| 09 Apr 2026
Evaluating Surface Mass Balance Variability from Climate Models using GPS Bedrock Vertical Time Series data
Abstract. 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 yr) 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.
The paper "Evaluating Surface Mass Balance Variability from Climate Models using GPS Bedrock Vertical Time Series Data", by Rajavarathan et al., presents a new approach for assessing the performance of Surface Mass Balance (SMB) models using vertical land motion derived from GPS observations. In this paper, the authors use seven SMB model products to calculate the corresponding loading displacements, which are then compared to GPS as an independent observational reference. The paper suggests that GPS provides a useful constraint on SMB model evaluation, with varying performance between models depending on their resolution and forcing. Interestingly, all SMB-corrected GPS time series consistently show reduced long-period (>1.5 yr) variance on average, but performance varies across Antarctic regions and GPS sites.
The data processing is rigorous, and the discussion of the influence of SMBL on GPS time series, as well as the spectral analysis of residual time series, is adequate. Overall, the study is well executed and contributes valuable insights into estimates of ice-sheet mass variability and its varying contribution to sea-level change. However, a few minor aspects of the analysis require further justification:
- The authors indicate in Section 2.1 that they compute the elastic loading displacements in a centre-of-solid Earth (CE) reference frame at each GPS site location. However, GPS displacement time series are in the centre-of-figure (CF) frame. Although the CE frame closely approximates the CF frame, it is important to acknowledge this potential mismatch in the manuscript.
- The authors also mention that SMB anomalies are bilinearly interpolated onto a common regular grid of 2 km resolution. It would be very complementary to the discussion to address the effect of interpolation, specifically smoothing of the signal versus using the native grid resolution.
- In line 170, it is also worth mentioning that different SMB models adopt different topography grids, which might potentially contribute to spatial coherence variability.