Using GNSS to derive new information about Greenland and the Greenland Ice Sheet

The Arctic is currently the region most susceptible to global climate change, experiencing the highest relative temperature rise. Furthermore, the possibility of rapid melt of the Greenland Ice Sheet (GrIS) is ranked among the most serious climate threats to our societies, with its potential contribution to global sea level rise regarded especially ominous. Completely melted the GrIS would be the equivalent to ∼7.4 m of global sea level rise. If the current increase in mass loss continues, the Greenland ice sheet alone may account for as much as ∼33 cm of global sea level rise by 2100, which is a significant increase compared to the ∼2.5 cm it contributed during the last century. The increased mass loss from the Greenland ice sheet and the growing interest in predicting future mass loss makes it increasingly important to unearth past climate, monitor the present and improve model predictions. This PhD project contributes to this by showing three new applications of existing Global Navigation Satellite System (GNSS) data that derive new information about Greenland and the GrIS.

In the first study we presented a novel method to estimate the dynamic ice loss of Greenland’s three largest outlet glaciers: Jakobshavn Isbræ, Kangerlussuaq and Helheim. We measured the elastic displacements of the solid Earth caused by dynamic thinning using three Greenland GNSS Network (GNET) stations located near the glacier termini. When we compared our results with discharge, we found a time lag between the onset of dynamic thinning/thickening and glacier speedup/slowdown. Our results showed that dynamic thinning on Jakobshavn Isbræ occur 0.87 ±0.07 years before speedup. This implies that the GNSS time series can be used to predict speedup/slowdown of Jakobshavn Isbræ by up to 10.4 months. For Kangerlussuaq and Helheim the thinning occur 0.37 ±0.17 years (4.4 months) and 0.03 ±0.16 years (11 days) before speed up, respectively.

In the second study, we used tenyear long records of Surface Elevation Change (SEC) derived from three GNSS stations placed in the interior of the GrIS to assess the ability of CryoSat-2radar altimetry to capture SEC during 20102021. We used GNSS Interferometric Reflectometry (GNSSIR) to derive the best possible time series of continuous daily surface elevations. We compared GNSS derived SEC with CryoSat-2 derived SEC and found CryoSat-2 performs best at the northernmost GNSS site with a maximum difference of 12 cm. The strength of assessing satellite radar altimetry against permanent GNSS stations lie in the GNSSIR methods ability to provide a continuous daily time series that capture both longterm and extreme shortterm changes. Furthermore, we calculated the yearly SEC (∂h/∂t) for every available date pair in the GNSS derived surface elevation time series. We found ∂h/∂t varies throughout the year and that an April to April ice sheet wide ∂h/∂t campaign would represent the average ∂h/∂t from GNSS the best.

In the third study we used data from the GNET station at Station Nord (NORD) to demonstrate GNSSIR can be used to derive terrain corrected snow thickness on Greenland bedrock. We identified snow free time periods and used the GNSSIR results to estimate a 360° summer surface topography profile, which we then used as a reference for estimating snow thickness. We found the snow thickness generally increased throughout winter, where the snow surface builds up to an approximately flat surface despite bedrock topography, which results in big differences in snow thickness. Furthermore, we found the distinct pattern of the average snow thickness time series can be used to identify the onset of melt.