validate the GRACE mass balance in that region by considering several different GIA models and mass change estimates derived from data obtained by the Ice, Cloud and land Elevation Satellite (ICESat). We conclude that the approximated mass balance between GRACE and IOM is consistent in most GrIS regions. The difference in the northwest is likely due to underestimated uncertainties in the IOM solutions.