The core partner data centres that are integrated in NorDataNet are listed in https://www.nordatanet.no/en/node/69. In addition to this NorDataNet harvests information on relevant datasets from a number of other data centres. The data centre responsible for the data presented is usually (but not always) listed in the discovery metadata. In essence NorDataNet is an aggregating service that combines information from a number of existing data centres.
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source:
Research Council of Norway, project number 245967/F50, Norwegian Scientific Data Network.
Always remember to cite data when used!
Citation information for individual datasets is often provided in the metadata. However, not all datasets have this information embedded in the discovery metadata. On a general basis a citation of a dataset include the same components as any other citation:
author, title,
year of publication,
publisher (for data this is often the archive where it is housed),
edition or version,
access information (a URL or persistent identifier, e.g. DOI if provided)
All partner repositories of NorDataNet support Digital Object Identifiers (DOI), but not all datasets are minted. Whether or not minted depends often on source of the data (e.g. operational data are often yet not minted). However, all data centres support persistent identifiers according to local systems. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
Brief user guide
The Data Access Portal has information in 3 columns. An outline of the content in these columns is provided above. When first entering the search interface, all potential datasets are listed. Datasets are indicated in the map and results tabulation elements which are located in the middle column. The order of results can be modified using the "Sort by" option in the left column. On top of this column is normally relevant guidance information to user presented as collapsible elements.
If the user want to refine the search, this can be done by constraining the bounding box search. This is done in the map - the listing of datasets is automatically updated. Date constraints can be added in the left column. For these to take effect, the user has to push the button marked search. In the left column it is also possible to specific text elements to search for in the datasets. Again pushing the button marked "Search" is necessary for these to take action. Complex search patterns can be constructed using logical operators identified in the drop down menu with and phrases embedded in quotation marks. Prefixing a phrase with '-' negates the phrase (i.e. should not occur in the results). Searches are case insensitive.
Other elements indicated in the left and right columns are facet searches, i.e. these are keywords that are found in the datasets and all datasets that contain these specific keywords in the appropriate metadata elements are listed together. Further refinement can be done using full text, date or bounding box constraints. Individuals, organisations and data centres involved in generating or curating the datasets are listed in the facets in the right column. The combination of search fields (including facets) is based on a logical "AND" combination of the fields, i.e. all conditions are fulfilled for the results provided.
Snow depth, snow water equivalent and basal ice thickness measurements were taken during the SIOS SnowPilot campaign in Spring 2022. Snowpits were dug on GPR profile crossings in the Fuglebekken and Revdalen catchments in the Hornsund fiord, Spitsbergen catchment. Snow density was measured with an IG PAS snow tube, and snow depth and basal ice (ice forming on the ground surface) thickness were measured with an avalanche probe.
The ACS_Bayelva_class dataset contains 302 high-resolution binary snow cover images that were obtained by classifying orthrorectified photographs of a 1.77 km^2 area of interest in the Bayelva catchment. This catchment is close to Ny-Ålesund, the northernmost permanent civilian settlement in the world and a major hub for polar research, in the Norwegian high-Arctic Svalbard archipelago. The imagery has a (roughly) daily temporal resolution and a ground sampling distance (pixel spacing) of 0.5 m. The dataset spans 6 snowmelt seasons, covering the months May-August for the period 2012-2017. The orthophotos were obtained by processing oblique time-lapse photographs taken by a terrestiral automatic camera system (ACS) mounted at 562 m a.s.l. near the summit of Scheteligfjellet (719 m a.s.l.) a few kilometers west of Ny-Ålesund. The orthophotos were manually classified into binary snow cover images (0=no snow, 1=snow) by iteratively selecting a (visually) optimal threshold on the intensity in the blue band for each image. More details are provided in the study of Aalstad et al. (2020) [a copy is available in this repository] where this dataset was created. The ACS was maintained by scientists from the group of Sebastian Westermann at the Section for Physical Geography and Hydrology in the Department of Geosciences at the University of Oslo, Oslo, Norway.
Aerosol size distribution measurements at the Polish Polar Station Hornsund, during the 2021 spring fieldwork (25.04-15.05). Data obtained by TSI particle spectrometer: NanoScan SMPS Nanoparticle Sizer 3910. Measurements carried out in specially prepared container (‘environmental house’) in the Fuglebekken catchment, located approximately in 500 m distance from the main base building. Data gaps occur due to repeated device failure.
