The data set provides calving front locations of major outlet glaciers of the Greenland Ice Sheet from SAR data from various sensors, produced as part of the ESA Greenland Ice Sheets Climate Change Initiative (CCI) project. Version 1.1 of the dataset has been updated to include information from Sentinel 1 data. The Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, for computing the mass fluxes at the calving gate, and for mapping glacier area change. From the ice velocity at the calving front and the time sequence of Calving Front Locations the iceberg calving rate can be computed which is of relevance for estimating the export of ice mass to the ocean. The calving front location has been derived by manual delineation based on SAR or optical satellite data. The CFL product is a collection of ESRI shapefile in latitude and longitude, on WGS84 projection. The basic data are vector line files (not polygons).

This dataset contains ice velocities for the Greenland northern drainage basin for 1991-1992.This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. This dataset consists of ice velocity maps which have been generated from SAR data from the ERS-1 satellite, for winter 1991-1992. The data is supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system).

This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2015. The surface elevation change data are provided as 2-year means (2011-2012, 2012-2013, 2013-2014 and 2014-2015), and a five-year mean is also provided (2011-2015), along with their associated errors. Data are provided in both NetCDF and gridded ASCII format, as well as png plots. The algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, which has been submitted to Remote Sensing of the Environment.

This dataset contains a time series of ice velocities for the Jakobshavn glacier in Greenland between 2002 and 2010. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. This dataset consists of a time series of ice velocity maps which have been generated from IS mode images from the ASAR instrument on the ENVISAT satellite, with a 35 day repeat cycle, and are supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system).

This dataset contains ice velocities for the Greenland margin for winter 1995-1996. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. This dataset consists of ice velocity maps which have been generated from SAR data from the ERS-2 satellite for winter 1995-1996. The data is supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system).

This dataset is part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project, and provides components of the ice velocity and the magnitude of the velocity for the Greenland Ice Sheet. The dataset is derived from Interferometric Wide Swath SAR data from the Sentinel-1 satellite, acquired in the period from the 1st November 2014 to the 1st December 2015. The ocean mask is based on the GIMP Ocean mask (Version 2.0; Howat et al. 2014), but calving fronts of marine terminating glaciers have been updated using Landsat-8 data acquired from May to August 2015.

This dataset contains ice velocities for the Greenland margin for winter 1995-1996. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. This dataset consists of ice velocity maps which have been generated from PALSAR data on the ALOS satellite for the winters between 2006-2011. The data is supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system).

This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2017. The surface elevation change data are provided as 2-year means (2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, and 2016-2017), and five-year means are also provided (2011-2015, 2012-2016, 2013-2017), along with their associated errors. Data are provided in both NetCDF and gridded ASCII format, as well as png plots. The algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, Remote Sensing of the Environment, 190,pp.207-216, doi:10.1016/j.rse.2016.12.012

This dataset comprises of geochemical, mineralogical and microbiological analyses of material collected on the southwestern margin of the Greenland Ice Sheet in 2016 and 2017. Stream water, melted ice and snow samples were collected and analysed for carbon, nitrogen, phosphorus, cation and anion concentrations, pH, conductivity, total dissolved solids (TDS), mineral phase and class abundances and Rare Earth Elements (REE). Microbial community composition was also analysed. In addition, the results of a nutrient incubation experiment are also presented.The data were collected as part of a project investigating drivers of glacial ice algal growth on the Greenland Ice Sheet. We acknowledge funding from UK Natural Environment Research Council Consortium Grant, Black and Bloom (NE/M020770/1, NE/M021025/1 and NE/S001670/1). LGB and SL acknowledge funding from the German Helmholtz Recruiting Initiative (award number: I-044-16-01). LGB, AMA, and MT were also supported through an ERC Synergy Grant (''Deep Purple'' grant # 856416) from the European Research Council (ERC)

This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from satellite (ERS‐1, ERS‐2, Envisat and Cryosat) radar altimetry. The ice mask is based on the GEUS/GST land/ice/ocean mask provided as part of national mapping projects, and based on 1980’s aerial photography. The data from ERS and Envisat are based on a 5‐year running average, using combined algorithms of repeat‐track (RT), along‐track (AT) or cross‐over (XO) algorithms, and include propagated error estimates. It is important to note that different processing algorithms were applied to the ERS‐1, ERS‐2, Envisat and CryoSat data; for details see the Product User Guide (PUG), available on the CCI website and in the documentation section here. For ERS‐1, the radar data were processed using a cross‐over algorithm (XO) only. For ERS‐2 data and Envisat data in repeat mode, a combination of RT and XO algorithms was applied, followed by filtering. For across‐mission (i.e. ERS‐2‐Envisat) combinations, and for Envisat operating in a drifting orbit, an AT and XO combination was applied (the difference between RT and AT algorithms is that AT use reference tracks and searches for data in the vicinity of this track). For CryoSat data a binning/gridding and plane fit method has been applied, following by weak filtering (0.05 degree resolution).