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.
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2024-03-13T11:33:04Z
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Abstract:
The climate change indicator products of glaciers in mainland Norway include surface mass balance and length change (from NVE’s field observations) and area changes (from satellite imagery and topographical maps) for a selection of glaciers. Glacier surface mass balance and glacier length change are obtained directly from NVE’s databases. https://glacier.nve.no/Glacier/viewer/CI/en/cc
Institutions: Norwegian Water Resources and Energy Directorate (NVE)
Last metadata update: 2024-03-13T11:33:04Z
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Abstract:
Glacier Periodic photos (GPP) from Norwegian glaciers. The photo series illustrate how the extent of a selection of Norwegian glaciers have changed. The pictures are not taken from the same position each year. The earliest photos are from the 1860s. The majority of the pictures are from the last 20 years. The number of photos per glacier varies. The source of the data is NVEs photo archive, with contributions from NVE collaborators. https://glacier.nve.no/Glacier/viewer/gpp/en/cc/
The Climate Change Tower Integrated Project (CCT-IP) represents the guide lines of the italian research in the arctic and aims to study the interaction between all the components of the climate system in the Arctic. The Amundsen-Nobile Climate Change Tower (CCT) is the key infrastructure of the project, and provides continuous acquisition of the atmospheric parameters at different heights as well as at the interface between the surface and the atmosphere.
30 minutes average (μ) and standard deviation (σ) of meteorological data are available for the download.
Data at resolution of 1 minute are available for online visualization and downloadable under request.
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.
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.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
The file contains time series of meteorological near-surface parameters measured on a temporary meteorological mast on the southern side of the coast of Adventdalen, Svalbard, from July to August 2022: Both temperature, humidity, wind speed, wind direction were measured at two levels.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, University of Bergen, University of Bergen, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
A scanning Doppler Lidar was placed in Adventdalen (Central Spitsbergen, Svalbard, Norway) close to the permanent weather mast SN99870. The Lidar measured between 4 July and 23 August 2022 with different scanning patterns in an hourly cycle. The cycle consisted of three Plan Position Indicator (PPI) scans at 1, 5 and 10 degree from xx:00 to xx:10, Range Height Indicator (RHI) scans alternating between up-valley and down-valley direction from xx:10 to xx:50, Doppler-Beam-Swinging (DBS) technique from xx:50 to xy:00. The radial resolution was 10 m with overlapping range gates of 50 m. Short periods of power cuts were encountered. Frequently there were conditions with little backscatter and low carrier-to-noise ratio, especially in light down-valley winds.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegain Infrastructure for Research Data (NIRD)
A set of auroral all-sky images captured over Svalbard in 2019-2020. Images contain auroral emission and have been automatically classified for auroral morphology. Morphological classes are included.
Aerosol scattering coefficient at 1 wavelength (530 nm) measured using a nephelometer M903 manufactured by Radiance Research and absorption coefficient at 7 wavelengths (370, 470, 520, 590, 660, 880, 950 nm) measured using an AETHALOMETER AE33 from Aerosol Magee Scientific.
Aerosol scattering coefficient at 1 wavelength (530 nm) measured using a nephelometer M903 and absorption coefficient at 3 wavelengths (467, 530, 660 nm) measured using a Particle Soot Absorption Photometer (PSAP), both manufactured by Radiance Research.
Air temperature measurements in snowbeds on the Varanger peninsula.
The dataset includes four different types of files and all files are
saved as ;-separated txt-files (except the readme):
* One data file per year (V_air_temperature_snowbed_YEAR.txt)
* One meatadata file per year with dates when the loggers were deployed and collected (V_air_temperature_snowbed_metadata_YEAR.txt)
* One coordinate file with coordinates of all sites (V_air_temperature_snowbed_coordinates.txt)
* One auxiliary file with information about which sites are included in the study design (V_air_temperature_snowbed_aux.txt)
* One readme file with additional information (_readme.pdf)
V3: Corrected dates when the temperature loggers were collected and cut the temperature data according to the corrected dates (for the years 2010 to 2017).
The data set present the calculated sea ice back-trajectories of 30 sea ice stations conducted in the northern Barents Sea and in western Arctic Basin north of Svalbard between August 2018 to March 2022. The sea ice stations were made during eight research cruises to the area with R/V Kronprins Haakon in the framework of the Nansen Legacy project. For details on the back-tracking methodology and data structure please see the attached metadata file NansenLegacy_sea_ice_stations_back-trajectories.pdf
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2023-10-30T11:07:25Z
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Abstract:
Since 2020, during the accumulation season, snow samples are collected from the Ariebreen glacier a few times per season. Snow samples are collected to the polyethylene sterile bags and are taken to the Polish Polar Station Hornsund. After melting at room temperature, the pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical. Site Information Ariebreen - 0.5 km long glacier between Skoddefjellet and the northern part of Ariekammen, southernmost in Wedel Jarlsberg Land.
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2023-10-30T11:07:22Z
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Abstract:
During the accumulation season, snow samples were collected from the Hansbreen glacier. Few times per season. Snow samples are collected to the polyethylene sterile bags and are taken to the Polish Polar Station Hornsund. After melting at room temperature, the pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical laboratory. Snow chemical composition: major ions, HCO3-, pH, conductivity