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.
This collection contains a high-resolution (2.5 km) dataset of glacier mass balance, runoff and snow conditions in Svalbard from 1991-2022, one of the fastest warming regions in the Arctic. The dataset is created using a full energy balance model (the CryoGrid community model) forced by both the Copernicus Arctic Regional ReAnalysis (CARRA) dataset (1991-2021) and AROME-ARCTIC forecasts (2016-2022). Each variable is available at both a daily and monthly resolution.
This collection contains a high-resolution (2.5 km) dataset of glacier mass balance and runoff in Franz Josef Land and Novaya Zemlya from 1991-2022, situated in one of the fastest warming regions in the Arctic. The dataset is created using a full energy balance model (the CryoGrid community model) forced by the Copernicus Arctic Regional ReAnalysis (CARRA) dataset (1991-2022). Each variable is available at both a daily and monthly resolution.
Satellittbildemosaikk for Svalbard, av Copernicus Sentinel data fra 2020, offline-versjon for GIS i JPG2000-filformatet. / Satellite imagery mosaic for Svalbard, using Copernicus Sentinel data of 2020, offline version for GIS in JPG2000 file format.
Dette produktet er tilgjengelig som en WMTS-karttjeneste, NP_Satellitt_Svalbard_WMTS_25833, og som et kartlag i bl.a. TopoSvalbard. / This product is available online as a WMTS service, NP_Satellitt_Svalbard_Raster_25833, and as a map layer in e.g. TopoSvalbard.
The Nansen Legacy (Arven etter Nansen), The Nansen Legacy
Last metadata update: 2023-02-06T15:15:09Z
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Abstract:
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.
This is a bedrock geological map of Jan Mayen distributed as vector files, a georeferenced raster and a related non-spatial lithostratigraphy table.
The map was compiled by W.K. Dallmann and published in Gabrielsen et al. (1997). A version was also published in Dallmann (2014), and the geology of this current edition is equivalent to that publication. The compilation was based on Imsland (1978), Roberts and Hawkins (1965) and Siggerud (1972, 1986)
The automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors (Pt100 1/3 DIN) have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour. This activity is carried out by the Aldo Pontremoli Centre part of the Joint Research Agreement ENI-CNR, in the framework of the SnowCorD project (SIOS Core Data).
The automated station to measures snow cover is operating at the Amundsen-Nobile Climate Change Tower since 2010, which is in a tundra site almost flat, located in the Kolhaugen area. The station is part of a complex infrastructure where multi-disciplinary observations are routinely performed. Data were collected using an ultrasonic distance sensor. This activity is carried out in the framework of the SnowCorD project (SIOS Core Data).
The automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors (NESA LU06) have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour. This activity is carried out by the Aldo Pontremoli Centre part of the Joint Research Agreement ENI-CNR, in the framework of the SnowCorD project (SIOS Core Data).
The automated station is operating at the Amundsen-Nobile Climate Change Tower since 2010, which is in a tundra site almost flat, located in the Kolhaugen area. The station is part of a complex infrastructure where multi-disciplinary observations are routinely performed. The instrument used for the meauserements is a PT100 thermocouple. This activity is carried out in the framework of the SnowCorD project (SIOS Core Data).
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
This dataset contains annually averaged ice surface velocity and thickness for all 202 tidewater glacier fronts on Svalbard, dating from 2012 to 2021. This is combined with mapping of front position changes to derive annual ice mass rates for retreat/advance, ice flux (discharge) and total frontal ablation.
The dataset is planned to be updated with new results every autumn.
Quality
Ice thickness was calculated with the help of surface (annual mosaics of ArcticDEM strip data) and bedrock DEMs (SVIFT v1.0 from Fürst et al., 2018; NPI DEM, and available bathymetry data from the Norwegian Mapping Authority). Velocity data were obtained from 3 datasets: Landsat-8 velocities from the ITS-Live product (2013 to 2018), and Sentinel-1 velocities derived by Adrian Luckman (2015 to 2020) and by Friedl et al. (2021) (2015 to 2021).Mean velocities values were calculated for each glacier when different datasets were available for similar years. Mass rates for retreat/advance were derived from front position changes manually digitized based on available satellite or aerial imagery, mainly acquired by Sentinel-2 or Landsat-8 during the period 15 Aug. to 15 Sept. each year and from ice thickness data. Ice flux (discharge) was derived from annual velocity data and ice thickness data. Frontal ablation was calculated as the combination of the ice mass rate and the discharge of ice.
This dataset presents a 1936/1938 3D reconstruction of Svalbard from NP’s archive of 5,507 aerial images acquired during the summers of 1936 and 1938 (Luncke, 1936). The dataset contains a Svalbard-wide DEM and orthophotomosaic from 1936/1938 and an elevation change map (1936 to ~2010) at 20 and 50 m resolution. Higher-resolution (5 m) DEMs and orthophotos also are available, but the data are separated into 8 regions due to file size constraints. The dataset also contains a shapefile inventory of the 1936/1938 glacier extents and an .xlsx spreadsheet with glacier-by-glacier mass balance statistics and climate parameters. See README.txt for a complete description of the files. The data are associated with the following article: Geyman, E.C., van Pelt, W., Maloof, A.C., Faste Aas, H., and Kohler, J., 2021. “Historical glacier change on Svalbard predicts doubling of mass loss by 2100.” Nature.
See README.txt for dataset organization.
Quality
Methods described in: Geyman, E.C., van Pelt, W., Maloof, A.C., Faste Aas, H., and Kohler, J., 2021. “Historical glacier change on Svalbard predicts doubling of mass loss by 2100.” Nature.