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.
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.
We present an ice-free (bedrock) topography of the Svalbard archipelago based on a two-step mass-conserving approach for mapping glacier ice thickness. The Svalbard-wide application is presented in Fürst et al. (2018) and details of the mass-conserving reconstruction approach are specified in Fürst et al. (2017). For the thickness reconstruction more than one million individual measurements were considered. The map is provided together with an error-estimate field, which provides first spatial information on the reliability of the reconstruction.
Each binary NetCDF file contains four variables, x, y, grid-mapping, and one variable specific to the file.
The x, y, grid-mapping variables define the Universal Transverse Mercator (UTM) projection of the data.
For Svalbard zone 33 was used. Results are presented on a 100-m resolution. For all files, -9999 signifies no data.
The following list provides the file names, the file-specific variable, and descriptions.
1. svift_v11_thickness.nc [ meters ] --- thi --- reconstructed ice thickness field 2. svift_v11_bed.nc [ meters above sea level ] --- bed --- bed elevation of both the ice-free and the ice-covered areas (above EGM96) 3. svift_v11_error.nc [ meters ] --- err --- Associated error estimates from a formal propagation of input uncertainties 4. svift_v11_distance.nc [ meters ] --- dist --- Distance of each raster cell to nearest thickness measurement Versions v1.1 --- Averaging in terms of ice viscosity. For SVIFT1.1, the inferred ice volume on Svalbard is 20% larger than reported in v1.0. This difference arises from the many small glaciers without thickness measurements on the main island of Spitsbergen. Yet, only small differences are seen for well-surveyed glaciers. On Nordaustlandet, which accommodates two large ice caps with a dense measurement network, the volume difference is only ~2% (3291km3 in SVIFT1.1 as compared to 3221km3 in SVIFT1.0). The number of glacier with a mean thickness of less than 25m reduces significantly with respect to SVIFT1.0. This is in better agreement with other independent estimates. v1.0 --- Original submission. For unsurveyed glaciers, rate factor values are averaged for each glacier that shows direct thickenss measurements.
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.