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 automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour. This activity is carried out by the Aldo Pontremoli Centre part of the Joint Research Agreement ENI-CNR.
The Climate Change Tower Integrated Project (CCT-IP) represents the guide lines of the italian research in the arctic and aims to study the interaction between all the components of the climate system in the Arctic. The Amundsen-Nobile Climate Change Tower (CCT) is the key infrastructure of the project, and provides continuous acquisition of the atmospheric parameters at different heights as well as at the interface between the surface and the atmosphere.
30 minutes average (μ) and standard deviation (σ) of meteorological data are available for the download.
Data at resolution of 1 minute are available for online visualization and downloadable under request.
This data set provides digital terrain models, snow depth, and canopy height, acquired by a scanning lidar system and derived from Point Cloud Digital Terrain Models (PCDTMs) from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer’s Loop/Creamer’s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). The raw data from which these data are derived are available as <a href="https://nsidc.org/data/SNEX23_Lidar_Raw">SnowEx23 Airborne Lidar Scans Raw, Version 1</a>.
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of 6-day and 12-day 50 m resolution image mosaics of the Greenland coastline and ice sheet periphery. The mosaics are derived from C-band Synthetic Aperture Radar (C-SAR) acquired by the Copernicus Sentinel-1A and -1B satellites.
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, contains monthly ice velocity mosaics for the Greenland Ice Sheet. The data are derived from Synthetic Aperture Radar (SAR) data, obtained by TerraSAR-X/TanDEM-X and Sentinel-1A and -1B, and from optical imagery acquired by Landsat 8 and Landsat 9.
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, contains 6 and 12 day surface velocity estimates for the Greenland Ice Sheet and periphery. Velocities are derived from images acquired by the European Space Agency (ESA) Copernicus Sentinel-1A and Sentinel-1B satellites.
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, provides velocity estimates determined from Interferometric Synthetic Aperture Radar (InSAR) data for major glacier outlet areas in Greenland, some of which have shown profound velocity changes over the MEaSUREs observation period. The InSAR Selected Glacier Site Velocity Maps are produced from image pairs measured by the German Aerospace Center's (DLR) twin satellites TerraSAR-X / TanDEM-X (TSX / TDX). The measurements in this data set are provided in addition to the ice sheet-wide data from the related data set, <a href="https://nsidc.org/data/nsidc-0478">MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data</a>.
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, contains quarterly (three-month interval) ice velocity mosaics for the Greenland Ice Sheet. This data set is derived from Synthetic Aperture Radar (SAR) data, obtained by TerraSAR-X/TanDEM-X and Sentinel-1A and -1B, and from optical imagery acquired by Landsat 8 and Landsat 9.
This data set presents new global snow cover classification regimes derived from the MODIS Terra cloud gap-filled NDSI data (<a href="https://nsidc.org/data/mod10a1f/versions/61">MOD10A1F</a>), elevation, and temperature climatology inputs. The six data granules are available as NetCDF (.nc) files, with each containing a unique snow cover classification spanning 2001 to 2023. The six classifications included in this data set are: (1) snow class climatology (SSC), (2) core snow season length (CSS), (3) snow cover duration (SCD), (4) full snow season length (FSS), (5) snow persistence (SP), and (6) snow season persistence (SSP).
This data set comprises results from a hybrid glacier evolution model that uses the mass balance module of the Python Glacier Evolution Model (PyGEM) and the glacier dynamics module of the Open Global Glacier Model (OGGM). Output parameters include projections of glacier mass change, fixed runoff, and various mass balance components at regionally aggregated and glacier scales.
This data set provides raw lidar data from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer’s Loop/Creamer’s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). Processed data, including digital terrain models, snow depth, and canopy height derived from Point Cloud Digital Terrain Models (PCDTMs) are available as <a href="https://nsidc.org/data/SNEX23_Lidar">SnowEx23 Airborne Lidar-Derived 0.25M Snow Depth and Canopy Height, Version 1</a>.
