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 / Arctic Data Centre, AWI
Last metadata update: 2023-06-29T11:12:39Z
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Abstract:
These CMIP5 model data show interpolated results in Arctic only. Original data
were cut and interpolated for internal use of the EU funded project ACCESS.
Institutions: NORCE Tromsø, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-05T13:18:30Z
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Abstract:
Sentinel-1 Wet snow product: The warming climate on Svalbard impacts the amounts of wet snow significantly. Sentinel-1 is sensitive to wet snow as compared with dry snow or bare soil, and the current dataset provides up to daily maps over Svalbard of the spatial distribution of wet snow. The maps are derived from three SAR instriments (Envisat ASAR 2004-2012, Radarsat-2 2012-2014, and Sentinel-1 A/B from 2014-2020). Grid cells are classified with codes where 20=water, 30=nodata, 100=bare ground, 200=dry snow, 205=wetsnow
Institutions: Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T13:56:05Z
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Abstract:
The climate in Svalbard has been warming dramatically compared with the global average for the last few decades. Seasonal snow cover, which is sensitive to temperature and precipitation changes, is therefore expected to undergo both spatial and temporal changes in response to the changing climate in Svalbard. This dataset contains a daily snow cover fraction maps for the Svalbard archipelago, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra data.
Institutions: Norwegian Computing Center, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-24T19:38:41Z
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Abstract:
The CryoClim FSC product provides daily information on fractional snow cover(0-100 %) per grid cell for global land areas except permanent snow and iceareas with 5 km grid size. The product is based on multi-sensor/time-series fusion of AVHRR, SMMR, SSM/I and SSMIS data eliminating cloud cover and polar night, resulting in a temporally consistent snow map.
Institutions: IOPAS, IOPAS, Tropos, PMOD/WRC, PMOD/WRC, NILU, AWI, UVa-GOA, IGFPAS, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
High resolution aerosol optical depth from Sverdrup Station in Ny Ålesund (instruments: PFR, lunar PFR), AWIPEV Station in Ny-Ålesund (instruments: SP1A, Cimel), Polish Polar Station at Hornsund (instrument: Cimel), RV Oceania and RV Polarstern (instrument: Microtops), as part of the ReHearsol Project.
Institutions: Norwegian Computing Center, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-24T23:12:54Z
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Abstract:
The CryoClim FSC product provides daily information on fractional snow cover(0-100 %) per grid cell for global land areas except permanent snow and iceareas with 5 km grid size. The product is based on multi-sensor/time-series fusion of AVHRR, SMMR, SSM/I and SSMIS data eliminating cloud cover and polar night, resulting in a temporally consistent snow map.
Institutions: UT Tartu Uelikool, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
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Abstract:
Data were collected using Aanderaa automatic weather station fixed on a 10 m
met. mast at the drfting Tara ice camp during September 2006 until December
2007. Data for every month are presented in separate files. Tara drifted on the
Arctic Ocean starting north from Severnaya Zemlya up to 88 degN and finishing in
Fram Strait east from Greenland. For a complete review of the measurements see
Vihma, T., Jaagus, J., Jakobson, E:, Palo, T., 2008. Meteorological conditions
in the Arctic Ocean in spring and summer 2007 as recorded on the drifting ice
station Tara. Geophys. Res. Lett., 35, L18706, doi:10.1029/2008GL034681
Institutions: AWI Alfred Wegener Institute for Polar and Marine Research, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
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Abstract:
The data contain observations over lead with the helicopter borne instrument
HELIPOD, carried out by AWI during the winter arctic polynya study (WARPS) 2003
in the northern Fram Strait region. Data of 8 horizontal flight legs and of the
downstream and upstream profiles are given. A more detailed data description is
given in the Damocles Deliverable report D2.2-1 by Lüpkes and Hartmann, 2006
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.