Identifying the Basal Sliding Law Using Numerical Modeling and GNSS Observations

Basal sliding is a key process that controls the ice discharge of ice into the ocean. Understanding this process is essential for improving the reliability of future projections of ice sheet evolution and sea level rise. The basal sliding law, which governs ice-bed interactions, remains a critical yet poorly understood process in ice sheet models. Recent advances in transient calibration techniques, which incorporate time series of observed surface velocity and elevation, have enhanced the ability of ice numerical models to infer basal conditions. However, relying on the same type of observational datasets for both model calibration and validation limits the ability to independently evaluate model performance, particularly for future projections. In this study, we introduce an independent observational dataset: measurements from the Global Navigation Satellite Systems (GNSS) collected by Greenland GNSS Network (GNET) stations located along Greenland's coastline. By comparing observed uplift signals with modeled mass change, we can validate model behavior and identify sliding laws most consistent with GNSS data. Here, we illustrate this approach by modeling Helheim and Jakobshavn Glaciers from 2007 to 2022 using three different sliding laws. While all sliding laws produce similar surface velocity patterns consistent with InSAR-derived velocity observations, the patterns of mass change, which control bed uplift, differ significantly. Our analysis reveals that all three sliding laws can reproduce uplift signals consistent with GNSS measurements in terms of inter-annual variability. However, only coulomb-limited sliding laws generate uplift signals consistent with GNSS measurements in multi-annual trends. These results highlight the importance of incorporating multiple independent observational data, such as GNSS, into ice sheet models to refine our understanding of basal sliding laws and reduce uncertainties in predicting future sea level rise.