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
Show more...
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).
Institutions: Norwegian Polar Institute, Norwegian Polar Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Institutions: Norwegian Polar Institute, Norwegian Polar Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
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.
Geophone and Hydrophone deployments in Svalbard 2022, to measure the vibrations in sea ice following the appearance of cracks. For more information, see https://github.com/jvoermans/Geophone_Logger .
Institutions: Norwegian Polar Institute, Norwegian Polar Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:48:12Z
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Abstract:
Temperature and Salinity measurements collected by the Norwegain Polar
Institute.
This ocean model is operated at 20km resolution covering the Nordic Seas
and the Arctic Ocean. This specific dataset provides the daily analysis
from the operational model. Only the analysis is provided for historical
periods, the daily forecast with 1 hour resolution is provided as a
separate dataset. Currently the WMS presentation of this dataset is not
supporting the 3D nature.
A numerical model is applied to describe the dynamics of the oceans, such
as sea level variations (tides and storm surge), movements in the water
column (currents) and the salinity and temperature. To simulate the ocean,
a 3-D grid is applied with different sizes, i.e., small grids for fine
scale or detailed calculations, and larger or coarser grids to cover
larger areas (and depth). The model runs on a supercomputer, and provides
forecasts of sea level, currents, salinity and temperature for a
time-range between 66 (2.75 days) and 240 hours (10 days). The model is
run operationally, i.e, in a "24/7/365" environment to provide a 99.5%
stability on a yearly basis. Currents from the model is further applied in
emergency-models that simulates pathways of oil slicks and drifting
objects (Search And Rescue).
The ocean model used is the Regional Ocean Modeling System (ROMS). This is
a three-dimensional, free-surface, terrain-following numerical model that
solve the Reynolds-averaged Navier-Stokes equations using the hydrostatic
and Boussinesq assumptions (Haidvogel et al., 2008).
Haidvogel, D. B., H. Arango, W. P. Budgell, B. D. Cornuelle, E.
Curchitser, E. Di Lorenzo, K. Fennel, W. R. Geyer, A. J. Hermann, L.
Lanerolle, J. Levin, J. C. McWilliams, A. J. Miller, A. M. Moore, T. M.
Powell, A. F. Shchepetkin, C. R. Sherwood, R. P. Signell, J. C. Warner,
and J. Wilkin, Ocean forecasting in terrain-following coordinates:
Formulation and skill assessment of the Regional Ocean Modeling System,
JOURNAL OF COMPUTATIONAL PHYSICS, 227, 3595–3624, 2008.
THIS MODEL IS DISCONTINUED AND NO FORECAST DATA IS AVAILABLE ONLINE.
This ocean model is operated at 20km resolution covering the Nordic Seas
and the Arctic Ocean. This specific dataset provides the hourly forecast
fields from the operational model. For historical purposes, the daily
analysis is provided as another dataset. If for some reason the
historical forecast is required, pleased use the contact information
provided to receive this (manual task).
A numerical model is applied to describe the dynamics of the oceans, such
as sea level variations (tides and storm surge), movements in the water
column (currents) and the salinity and temperature. To simulate the ocean,
a 3-D grid is applied with different sizes, i.e., small grids for fine
scale or detailed calculations, and larger or coarser grids to cover
larger areas (and depth). The model runs on a supercomputer, and provides
forecasts of sea level, currents, salinity and temperature for a
time-range between 66 (2.75 days) and 240 hours (10 days). The model is
run operationally, i.e, in a "24/7/365" environment to provide a 99.5%
stability on a yearly basis. Currents from the model is further applied in
emergency-models that simulates pathways of oil slicks and drifting
objects (Search And Rescue).
The ocean model used is the Regional Ocean Modeling System (ROMS). This is
a three-dimensional, free-surface, terrain-following numerical model that
solve the Reynolds-averaged Navier-Stokes equations using the hydrostatic
and Boussinesq assumptions (Haidvogel et al., 2008).
Haidvogel, D. B., H. Arango, W. P. Budgell, B. D. Cornuelle, E.
Curchitser, E. Di Lorenzo, K. Fennel, W. R. Geyer, A. J. Hermann, L.
Lanerolle, J. Levin, J. C. McWilliams, A. J. Miller, A. M. Moore, T. M.
Powell, A. F. Shchepetkin, C. R. Sherwood, R. P. Signell, J. C. Warner,
and J. Wilkin, Ocean forecasting in terrain-following coordinates:
Formulation and skill assessment of the Regional Ocean Modeling System,
JOURNAL OF COMPUTATIONAL PHYSICS, 227, 3595–3624, 2008.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
Sea ice concentration charts based on a manual interpretation of different satellite data. The main satellite sensor used are the SAR sensor (Synthetic Aperture Radar) suplemented by visual and infrared sensors and data from passive microwave sensors. As part of the Copernicus project the sea ice concentration product is gridded to a 1km spatial resoluton and converted to a NetCDF format. The concentration intervals follow the World Meteorological Organization (WMO) total concentration standard. A new product is delivered every weekday around 1500 UTC.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available satellite data and insitu observations and provides a gridded map. It is a continuation of the previous sea ice chart which basically identified the ice edge.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available insitu observations. This dataset is the predecessor of the gridded ice charts based on satellite data and other sources. This dataset primarily identifies the sea ice edge.
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-24T15:30:23Z
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Abstract:
This climate data record of sea ice concentration is obtained from coarse resolution passive microwave satellite data over the polar regions (SMMR, SSM/I, and SSMIS). The processing chain features: 1) dynamic tuning of tie-points and algorithms, 2) correction of atmospheric noise using a Radiative Transfer Model, 3) computation of per-pixel uncertainties, and 4) an optimal hybrid sea ice concentration algorithm. This dataset was generated by the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF). The ESA CCI Programme contributed with Research and Development on the algorithms. The algorithm and validation of the dataset are described in Lavergne et al. (2019, https://doi.org/10.5194/tc-13-49-2019)
Use of this dataset should be acknowledged with the following citation: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Global sea ice concentration climate data record 1979-2015 (v2.0, 2017), OSI-450, doi: 10.15770/EUM_SAF_OSI_0008, (Data extracted from OSI SAF FTP server/EUMETSAT Data Center: ([extracted period],) ([extracted domain],)) accessed [download date]