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.
Snow depth, snow water equivalent and basal ice thickness measurements were taken during the SIOS SnowPilot campaign in Spring 2022. Snowpits were dug on GPR profile crossings in the Fuglebekken and Revdalen catchments in the Hornsund fiord, Spitsbergen catchment. Snow density was measured with an IG PAS snow tube, and snow depth and basal ice (ice forming on the ground surface) thickness were measured with an avalanche probe.
Field measurements of aerosol vertical distribution carried out in Hornsund area, during the 2021 spring fieldwork. Data obtained using PMS7003 particle concentration sensor, capable of detecting aerosol particles with a size beyond 0.3 micrometer.
Field measurements of aerosol vertical distribution carried out in Hornsund area, during the 2021 spring fieldwork. Data obtained using TSI P-Trak ultrafine particle counter 8525, capable of detecting aerosol particles with a size of 0.02 to 1 micrometer.
Aerosol size distribution measurements at the Polish Polar Station Hornsund, during the 2021 spring fieldwork (25.04-15.05). Data obtained by PMS7003 particle concentration sensor. The device was installed in a fixed position on the roof of a specially prepared container (‘environmental house’) in the Fuglebekken catchment, located approximately in 500 m distance from the main base building.
Aerosol size distribution measurements at the Polish Polar Station Hornsund, during the 2021 spring fieldwork (25.04-15.05). Data obtained by TSI particle spectrometer: Optical Particle Sizer (OPS) Model 3330. Measurements carried out in specially prepared container (‘environmental house’) in the Fuglebekken catchment, located approximately in 500 m distance from the main base building.
Aerosol size distribution measurements at the Polish Polar Station Hornsund, during the 2021 spring fieldwork (25.04-15.05). Data obtained by TSI particle spectrometer: NanoScan SMPS Nanoparticle Sizer 3910. Measurements carried out in specially prepared container (‘environmental house’) in the Fuglebekken catchment, located approximately in 500 m distance from the main base building. Data gaps occur due to repeated device failure.
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.
The high Arctic Bayleva site is located on western Spitsbergen about 3 km from the settlement
of Ny Ålesund. The provided data set comprises snow water equivalent (SWE) and snow depth
measurements recorded by automated sensors installed in August 2019 close to the Bayelva
soil and climate station, running since 1998. The SWE is recorded using a Campbell Scientific
CS725 gamma ray sensor covering a footprint area of up to 55 m2. The snow depth is measured
using a Campbell Scientific SR50/AT ultrasonic distance sensor covering a footprint area of up
to 1.3 m2 close to the center of the SWE footprint. The provided data set furthermore includes
snow temperature measurements from two PT100 sensors installed at 0.04 and 0.2 m above
the ground within the fenced area of the nearby climate monitoring station. Additionally,
measurements of the snow dielectric constant are provided from a vertically installed TDR
probe inside the fenced area. Moreover the data set includes sporadic manual records of SWE
and snow depth, performed to validate the automated measurements.
Upwelling and downwelling longwave and shortwave radiation and shortwave albedo from station deployed out on the ice floe, nearby surface meteorology observations.
WP2
Quality
Albedo data is on a different time step and is a heavily processed version of a subset of the the radiation data, see attributes in the NetCDF files and the READMEs:
The ACS_Bayelva_class dataset contains 302 high-resolution binary snow cover images that were obtained by classifying orthrorectified photographs of a 1.77 km^2 area of interest in the Bayelva catchment. This catchment is close to Ny-Ålesund, the northernmost permanent civilian settlement in the world and a major hub for polar research, in the Norwegian high-Arctic Svalbard archipelago. The imagery has a (roughly) daily temporal resolution and a ground sampling distance (pixel spacing) of 0.5 m. The dataset spans 6 snowmelt seasons, covering the months May-August for the period 2012-2017. The orthophotos were obtained by processing oblique time-lapse photographs taken by a terrestiral automatic camera system (ACS) mounted at 562 m a.s.l. near the summit of Scheteligfjellet (719 m a.s.l.) a few kilometers west of Ny-Ålesund. The orthophotos were manually classified into binary snow cover images (0=no snow, 1=snow) by iteratively selecting a (visually) optimal threshold on the intensity in the blue band for each image. More details are provided in the study of Aalstad et al. (2020) [a copy is available in this repository] where this dataset was created. The ACS was maintained by scientists from the group of Sebastian Westermann at the Section for Physical Geography and Hydrology in the Department of Geosciences at the University of Oslo, Oslo, Norway.
Dataset of annual mass balances of Svenbreen, a small valley glacier in Central Spitsbergen, 2010/2011 - 2017/2018
To date (31st Jan 2020), the data have not been published in an article in a peer-reviewed journal, which is planned for 2021 or 2022, following the completion of ten years of measurements. It is possible that the exact values might differ slightly between this dataset and the planned paper due to differences in methodology, eg. updated glacier hypsometries. If this dataset is of your interest, please check Jakub Malecki’s publication record for the most up-to-date data..
Quality
Annual mass balance of Svenbreen has been measured with a glaciological method since 2010/2011, typically between 1st and 15th day of September every year. Ablation stake network comprises 12-16 stakes distributed along the glacier tongue and in two (out of three) high-elevation sections, i.e. in the cirque and along an ice patch leading towards neighbouring glacier Hoelbreen.
Satellite albedo data from MODIS is used to track snow-line on glaciers in Svalbard, with snow-line serving as a proxy for the Equilibrium Line Altitude (ELA). Eventually the results will be available as shapefiles.
A table with snow lines derived with this method is available and snow line can be plotted against time
Method: albedo data and snow line tracking. Sensors: MODIS.
Institutions: Nicolaus Copernicus University in Torun
Last metadata update: 2022-04-29T13:30:00Z
Show more...
Abstract:
Glacier mass balance data for Waldemarbreen (sonce 1996), Irenebreen (since 2002) and Elisebreen (2007-2013). The mass balance of Kaffiøyra region glaciers is very negative. Similarly negative mass balance values are characteristic of other Svalbard glaciers. The rapid and substantial changes in mass balance of glaciers which have been occurring in recent years are also reflected in a growing rate of surface area shrinkage. This negative balance is mainly attributed to the climate change in that region, and with an increase in mean air temperature in particular.
On many glaciers in Svalbard, three surface types are visible on SAR images, the dark glacier ice at the glacier's lower end, the brighter superimposed ice in the middle, and the white firn at the higher elevations. Surface classification of these types is valuable especially since the retreat or advance of the firn area provides information on the status of the glacier. While the snowline reacts immediately to annual changes, the firn area smoothes out these short-term changes and shows, similar to the glacier front, longer-term changes of the glaciers.
Glacier Firn Area Change is based on the "Glacier Surface Type - Svalbard" dataset, presenting the actual area value sper glacier and year as tabular data to be plotted graphically