Field measurements of aerosol vertical distribution carried out in Hornsund area, during the 2021 spring fieldwork. Data obtained using TSI P-Trak ultrafine particle counter 8525, capable of detecting aerosol particles with a size of 0.02 to 1 micrometer.
Aerosol size distribution measurements at the Polish Polar Station Hornsund, during the 2021 spring fieldwork (25.04-15.05). Data obtained by PMS7003 particle concentration sensor. The device was installed in a fixed position on the roof of a specially prepared container (‘environmental house’) in the Fuglebekken catchment, located approximately in 500 m distance from the main base building.
Aerosol size distribution measurements at the Polish Polar Station Hornsund, during the 2021 spring fieldwork (25.04-15.05). Data obtained by TSI particle spectrometer: Optical Particle Sizer (OPS) Model 3330. Measurements carried out in specially prepared container (‘environmental house’) in the Fuglebekken catchment, located approximately in 500 m distance from the main base building.
The dataset shows the total thickness of sediments deposited on the continental margin south and west of Norway during the Quaternary (the last 2,6 million years). The thickness is presented in milliseconds to-way traveltime (ms twt). 1 ms twt corresponds approximately 1 m in Quaternary sediments. The dataset is a raster-file (tiff), 1000m-grid.
Upwelling and downwelling longwave and shortwave radiation and shortwave albedo from station deployed out on the ice floe, nearby surface meteorology observations.
WP2
Quality
Albedo data is on a different time step and is a heavily processed version of a subset of the the radiation data, see attributes in the NetCDF files and the READMEs:
Dataset of annual mass balances of Svenbreen, a small valley glacier in Central Spitsbergen, 2010/2011 - 2017/2018
To date (31st Jan 2020), the data have not been published in an article in a peer-reviewed journal, which is planned for 2021 or 2022, following the completion of ten years of measurements. It is possible that the exact values might differ slightly between this dataset and the planned paper due to differences in methodology, eg. updated glacier hypsometries. If this dataset is of your interest, please check Jakub Malecki’s publication record for the most up-to-date data..
Quality
Annual mass balance of Svenbreen has been measured with a glaciological method since 2010/2011, typically between 1st and 15th day of September every year. Ablation stake network comprises 12-16 stakes distributed along the glacier tongue and in two (out of three) high-elevation sections, i.e. in the cirque and along an ice patch leading towards neighbouring glacier Hoelbreen.
The dataset is an improved, high resolution ice shelf freeboard, thickness and draught product for Ekström, Jelbart, Fimbul, Vigrid and Nivlisen ice shelves in Dronning Maud Land, East Antarctica. It is based on high resolution (8 m) digital elevation model (DEM) strips from WorldView stereo-satellite image pairs used to create the Reference Elevation Model of Antarctica (REMA) mosaic (Howat et al., 2019). The standard mosaic product suffers from artifacts where ice shelf features such as rifts, the surface expressions of basal channels or crevasses, and the calving front are discontinuous as a result of the advection of features with ice flow between the time of different image acquisitions. Here, NASA ITS_LIVE ice flow velocity mosaics (Gardner et al., 2018) and the ArcMap/Python Warp tool were used to shift DEM tiles up or down the glacier flow field to a common reference date (based on the austral summer maximal DEM coverage of the grounding zone), then corrected for elevation biases and tilts in the vertical dimension using the offsets to CryoSat-2 derived Point of Closest Approach elevations (Gray et al., 2015; 2017), before being mosaicked. WGS84 ellipsoidal heights were converted to freeboard using the EIGEN6C4 geoid (Förste et al., 2014) and an ocean Mean Dynamic Topography of -1.3 m (Andersen et al., 2015). Freeboard was converted to thickness and draught using the assumption of hydrostatic equilibrium (density of ice 917 kg/m^3, density of seawater 1027.5 kg/m^3) and an upsampled Firn Air Content (FAC) field (Ligtenberg et al., 2011). FAC was limited to 50% of freeboard in some marginal areas and ice filled rifts to prevent physically unrealistic ice thicknesses, an artifact of the oversampling of the FAC field. In addition, some discontinuities of small-scale features may persist.
References:
Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P.: The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665–674, https://doi.org/10.5194/tc-13-665-2019, 2019.
Gardner, A. S., M. A. Fahnestock, and T. A. Scambos, [2020]: ITS_LIVE Regional Glacier and Ice Sheet Surface Velocities: Version 1. Data archived at National Snow and Ice Data Center; https://doi:10.5067/6II6VW8LLWJ7. 2019.
