The data set consists of digital elevation models (DEM) of subglacial topography, ice thickness, bathymetry and ice surface elevation of Kongsfjorden, northwestern Svalbard, near Ny-Ålesund (78.9 deg N, 12.4 deg E). The DEMs cover five tide-water glaciers with a grid size of 150 m. The data have a total area of ~1100 km^2 and cover the glaciers Blomstrandbreen, Conwaybreen, Kongsbreen, Kronebreen, and Kongsvegen, including the ice fields Holtedahlfonna and Isachsenfonna. A 50 m resolution DEM is also available for Kronebreen. The compiled data set covers one of the most studied regions in Svalbard and can be valuable for studies of glacier dynamics, geology, hydrology and fjord circulation. For further details see Lindbäck et al. (2018, https://doi.org/10.5194/essd-2018-37). If you use the data set in presentations and publications please also refer to the peer-reviewed paper (Lindbäck et al., 2018, https://doi.org/10.5194/essd-2018-37). The data set will be updated when the quality of the data is improved or if new data sets become available. File format: GeoTIFF and ASCII Spatial reference: WGS-1984 UTM Zone 33W Contact person: Jack Kohler (jack.kohler@npolar.no) This work was part of the TIGRIF (Tidewater Glacier Retreat Impact on Fjord circulation and ecosystems) project, funded by the Research Council of Norway.

In the period between the austral summers of 1982/83 to 1997/98, iceberg observations were recorded by most research vessels cruising Antarctic waters, under an international programme for systematic collection of Antarctic iceberg data initiated by The Norwegian Polar Institute (NPI) in 1981 with the endorsement of the Scientific Committee on Antarctic Research (SCAR). The resulting database contains records of 323 520 iceberg positions from 26 634 individual observations. Of these, 262 007 icebergs have been classified by size into five different length categories: 10-50, 50-200, 200-500, 500-1000 and ˃1000 m. The database also includes 8061 additional iceberg observations collected by the Australian National Antarctic Research Expeditions ships from 1984 (AAD), operating in the 50-150° E longitude sector. Some of these have been classified by slightly different size categories. For this reason, the complete database has been packaged in three separate csv files: - one file containing the entire NPI database, including AAD observations 1978-1984 - one file containing the 8061 additional AAD observations 1984-2010 - one file containing 970 AAD observations 1978-1984, also included in the NPI data file The dataset is described in detail in the attached data report, with an overview of the contents of the database and their potential use, the data quality and quality control process, and some concluding remarks on iceberg occurrence and distribution around Antarctica; drift patterns, dissolution rates, calving rates and their contribution to the mass balance of Antarctica. During the three decades of observations, most of the ocean around Antarctica has been observed, but there are large differences in data density, primarily because nearly all ship tracks follow repeated routes to the various research stations, and these are not evenly located around the continent.  Figure 1: The 34 695 individual observations in the SCAR database shown as blue dots for the NPI data collection scheme with 5 classes and red for the AAD data with 7 classes (described in subsequent sections). The red dots overprint and hide many blue dots.

Tidal glacier fronts in Svalbard are mapped using Landsat 8 orthorectified imagery. Fronts are determined for places where the ice is apparently in contact with seawater. This might not be 100% correct: there are some places where there may be sediment emerging, but if this can’t be seen clearly in the L8 image the glacier front is retained as being “in contact”, especially if it is only a short stretch.

Datasets collected during TW-ICE cruise to Kongsfjorden in July 2017. The datasets contain measurements close to glacier fronts taken with a research vessel and helicopter, and have been published in Halbach et al. (2019; see the "Citation Custom" field). The datasets are compiled following files: **Nutrient data.csv** Nutrient measurements together with station metadata. Columns: station = station name; vessel = either the research vessel (Lance) or helicopter; lon = longitude as decimal degrees (WGS84); lat = latitude as decimal degrees (WGS84); date = date in ISO8601 format; area = zone used in the article; dist = distance from the closest glacier front in km; depth = bottom depth in m at the station; from = the water depth from which the sample was collected in m; sal = salinity from the closest CTD; temp = water temperature from the closest CTD; type = water type classification based on salinity and temperature (see the article); ctd.name = name of the closest CTD cast; chla = chlorophyll a in mg m-3; phaeo = phaeophytin in mg m-3; tsm = total suspended matter in g m-3; no2 = nitrite concentration in mmol m-3; no3 = nitrate concentration in mmol m-3; sioh4 = silicate concentration in mmol m-3; po4 = phosphate concentration in mmol m-3; nh4 = ammonium concentration in mmol m-3; urea = urea concentration in mmol m-3. **Phytoplankton data.csv** Phytoplankton taxonomy data together with station metadata. Columns: station = station name; lon = longitude as decimal degrees (WGS84); lat = latitude as decimal degrees (WGS84); date = date in ISO8601 format; area = zone used in the article; dist = distance from the closest glacier front in km; depth = bottom depth in m at the station; from = the water depth from which the sample was collected in m; sal = salinity from the closest CTD; temp = water temperature from the closest CTD; type = water type classification based on salinity and temperature (see the article); ctd.name = name of the closest CTD cast; group = coarse functional grouping; species = species or taxa; abundance = abundance of the species in cells dm-3. **CTD data.json** CTD data in a list format. See the [oce-class](https://www.rdocumentation.org/packages/oce/versions/1.0-1/topics/ctd-class) documentation for the `oce` R package for further details on formatting. The results are from a Sea-Bird SBE 9 (Lance) and Hydro-Bios Multi-Water-Sampler (helicopter). **Water type data.csv** Water type classification data together with station metadata. Columns: row_id = unique ID for a CTD cast; station = station name; vessel = either the research vessel (Lance) or helicopter; lon = longitude as decimal degrees (WGS84); lat = latitude as decimal degrees (WGS84); date = date in ISO8601 format; area = zone used in the article; depth = bottom depth in m at the station; ctd.name = name of the closest CTD cast; type = water type classification based on salinity and temperature (see the article); freq = frequency of 1 decibar bins containing the given water type; per = percentage of 1 decibar bins containing the given water type as compared to total number of bins for a CTD cast. **Mixed layer data.csv** Mixed layer data. Columns: station = station name; ctd.name = name of the closest CTD cast; pres = pressure of the maximum N2 bin in decibars; sal = salinity at the maximum N2 depth; temp = water temperature at the maximum N2 depth in Celsius; rho = potential water density at the maximum N2 depth; n2 = the maximum Brunt-Väisälä-frequency during CTD cast close to the surface; mld = estimated mixed layer depth based on maximum N2 in m. **Euphotic depth data.csv** Euphotic depth data. Columns: station = station name; depth = depth of the estimated euphotic depth in m; par = photosynthetically active radiation at the euphotic depth; spar = photosynthetically active radiation on the surface; per = percentage ratio between par and spar.

This is an umbrella (metadata-only) dataset that provides links to all individual datasets collected during the Norwegian young sea ICE expedition (N-ICE2015). The metadata is available in [DCAT (JSON-LD)](http://api.npolar.no/dataset/?q=&filter-sets=N-ICE2015&format=json&variant=ld) and as [DIF XML via OAI-PMH](http://api.npolar.no/dataset/oai?verb=ListRecords&metadataPrefix=dif&set=N-ICE2015). For humans: The NPDC dataset catalogue contains a searchable [list of N-ICE2015 datasets](https://data.npolar.no/dataset/?filter-sets=N-ICE2015).

Quantarctica is a collection of Antarctic geographical datasets which works with the free, cross-platform, open-source software QGIS. It includes community-contributed, peer-reviewed data from ten different scientific themes and a professionally-designed basemap.