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2023-11-04T00:00:00Z
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Abstract:
Ground based in situ observations of ozone at Zeppelin mountain (Ny-Ålesund) (NO0042G) using uv_abs. These measurements are gathered as a part of the following projects EMEP_NRT, GAW-WDCRG_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: ozone in air (mole_fraction_of_ozone_in_air), ozone in air (mass_concentration_of_ozone_in_air)
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2024-03-22T00:00:00Z
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Abstract:
Main greenhouse gases and carbon_monoxide at Birkenes II. These measurements are gathered as a part of the following projects NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), methane in air (mole_fraction_of_methane_in_air), methane in air (mole_fraction_of_methane_in_air), water_vapor in air (mole_fraction_of_water_vapor_in_air), water_vapor in air (mole_fraction_of_water_vapor_in_air)
Institutions: FI03L, University of Helsinki, UHEL, Institute for Atmospheric and Earth System Research (INAR), PO BOX 64, FI-00014, University of Helsinki, Finland, FI03L, University of Helsinki, UHEL, Institute for Atmospheric and Earth System Research (INAR), PO BOX 64, FI-00014, University of Helsinki, Finland
Last metadata update: 2024-01-31T00:00:00Z
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Abstract:
Ground based in situ observations of cpc at Värriö (FI0023R). These measurements are gathered as a part of the following projects ACTRIS, GAW-WDCA and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: particle_number_concentration in pm10 (number_concentration_of_pm10_aerosol_particles_in_air), particle_number_concentration in pm10 (number_concentration_of_pm10_aerosol_particles_in_air), particle_number_concentration in pm10 (number_concentration_of_pm10_aerosol_particles_in_air)
Institutions: DE60L, Technical University Munich and Helmholtz Center Munich, ZAUM, Centre of Allergy & Environment, Biedersteinerstrasse 29, 80802, Munich, Germany, DE60L, Technical University Munich and Helmholtz Center Munich, ZAUM, Centre of Allergy & Environment, Biedersteinerstrasse 29, 80802, Munich, Germany
Last metadata update: 2024-01-12T00:00:00Z
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Abstract:
Ground based in situ observations of pollen_monitor at Munich Biedersteiner (DE0203U). These measurements are gathered as a part of the following projects AutoPollen_NRT, PollenScience_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: pollen_abies in aerosol, pollen_abies in aerosol, pollen_acer in aerosol, pollen_acer in aerosol, pollen_aesculus in aerosol, pollen_aesculus in aerosol, pollen_alnus in aerosol, pollen_alnus in aerosol, pollen_ambrosia in aerosol, pollen_ambrosia in aerosol, pollen_artemisia in aerosol, pollen_artemisia in aerosol, pollen_asteraceae in aerosol, pollen_asteraceae in aerosol, pollen_betula in aerosol, pollen_betula in aerosol, pollen_brassica in aerosol, pollen_brassica in aerosol, pollen_carpinus in aerosol, pollen_carpinus in aerosol, pollen_castanea in aerosol, pollen_castanea in aerosol, pollen_chenopodium in aerosol, pollen_chenopodium in aerosol, pollen_corylus in aerosol, pollen_corylus in aerosol, pollen_cruciferae in aerosol, pollen_cruciferae in aerosol, pollen_cyperaceae in aerosol, pollen_cyperaceae in aerosol, pollen_erica in aerosol, pollen_erica in aerosol, pollen_fagus in aerosol, pollen_fagus in aerosol, pollen_fraxinus in aerosol, pollen_fraxinus in aerosol, pollen_galium in aerosol, pollen_galium in aerosol, pollen_humulus in aerosol, pollen_humulus in aerosol, pollen_impatiens in aerosol, pollen_impatiens in aerosol, pollen_juglans in aerosol, pollen_juglans in aerosol, pollen_juniperus in aerosol, pollen_juniperus in aerosol, pollen_larix in aerosol, pollen_larix in aerosol, pollen_parietaria in aerosol, pollen_parietaria in aerosol, pollen_picea in aerosol, pollen_picea in aerosol, pollen_pinaceae in aerosol, pollen_pinaceae in aerosol, pollen_plantago in aerosol, pollen_plantago in aerosol, pollen_platanus in aerosol, pollen_platanus in aerosol, pollen_poaceae in aerosol, pollen_poaceae in aerosol, pollen_populus in aerosol, pollen_populus in aerosol, pollen_quercus in aerosol, pollen_quercus in aerosol, pollen_quercus_ilex in aerosol, pollen_quercus_ilex in aerosol, pollen_rumex in aerosol, pollen_rumex in aerosol, pollen_salix in aerosol, pollen_salix in aerosol, pollen_sambucus in aerosol, pollen_sambucus in aerosol, pollen_secale in aerosol, pollen_secale in aerosol, pollen_solidago in aerosol, pollen_solidago in aerosol, pollen_taraxacum in aerosol, pollen_taraxacum in aerosol, pollen_taxus in aerosol, pollen_taxus in aerosol, pollen_tilia in aerosol, pollen_tilia in aerosol, pollen_triticum in aerosol, pollen_triticum in aerosol, pollen_ulmus in aerosol, pollen_ulmus in aerosol, pollen_urticaceae in aerosol, pollen_urticaceae in aerosol, pollen_zea_mays in aerosol, pollen_zea_mays in aerosol, spores_fungi in aerosol, spores_fungi in aerosol, spores_fungi_alternaria in aerosol, spores_fungi_alternaria in aerosol