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)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
If you use data retrieved through this portal, please acknowledge the SAON Data Portal.
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 through the drop down menu above the text field. Text strings that are not quoted are treated as separate words and will match any of the words (i.e. assuming the OR operator). Phrases may be prefixed with '-' to indicate no occurence of the phrase in the results.
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.
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).
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: 2023-06-29T11:12:36Z
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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: 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: 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.
To study the Svalbard reindeer and their basis of existence.Part of Nils Are Øritslands work over many years. Based on field work and hunting material. The hunting material is from 1984, 1986 and 1987 and contains the age mix of the animals.Countings, observations and experiments
Institutions: Norwegian Meteorogical Institute, Norwegian Meteorogical Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
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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 Meteorogical Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
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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.
Institutions: Norwegian Meteorogical Institute, Norwegian Meteorogical Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
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Abstract:
Time series of Monthly Mean Sea Ice Area (SIA) 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 Meteorogical Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
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Abstract:
Time series of Daily Sea Ice Area (SIA) 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 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 0-578-0-99840. 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 0-578-0-99710. 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.