The SIOS Data Management Service (SDMS) integrates information from SIOS partner data repositories into a unified virtual data centre, the SIOS Data Access Portal, allowing users to search for and access data regardless of where they are archived. Providers and users have to commit to the SIOS data policy.
The current focus is on dataset discovery through standardised metadata, and retrieval, visualisation & transformation of data. Ultimately, the Data Management Service works towards integration of datasets which requires a high level of interoperability at the data level.
SDMS currently harvests information on SIOS relevant datasets from a number of data centres (see below), some hosted by SIOS partners and some not. Data centres hosted by SIOS partners work to harmonise access to the data allowing integrated visualisation etc for the relevant datasets.
Data centres SDMS is harvesting information from.
SIOS partner data centres
Other
AWI (DE)
British Antarctic Survey
CNR (IT) - temporarily disabled due to server issues
National Snow and Ice Data Center
IGPAS (PL)
IMR (NO)
IOPAN (PL)
MET (NO) - weather stations have not been updated for a while, update in progress
NERSC (NO)
NILU (NO)
NIPR (JP)
NPI (NO)
UiS (PL)
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source: Research Council of Norway, project number 291644, Svalbard Integrated Arctic Earth Observing System – Knowledge Centre, operational phase.
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)
SIOS recommends all partner data repositories to mint Digital Object Identifiers (DOI) on all datasets. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
SIOS Core Data
In order to find SIOS Core Data please use the searchable item marked "Collection" on the right hand side of the map and select "SIOSCD". Quick access to SIOS Core Data is provided here.
Nansen Legacy Data
The Nansen Legacy project is using the SIOS Data Management system as the data portal. Quick access to all Nansen Legacy related datasets is available here.
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 from the drop down above the text field and prefixing words with '+' to require their presence and '-' to require their non presence.
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 Fram Strait Arctic Outflow Observatory, The Fram Strait Arctic Outflow Observatory
Last metadata update: 2019-11-21T14:31:15Z
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Abstract:
Current measurements from Doppler Current Meters (DCM), Recording Doppler Current Meters (RDCP), Acoustic Doppler Current Meters (ADCP) and Recording Current Meters (RCM) from the moorings F11, F12, F13, F14, F17 from the Fram Strait Arctic Outflow Observatory in the East Greenland Current maintained by the Norwegian Polar Institute (NPI) since September 1997. F17 has been deployed since 2003. The mooring positions were changed from 79°N to 78°50’N in September 2002. Exact locations and additional instrument information are given in the meta data in each data file individually.
Quality
Data are provided at the original sampling rate (which varies from 20 minutes to 2 hours).
The Fram Strait Arctic Outflow Observatory, The Fram Strait Arctic Outflow Observatory
Last metadata update: 2018-10-31T14:22:34Z
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Abstract:
Freshwater transport (relative to a reference salinity of 34.9) and gridded data fields of southward velocity and salinity from the East Greenland Current in Fram Strait. The time series are collected by moorings F11, F12, F13, F14, F17 from the Fram Strait Arctic Outflow Observatory (Norwegian Polar Institute) and by moorings F9 and F10 (Alfred Wegener Institute). The moorings were at 79N from Sept. 1997 to Aug. 2002 and at 78°50’N from Sept. 2002 to Aug. 2015. Only in Sept. 2003 the extra mooring (F17) was added on the shelf.
Note: data files are created for both latitudes (79N and 78°50’N) and time periods individually and need to be looked at separately since the southward move of the array had significant implications for the observed flow field. The moorings were located between 0°W and 6.5°W until Aug. 2002. In Sept. 2003 an extra mooring was added at 8°W and allowed for a larger portion of the outflow to be measured.
Quality
Velocity data are corrected for magnetic deviation and tides are removed with a 41-hr low-pass filter. The salinity is based on mooring data and a seasonally varying hydrographic data set to improve the stratification. Data are monthly averaged. Data gaps are treated with regression with neighboring instruments of filled in with long-term mean values. Note: Version V2.0 is a corrected version from V1.0. An error was found in the regression of velocity on the shelf in 2011-2012 which amounted to a too large near-surface velocity. The gridded V and freshwater transport time series are corrected accordingly.
