Evaluating surface mass balance variability from climate models using GPS Bedrock Vertical Time Series data

Accurate estimates of Antarctic Surface Mass Balance (SMB) are essential for quantifying ice-sheet mass changes and their contributions to global sea level rise. Regional Climate Models (RCMs) and atmospheric reanalyses provide SMB products that are widely used in glaciology and climatology studies, yet substantial discrepancies between models persist. This study evaluates interannual to decadal variability in seven SMB models by comparing computed SMB elastic vertical bedrock displacements with GPS vertical timeseries from across Antarctica. The models vary in spatial and temporal resolution: RACMO2.3p2 (27 km), RACMO2.4p1 (11 km), statistically downscaled RACMO2.3p2 (2 km), MAR (35 km), GEMB (10 km), HIRHAM5 (12.5 km) and MERRA2 (12.5 km). Model performance is assessed through the quantification of low-frequency variance reduction in GPS residuals after SMB loading correction and by computing scale factors between the observed and model time series. Results indicate that all considered SMB models reduce long-period (>1.5 years) GPS variance on average, but performance varies across Antarctic regions and GPS sites. All RACMO variants, specifically the higher-resolution variants (2 and 11 km) show better performance overall, achieving typically the largest variance reductions and yielding scale factors closest to unity, particularly in the Antarctic Peninsula and coastal margin of Antarctica; MERRA2 and HIRHAM5 have the weakest overall performance. Our findings suggest that GPS observations, with some limitations, provide a useful new constraint on SMB model evaluation that yields insights into spatial and temporal variabilities that traditional SMB model evaluations are unable to fully resolve.