Spatio-Temporal Patterns of Accumulation and Surface Roughness in Interior Greenland with a GNSS-IR Network

Abstract. The dry snow zone is the largest region of the Greenland Ice Sheet, yet temporally and spatially dense observations of surface accumulation and surface roughness in this area are lacking. We use the global navigation satellite system (GNSS) interferometric reflectometry (GNSS-IR) technique with a novel, low-cost GNSS network of twelve stations in the vicinity of the ice sheet summit to reveal temporal and spatial patterns of accumulation of the upper snow layer. We show that individual measurements are highly precise (±2.8 cm), while the aggregate of hundreds of daily measurements across a large spatial footprint can detect millimeter-level surface changes and are biased by -2.7 ± 3.0 cm compared to a unique validation dataset that covers a similar spatial extent as the instrument sensing footprint. Using the validation dataset, we find that the reflectometry technique is most sensitive to the surrounding 4–20 m of the surface, with the antenna at a height of 1–2 m above ground level. Along with an exceptionally high rate of accumulation at the beginning of the study, we also detect an across-slope dependence in accumulation rates at yearly timescales. For the first time, we also validate GNSS-IR sensitivity to meter-scale surface heterogeneities such as sastrugi, and we construct a time series of seasonal surface roughness evolution that may hint at a seasonal pattern of heightened wintertime roughness features in this region. These surface accumulation and roughness measurements provide a novel dataset for these critical variables and show a statistically significant (p < 0.01) relationship with occurrences of both high winds and precipitation events, but only moderate correlations, suggesting other processes must also contribute to accumulation and enhanced surface roughness in the interior region of Greenland.