The dataset contains 2 archives. The first archive contains all data (saved as netCDF files) relative to the Figures presented in Boutin et al. (2023). The second archive contains monthly averaged fields (saved as netCDF files) of the simulation described in Boutin et al. (2023). They include quantities relative to sea ice properties (icemod files) and to the mass balance (ice growth/melt etc... simba files). They cover the north Atlantic and the Arctic Ocean (north of Bering Strait) for the period 2000-2018.
icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018.Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment).transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport.In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.
Monthly values for sea ice extent in the inner part of Kongsfjorden, Svalbard 2003-2019, as percentages of the total surface area during February-June each year. The data file has six columns: a) the year the data connects to, and b)-f) the numbers for maximum fast ice coverage (in percent from the defined observation area, equalling 120 km2) for each month from February to June (2003-2019) in the inner part of Kongsfjorden, derived from manually drawn and digitized ice maps (see above). This inner fjord area is based on a coastline from 1993. Since glaciers have been retreating since then, some new areas developed where there is a potential of sea ice formation. Those areas will be considered in future updates of the dataset. Gaps in some lines in the figure are related to years/months where no data are available. If an observation is missing, data is set to 999.
Land-fast sea ice covers the inner parts of Kongsfjorden, Svalbard, for a limited time in winter and spring months, being an important feature for the physical and biological fjord systems. Monitoring of the Kongsfjorden area has been carried out by the Norwegian Polar Institute (NPI) systematically since 2003 (Gerland and Renner 2007; Pavlova et al. 2019; Gerland et al. 2020). Conception and methodology of the systematic fast-ice monitoring in Kongsfjorden are described in Gerland and Hall (2006), Gerland and Renner (2007), and Pavlova et al. (2019) and include visual sea ice extent observations from the mountain Zeppelinfjellet (mapping) as well as in situ measurements of snow and ice thickness (Gerland and Renner 2007; Pavlova et al. 2019). The monitoring was designed to be relatively inexpensive, robust, and consistent over time. The permanent presence of NPI personnel at the Sverdrup unit in Ny-Ålesund Research Station and daily visits to the observatory on the mountain Zeppelinfjellet just south of Ny-Ålesund enable regular ice extent observations (weather, visibility, and daylight permitting). Data collected within this standardized monitoring programme have contributed to a number of studies (see, e.g. Moe et al. 2012; Johansson et al. 2020). Monitoring of the sea-ice conditions in Kongsfjorden can be used to demonstrate and investigate phenomena related to climate change in the Arctic.
This archive presents the results of sea ice extent observations in Kongsfjorden - the Arctic fjord located in the west coast of Spitsbergen, Svalbard archipelago at approximately 79° N, 12° E . The permanent presence of Norwegian Polar Institute’s staff at Ny-Ålesund Research Station, and daily visits to the observatory on the mountain Zeppelinfjellet (474ma.s.l., south of Ny-Ålesund) enable regular visual sea ice observations in the fjord, which have been done systematically since 2003 . The observations are weather- and visibility permitting and typically conducted several times a week from February to June: from the onset of daylight conditions sufficient for visual observations and lasting until the end of ice season in the fjord. The archive covers years 2003 – 2021 and contains 668 ice charts evenly distributed over the period, on average 36 per ice season. Since some of the charts represented a few days of observations in a row, reporting “similar ice conditions”, the digitized archive comprises 887 ice observation days in total. This dataset is a detailed extension of previously published monthly values for sea ice extent in the inner part of Kongsfjorden, Svalbard 2003-2019, compiling in one archive the original observations of sea ice conditions in the fjord back to 2003.
FreshArC, The Fram Strait Arctic Outflow Observatory
Last metadata update: 2021-12-20T11:49:42Z
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Abstract:
These velocity and salinity data have been collected by moorings of the Fram Strait Arctic Outflow Observatory (FSAOO) at 78°50’N (F17 at 8°W, F14 at 6.5°W, F13b at 5.5°W, F13 at 5°W, F12 at 4°W, F11 at 3°W, F10 at 2°W) between Sept. 2003-Aug. 2019. The moorings have been maintained by the Norwegian Polar Institute (between 2003-2016, F10 was maintained by the Alfred Wegener Institute). The time-series of freshwater transport, freshwater content, volume transport and salt transport are calculated from the gridded salinity and velocity fields and are integrated over the full section as well as in the Polar Water (PW) (sigma<27.7 & T<0). Freshwater is calculated relative to a reference salinity of 34.9.
