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.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
The file contains time series of meteorological near-surface parameters measured on a temporary meteorological mast on the southern side of the coast of Adventdalen, Svalbard, from July to August 2022: Both temperature, humidity, wind speed, wind direction were measured at two levels.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, University of Bergen, University of Bergen, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
A scanning Doppler Lidar was placed in Adventdalen (Central Spitsbergen, Svalbard, Norway) close to the permanent weather mast SN99870. The Lidar measured between 4 July and 23 August 2022 with different scanning patterns in an hourly cycle. The cycle consisted of three Plan Position Indicator (PPI) scans at 1, 5 and 10 degree from xx:00 to xx:10, Range Height Indicator (RHI) scans alternating between up-valley and down-valley direction from xx:10 to xx:50, Doppler-Beam-Swinging (DBS) technique from xx:50 to xy:00. The radial resolution was 10 m with overlapping range gates of 50 m. Short periods of power cuts were encountered. Frequently there were conditions with little backscatter and low carrier-to-noise ratio, especially in light down-valley winds.
Spatiotemporal variability in mortality and growth of fish larvae and zooplankton in the Lofoten-Barents Sea ecosystem, The Nansen Legacy (SVIM, NLEG)
Institutions: Institute of Marine Reseach - Norway, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2024-01-03T11:42:12Z
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Abstract:
The SVIM archive contains results from an ocean and sea ice hindcast. The original version of the archive covered the period 1960-2011, and has later been extended on several occasions. The results are provided on a 4km polar stereographic grid projection, and the ocean model has a vertical resolution of 32 s layers. The focus is an adequate representation of the Atlantic influenced water masses within the Nordic Seas and the Barents Sea. Less emphasize has been put on the areas downstream of the Arctic bound Atlantic Water flow, i.e. the Arctic Ocean and the Greenland Sea. There were multiple aims for this product, including (1) process studies within physical oceanography, (2) representation of oceanographic conditions for other applications such as primary production models and individual-based models for zoo- and ichtyoplankton, (3) boundary values for smaller scale model studies. For ocean circulation the Regional Ocean Modeling System (ROMS; https://www.myroms.org/) was used (v.3.2 up to and including September 2018, v.3.5 thereafter). The sea-ice model used is similar to the module described in Budgell (Ocean Dyn. 2005). Boundary values for the ocean model were derived from the Simple Ocean Data Assimilation dataset (SODA v.2.1.6), while boundary values for the sea ice conditions were taken from a regional simulation (Sandø et al., JGR 2012). After 2008, the ocean boundaries were forced with monthly climatologies from 2000-2008, while for ice conditions after 2007, the 2000-2007 monthly climatologies were used. Tidal forcing was based on the global ocean tides model TPXO4. The quality of the model results for the original archive period were assessed by Lien et al. (2013; https://www.hi.no/resources/publikasjoner/fisken-og-havet/2013/fh_7-2013_swim_til_web.pdf).
Spatiotemporal variability in mortality and growth of fish larvae and zooplankton in the Lofoten-Barents Sea ecosystem, The Nansen Legacy (SVIM, NLEG)
Institutions: Institute of Marine Reseach - Norway, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2024-01-03T11:42:12Z
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Abstract:
The SVIM archive contains results from an ocean and sea ice hindcast. The original version of the archive covered the period 1960-2011, and has later been extended on several occasions. The results are provided on a 4km polar stereographic grid projection, and the ocean model has a vertical resolution of 32 s layers. The focus is an adequate representation of the Atlantic influenced water masses within the Nordic Seas and the Barents Sea. Less emphasize has been put on the areas downstream of the Arctic bound Atlantic Water flow, i.e. the Arctic Ocean and the Greenland Sea. There were multiple aims for this product, including (1) process studies within physical oceanography, (2) representation of oceanographic conditions for other applications such as primary production models and individual-based models for zoo- and ichtyoplankton, (3) boundary values for smaller scale model studies. For ocean circulation the Regional Ocean Modeling System (ROMS; https://www.myroms.org/) was used (v.3.2 up to and including September 2018, v.3.5 thereafter). The sea-ice model used is similar to the module described in Budgell (Ocean Dyn. 2005). Boundary values for the ocean model were derived from the Simple Ocean Data Assimilation dataset (SODA v.2.1.6), while boundary values for the sea ice conditions were taken from a regional simulation (Sandø et al., JGR 2012). After 2008, the ocean boundaries were forced with monthly climatologies from 2000-2008, while for ice conditions after 2007, the 2000-2007 monthly climatologies were used. Tidal forcing was based on the global ocean tides model TPXO4. The quality of the model results for the original archive period were assessed by Lien et al. (2013; https://www.hi.no/resources/publikasjoner/fisken-og-havet/2013/fh_7-2013_swim_til_web.pdf).