Gray, L., Burgess, D., Copland, L., Demuth, M. N., Dunse, T., Langley, K., and Schuler, T. V.: CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps, The Cryosphere, 9, 1895–1913, https://doi.org/10.5194/tc-9-1895-2015, 2015.
Gray, L., Burgess, D., Copland, L., Dunse, T., Langley, K., and Moholdt, G.: A revised calibration of the interferometric mode of the CryoSat-2 radar altimeter improves ice height and height change measurements in western Greenland, The Cryosphere, 11, 1041–1058, https://doi.org/10.5194/tc-11-1041-2017, 2017.
Förste, C., Bruinsma, S. L., Abrykosov, O., Lemoine, J.-M., Marty, J. C., Flechtner, F., Balmino, G., Barthelmes, F., Biancale, R.: EIGEN-6C4 The latest combined global gravity field model including GOCE data up to degree and order 2190 of GFZ Potsdam and GRGS Toulouse. GFZ Data Services. https://doi.org/10.5880/icgem.2015.1, 2014.
Andersen, O., Knudsen, P., Stenseng, L.: The DTU13 MSS (Mean Sea Surface) and MDT (Mean Dynamic Topography) from 20 Years of Satellite Altimetry. In: Jin, S., Barzaghi, R. (eds) IGFS 2014. International Association of Geodesy Symposia, vol 144. Springer, Cham. https://doi.org/10.1007/1345_2015_182, 2015
Ligtenberg, S. R. M., Helsen, M. M., and van den Broeke, M. R.: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere, 5, 809–819, https://doi.org/10.5194/tc-5-809-2011, 2011.
These datasets contain 100 continuous grids of ice thickness, bed topography, and topographic adjustments to geothermal heat flow in the region surrounding Dome Fuji, East Antarctica. Continuous ice thickness grids were created using publicly available measurement data and sequential gaussian simulation to generate statistically likely values between measurements. The simulation was run 100 times to create the ice thickness grids, which were then used to calculate bed elevation by subtracting from REMA ice surface elevations, and the local topographic impacts on background geothermal heat flow. The results are in raster format (.tif) and are projected in an EPSG: 3031 Antarctic Polar Stereographic coordinate system. The spatial extent is 596000 m to 1020000 m Easting and 816000 m to 1240000 m Northing with cell size 500 m x 500 m (848 columns, 848 rows). Ice-thicknesses are provided in meters and bed elevations are in meters referenced to the WGS84 Ellipsoid.
The data set contains information on weather, sea state, sea ice and icebergs recovered from the logbooks and meteorological journals of three Norwegian vessels during their five voyages to the Southern Ocean and Antarctica. The following information was recovered from the keyed and translated logbooks. Factory ship (FS) Antarctic: sea ice notes, icebergs, meteorological information, state of sea surface. FS Svend Foyn: sea ice notes, icebergs. Research vessel (RV) Norvegia: sea ice notes, icebergs; meteorological information. The observations cover the spring to early fall periods of 1929-1933. Details on data sources, methods used and basic analysis conducted on the data are found in the attached project report file.
Quality
Details on data sources, data analysis and methods are found in the attached project report file. List of files comprising the data set:
SeaIceNotes_Logbook_RV_Norvegia_1929_1930_final.xlsx Sea ice and iceberg observations from the third expedition of RV Norvegia to the SO and Antarctic.
SeaIceNotes_Weather_Logbook_FS_Antarctic_1930_final.xlsx Sea ice, icebergs and weather observations from FS Antarctic during the whaling season of 1929-1930 (only 1930 covered).
SeaIceNotes_Weather__Logbook_FS_Antarctic_1930-1931_final.xlsx Sea ice, icebergs and weather observations from FS Antarctic during the whaling season of 1930-1931.
SeaIceNotes_Meteojournal_FS_SvendFoyn1932-1933_final.xlsx Sea ice and iceberg observations from FS Svend Foyn during the whaling season of 1932-1933.
On many glaciers in Svalbard, three surface types are visible on SAR images, the dark glacier ice at the glacier's lower end, the brighter superimposed ice in the middle, and the white firn at the higher elevations. Surface classification of these types is valuable especially since the retreat or advance of the firn area provides information on the status of the glacier. While the snowline reacts immediately to annual changes, the firn area smoothes out these short-term changes and shows, similar to the glacier front, longer-term changes of the glaciers.
Glacier Firn Area Change is based on the "Glacier Surface Type - Svalbard" dataset, presenting the actual area value sper glacier and year as tabular data to be plotted graphically