Quality
The raw data collected from the moored instruments received standard post processing and quality control. Velocity data are corrected for magnetic deviation and tides are removed with a 41-hr low-pass filter. The salinity is based on mooring data combined with a seasonally varying hydrographic data set to improve the stratification and corrected for any density instabilities. Data are then monthly averaged. Data gaps are treated with regression with neighbouring instruments or filled in with long-term mean values. Data are interpolated on a grid with bottom following contours below 150 m and horiontal z-levels with 10 m resolution above. Horizontal resolution is 0.25 degrees longitude. Interpolation for velocity is linear while salinity is interpolated cubically in the vertical. The data have been corrected (back in time) for the effect of increasing coverage of the mooring array.
The data set consists of digital elevation models (DEM) of subglacial topography, ice thickness, bathymetry and ice surface elevation of Kongsfjorden, northwestern Svalbard, near Ny-Ålesund (78.9 deg N, 12.4 deg E). The DEMs cover five tide-water glaciers with a grid size of 150 m. The data have a total area of ~1100 km^2 and cover the glaciers Blomstrandbreen, Conwaybreen, Kongsbreen, Kronebreen, and Kongsvegen, including the ice fields Holtedahlfonna and Isachsenfonna. A 50 m resolution DEM is also available for Kronebreen. The compiled data set covers one of the most studied regions in Svalbard and can be valuable for studies of glacier dynamics, geology, hydrology and fjord circulation. For further details see Lindbäck et al. (2018, https://doi.org/10.5194/essd-2018-37).
If you use the data set in presentations and publications please also refer to the peer-reviewed paper (Lindbäck et al., 2018, https://doi.org/10.5194/essd-2018-37). The data set will be updated when the quality of the data is improved or if new data sets become available.
File format: GeoTIFF and ASCII Spatial reference: WGS-1984 UTM Zone 33W
Contact person: Jack Kohler (jack.kohler@npolar.no)
This work was part of the TIGRIF (Tidewater Glacier Retreat Impact on Fjord circulation and ecosystems) project, funded by the Research Council of Norway.
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T14:51:09Z
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Abstract:
The daily analysis of sea ice concentration is obtained from
operational satellite images of the polar regions. It is based on
atmospherically corrected signal and a carefully selected sea ice
concentration algorithm. This product is freely available from the
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI
SAF). The Eumetsat identifier for this product is OSI-401.
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T14:51:09Z
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Abstract:
The daily analysis of sea ice concentration is obtained from
operational satellite images of the polar regions. It is based on
atmospherically corrected signal and a carefully selected sea ice
concentration algorithm. This product is freely available from the
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI
SAF). The Eumetsat identifier for the product is OSI-401.
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, Danish Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-07-14T09:27:43Z
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Abstract:
A 9 month ice drift data set based on VIS and IR data
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, Danish Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-07-14T09:06:28Z
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Abstract:
A 9 month ice drift data set based on VIS and IR data
Institutions: Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany, Norwegian Meteorological Institute / Arctic Data Centre, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
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Abstract:
Array of 12 deep moorings across Fram Strait at 78deg50min N maintained by AWI
Hydrographic and current time series data from outside the southern side of the Isfjorden Mouth during 16 September 2005 to 15 September 2006 at 78°03.650’ N; 013°31.369’ E, and 210 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor inflow of Atlantic Water to Isfjorden, and was equipped with two Aanderaa Instruments recoding current meters (RCMs) and one water level recoder (WLR) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. For further details of the mooring and data, see Skogseth et al. (2020).
Reference: Skogseth R., Olivier L.L.A., Nilsen F., Falck E., Fraser N., Tverberg V., Ledang A.B., Vader A., Jonassen M.O., Søreide J., Cottier F., Berge J., Ivanov B.V., and Falk-Petersen S. (2020). Variability and decadal trends in the Isfjorden (Svalbard) ocean climate and circulation – an indicator for climate change in the European Arctic, Progress in Oceanography, 187, DOI: doi.org/10.1016/j.pocean.2020.102394.
Quality
No salinity data. Pressure and temperature data have been despiked with a window size of 60 and a standard deviation of 2. Temperature data have been calibrated against nearby SBE 911+ CTD profiles taken during the deployment period. Times rounded to nearest hour or 10 min.