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.
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).
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
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.
Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are daily composites of merged sensor (MERIS, MODIS Aqua, SeaWiFS LAC & GAC, VIIRS, OLCI) products. MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007. VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2013; and at the third stage OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30. VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA/s l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.12 (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with polymer. The Rrs were binned to a sinusoidal 1km level-3 grid, and later to 1km geographic projection, by Brockmann Consult/s SNAP. Derived products were generally computed with the standard algorithmsthrough SeaDAS. QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting. The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships. Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated accorsing to Jackson et al. (in prep).
Institutions: UNIS, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-02-28T13:00:00Z
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Abstract:
Wave observations from a buoy located in Isfjorden at Svalbard. This dataset contains several sub datasets representing different variables and time periods.
Centre for Sustainable Arctic Marine and Coastal Technology, Arctic Offshore and Coastal Engineering in a Changing Climate, Programme for International Partnerships for Excellent Education, Research, and Innovation, Dynamics of Floating Ice, Large-scale Programme for Petroleum Research, Survey to assess harp and hooded seal pup production in the Greenland sea pack-ice in 2018, Integrated System for Operations in Polar Seas, Nansen Legacy, Dynamics of Floating ice, Australian Antarctic Program projects 4593 and 4506, Joyce Lambert Antarctic Research Fund grant no. 604086, Research Council of Norway grant no. 280625, Fram 2020, Arctic Challenge for Sustainability II, JSPS KAKENHI Grant Numbers JP 19H00801, 19H05512, 21K14357 and 22H00241, Survey to assess harp and hooded seal pup production in the Greenland sea pack-ice in 2022, SURVEYS TO ASSESS HARP AND HOODED SEAL PUP PRODUCTION IN THE GREENLAND SEA PACK-ICE IN 2022 (SAMCoT, AOCEC, INTPART, DOFI, PTEROMAKS2, ISOPS, AeN, ArCS II)
Institutions: Norwegian Meteorological Institute (MET), University of Melbourne, College of Fisheries and Ocean Sciences, University of Tokyo, Havforskningsinstituttet, Norwegian Meteorological Institute / Arctic Data Centre
Sea ice drift trajectories and waves in sea ice data collected over the period 2017-2022 by a consortium of researchers, both in the Arctic and the Antarctic.
The Isfjorden-Adventfjorden (IsA) time series station is a marine station operated by the University Centre in Svalbard (UNIS). It is located in the mouth of Adventfjorden within Isfjorden on the west coast of Spitsbergen, and is frequently influenced by inflow of warm Atlantic Water from the West Spitsbergen Current. The station is therefore well suited for monitoring seasonal variability and ecosystem effects of climate change. IsA has been sampled on a monthly basis since December 2011. This dataset represents the acid-corrected Chl a values from several depths
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
The Isfjorden-Adventfjorden (IsA) time series station is a marine station operated by the University Centre in Svalbard (UNIS). It is located in the mouth of Adventfjorden within Isfjorden on the west coast of Spitsbergen, and is frequently influenced by inflow of warm Atlantic Water from the West Spitsbergen Current. The station is therefore well suited for monitoring seasonal variability and ecosystem effects of climate change. IsA has been sampled on a monthly basis since December 2011. This dataset represents the acid-corrected Chl a values from several depths
The Nansen Legacy cruise Q1 was part of the seasonal investigation of the northern Barents Sea and adjacent Arctic Basin. The cruise was conducted in 2-24 March 2021 onboard R/V Kronprins Haakon, and focused on studying the physical, chemical and biological conditions along the Nansen Legacy main transect in open waters and within the sea ice. While in sea ice we conducted ten regional scale sea ice helicopter-borne surveys of ice conditions along the Nansen Legacy transect using a helicopter-borne electromagnetic instrument (HEM) EM-bird. This dataset presents processed EM-bird data on total snow and sea-ice thickness along the flight tracks.
This is a contribution to the Research Council of Norway project “Nansen Legacy” (https://arvenetternansen.com/), WP RF-1 “Physical drivers”.
Quality
See the attached docuement “AeN_Q1_202103_HEM_icethickness_metadata_v1.0.pdf” for details on the data acqusition, processing and structure.