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: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99710. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99910. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99752. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99765. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99720. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99760. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99790. Data are climate consistent following a number of automated and manual quality control routines.
This data set consists of inferred accumulation rates from three radar layers (26, 35 and 41 thousand years old) in the Vostok Subglacial Lake region. Accumulation rates were inferred using Local-Layer Approximation (LLA), which assumes that the strain-rate history of a particle traveling through the ice sheet can be approximated by the vertical strain-rate profile at the current position of the particle, which the researchers assume to be uniform. Parameters include location, in latitude and longitude, polar stereographic coordinates, and local grid X and Y coordinates, along with layer age, in thousands of years (ka), and inferred accumulation rate (cm/a). The data cover a 150 by 350 km area.
This dataset contains ground-based, co-polarized radar data collected using pulse-modulated 60 MHz and 179 MHz radar at 19 sites around a deep ice coring site near the Ross and Amundsen flow divide of West Antarctic Ice Sheet (WAIS Divide). At each site, the radar data were collected at 12 orientations of the radar polarization plane for three radar pulse widths: 250 nsec, 500 nsec, and 1000 nsec. Useful signals were received from depths roughly between 200 m and 2000 m. Ice flow velocities and strain configurations were measured at most of these radar survey sites, and these ice motion data are also provided at NSIDC (GPS-Measured Ice Velocities and Strain Data from the Ross and Amundsen Sea Ice Flow Divide, West Antarctica).
This product contains ice edge coordinates for the Nordic Seas from 1750 through 2002 for months March through August.
Ice edge in this product is defined as the outer boundary of ice having at least 30% ice concentration. Data are derived from publicly available sea ice products and use observational data from ship logbooks, diaries and other sources in addition to more recent satellite data products from the Scanning Multichannel Microwave Radiometer (SMMR) and the Special Sensor Microwave Imager (SSM/I).
The data are distributed via FTP in ASCII, JPEG, and shapefile format.
Divine, D. V., and C. Dick. 2007. March through August ice edge positions in the Nordic Seas, 1750-2002. Boulder, Colorado USA: National Snow and Ice Data Center. http://dx.doi.org/10.7265/N59884X1
The Norwegian Polar Institute measures mass balance on three glaciers, all in the Kongsfjorden area of north-western Spitsbergen, Svalbard. They are: Austre Brøggerbreen (data since 1967, Midtre Lovénbreen (since 1968) and Kongsvegen (since 1987). The first two are among the longest continuous high arctic glacier mass balance time-series. The Norwegian Polar Institute uses the so-called “combined method”, a mixture of the fixed-date and the stratigraphic methods, and comprises sounding of winter snow depth and repeated measurement of heights of an array of 8-10 stakes along the glacier centerline. Winter balance is obtained by snow-depth soundings over much of the glacier, an estimate of the autumn superimposed ice by shallow ice-cores along the longitudinal axis or at least by a measurement at the bottom of snow pits, stake height measurements, and snow density measurements. The work is carried out at the end of the accumulation period, in May. Stake positions are measured using differential GPS every year to monitor long-term velocity and elevation changes, both of which respond to the yearly mass fluctuations. Summer balance is obtained directly by comparing stake heights made in spring to fall stake measurements. The latter work is usually done at the end of the ablation period (in September and sometimes in October). Balance estimates are extrapolated over the entire glacier basin by using the distribution of glacier area per 50-m elevation band (hypsometry) obtained from maps or digital elevation models (DEMs). Net, winter and summer mass balance values are reported each year to MOSJ and as well to the World Glacier Monitoring Service.
Institutions: University of Oslo - Department of Geosciences
Last metadata update: 2022-04-29T13:30:00Z
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Abstract:
Atmospheric variables needed to force terrestrial process models (permafrost, glacier mass balance, seasonal snow, surface energy balance), have been downscaled from the ERA 40 and ERA interim re-analyses using methodology described in the accompanying paper. The gridded dataset has a horizontal resolution of 1 km and covers the entire Svalbard archipelago. The data have a temporal resolution of 6h and cover the entire ERA40 period (1957-2002) and the ERAinterim period (1979-2016).
Institutions: Norwegian Meteorogical Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-06T10:08:42Z
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Abstract:
Time series of Monthly Mean Sea Ice Extent (SIE) for Global, computed from the EUMETSAT OSI SAF Sea Ice Concentration (SIC) Climate Data Records v2. EUMETSAT OSI SAF data, with Research and Development input from the ESA Climate Change Initiative programme.
Institutions: Norwegian Meteorogical Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-06T10:08:37Z
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Abstract:
Time series of Daily Sea Ice Extent (SIE) for Global, computed from the EUMETSAT OSI SAF Sea Ice Concentration (SIC) Climate Data Records v2. EUMETSAT OSI SAF data, with Research and Development input from the ESA Climate Change Initiative programme.