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
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Abstract:
The daily analysis of sea ice concentration is obtained from
operational satellite images of the polar regions. It is based on
atmospherically corrected signal and a carefully selected sea ice
concentration algorithm. This product is freely available from the
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI
SAF). The Eumetsat identifier for the product is OSI-401.
License : All intellectual property rights of the OSI SAF products belong to EUMETSAT. The use of these products is granted to every interested user, free of charge. If you wish to use these products, EUMETSAT's copyright credit must be shown by displaying the words "copyright (year) EUMETSAT" on each of the products used.
Access: Open
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
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Abstract:
The daily analysis of sea ice concentration is obtained from
operational satellite images of the polar regions. It is based on
atmospherically corrected signal and a carefully selected sea ice
concentration algorithm. This product is freely available from the
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI
SAF). The Eumetsat identifier for this product is OSI-401.
License : All intellectual property rights of the OSI SAF products belong to EUMETSAT. The use of these products is granted to every interested user, free of charge. If you wish to use these products, EUMETSAT's copyright credit must be shown by displaying the words "copyright (year) EUMETSAT" on each of the products used.
Access: Open
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway
Last metadata update: 2024-01-19T11:29:43Z
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Abstract:
An X-ray scan of Priapulopsis bicaudatus. Sample collected by Bodil Bluhm in field (2019-08-16), preserved in 70% EtOH, then stored as a voucher specimen at The Arctic University Museum of Norway with collection number TSZY 427. Before scanning the specimen was encapsuled in wax, then imaged in a Zeiss Xradia Versa 620.
The dataset contains 2 archives. The first archive contains all data (saved as netCDF files) relative to the Figures presented in Boutin et al. (2023). The second archive contains monthly averaged fields (saved as netCDF files) of the simulation described in Boutin et al. (2023). They include quantities relative to sea ice properties (icemod files) and to the mass balance (ice growth/melt etc... simba files). They cover the north Atlantic and the Arctic Ocean (north of Bering Strait) for the period 2000-2018.
icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018.Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment).transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport.In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.
On Svalbard, the long-lasting snow cover and the timing of the snowmelt is a crucial factor in the yearly cycle of all land ecosystems. To monitor the timing and patterns of snow melt, automatic camera systems have been set up at three locations overlooking key research areas near Ny-Ålesund, Svalbard. All images are provided in daily resolution, and the date coded in the filename as yyyy-MM-dd. This work was funded by SMACS (project no. 236768 / E10; Svalbard Science Forum, Research Council of Norway). ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.846617"!
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegain Infrastructure for Research Data (NIRD)
A set of auroral all-sky images captured over Svalbard in 2019-2020. Images contain auroral emission and have been automatically classified for auroral morphology. Morphological classes are included.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-12-11T08:39:51Z
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Abstract:
The SENTINEL-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band synthetic aperture radar imaging, enabling them to acquire imagery regardless of the weather.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-12-11T07:15:25Z
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Abstract:
The SENTINEL-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band synthetic aperture radar imaging, enabling them to acquire imagery regardless of the weather.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-12-11T08:40:13Z
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Abstract:
The SENTINEL-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band synthetic aperture radar imaging, enabling them to acquire imagery regardless of the weather.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-12-11T08:40:12Z
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Abstract:
The SENTINEL-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band synthetic aperture radar imaging, enabling them to acquire imagery regardless of the weather.