ALBERT

Description: Processed GNSS data of four stations at 79°N Glacier (Nioghalvfjerdsbraeen Glacier) in northeast Greenland from 2017 (see link in "Further details"). The GNSS data were processed using the GIPSY-OASIS software Package with high-precision kinematic data processing methods (Nettles et al., 2008) with ambiguity resolution using Jet Propulsion Laboratory (JPL)'s orbit and clock products, constraint on kinematic position solution. We use the GIPSY-OASIS version 6.4 developed at JPL, and released in January 2020 (Bertiger et al., 2020). We use JPL final orbit products which include satellite orbits, satellite clock parameters and Earth orientation parameters. The orbit products take the satellite antenna phase center offsets into account. The atmospheric delay parameters are modelled using the Vienna Mapping Function 1 (VMF1) with VMF1grid nominals (Boehm et al., 2006). Corrections are applied to remove the solid Earth tide and ocean tidal loading. The amplitudes and phases of the main ocean tidal loading terms are calculated using the Automatic Loading Provider (http://holt.oso.chalmers.se/loading/) applied to the FES2014b (Lyard et al., 2006) ocean tide model including correction for centre of mass motion of the Earth due to the ocean tides. The site coordinates are computed in the IGS14 frame (Altamimi et al., 2016). We convert the Cartesian coordinates at 5 min intervals to local up, north and east for each GNSS site monitored at the surface of the 79°N Glacier. In addition, we use Waypoint GravNav 8.8 processing software. We applied kinematic PPP processing using precise satellite orbits and clocks. The site coordinates are computed in the IGS14 frame and converted to WGS84 during data export at 15 seconds interval. To avoid jumps between daily solutions of the Waypoint PPP product, as the data is recorded in daily files, we merged three successive files prior to processing to enable full day overlaps. In a second step, the 3-day solutions are combined using relative point to point distances. To avoid edge effects, we combined the files in the middle of each 1-day overlap and removed outliers. The data were re-sampled to 5 min interval to match the GIPSY-OASIS product.