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 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.
Observing earth critical zone processes in the bayelva basin (CZO@Bayelva)
Data represents the average values and the corresponding standard deviation obtained from each plots at different site along the transect CCT-airport. Each average value is obtained as a mean over a set of more than 20 point measures for each plot and each sampling date. Flux data are complemented by measurements of soil temperature and volumetric water content. data obtain using accumulation chamber and portable probe.
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.
Ocean microstructure profiles from Kongsfjorden August 2021. This dataset includes 75 profiles of 0.5-decibar vertically averaged dissipation rate of turbulent kinetic energy, in situ temperature (ITS-90 scale) and salinity (practical salinity scale). Profiles are collected using Sea and Sun Technology vertical microstructure profiler (MSS90L) SN#046. Dissipation rate is measured using two airfoil shear probes. Dissipation rate profiles are averages from the two shear probes. The temperature and salinity profiles are measured from the SBE sensors on the same instrument. MSS90L has an unpumped CTD system. Only downcasts are used. Data has been processed using the Sea and Sun technology routines. The sensors were calibrated before data collection. Resulting profiles are quality controlled, but still require caution from the user. For more details contact arild.sundfjord@npolar.no
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
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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).
SUDARCO, The Fram Strait Arctic Outflow Observatory, Arctic PASSION, Atlantic-Arctic Distributed Biological Observatory (A-DBO)
Last metadata update: 2023-12-04T17:11:12Z
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Abstract:
Conductivity-Temperature-Depth (CTD) profiles from Norwegian Polar Institute cruise AO-I-2023 to the Fram Strait. The dataset includes profiles of sensor temperature, conductivity, dissolved oxygen, chlorophyll fluorescence, coloured dissolved organic matter fluorescence, beam attenuation, and calculated practical salinity (EOS-80). Profile data are from down casts only and made available in a vertical resolution of 1 decibar (i.e. averaged into 1-decibar bins). The dataset also includes laboratory measurements of salinity and chlorophyll a from Niskin bottle samples. Laboratory results for several core parameters are to be added successively. The data are contained in a single, self-documenting netCDF file. Profile data are organised in arrays with one column per cast and one row per depth bin (pressure bin). Bottle data are organised in arrays with one column per cast and one row per Niskin bottle. One-dimensional metadata (such as time and position) are organised as a single row with one column per cast. Two-dimensional metadata (such as sample number) relate to Niskin bottle data and are organised in arrays with one column per cast and one row per Niskin bottle. All variables have the same number of columns, equal to the total number of CTD casts. For full information on the sampling and processing routines, please refer to the AO-I-2023 cruise report (https://hdl.handle.net/11250/3089166) and the CTD post-cruise processing report (included as file here).
Svalbard rock ptarmigan spring breeding habitat suitability raster map from Pedersen et al. (2017). The habitat suitability map was developed using 11 years (2000–2010) of presence/absence data of territorial males from monitoring, a multi-scale generalized linear modelling framework (glms), and digital satellite-based vegetation mapping. The final habitat model contained four significant predictors related to vegetation, terrain (elevation and slope) and heat load index. High values indicate better breeding habitat suitability. Spatial resolution of the map is 100 x 100 m. Provided in UTM 33N / WGS84 (CRS: 32633). See Pedersen et al. (2017) for more information.
Pedersen, Å.Ø., Fuglei, E., Hörnell-Willebrand, M., Biuw, M. and Jepsen, J.U. (2017), Spatial distribution of Svalbard rock ptarmigan based on a predictive multi-scale habitat model. Wildlife Biology, 2017: 1-11 wlb.00239. https://doi.org/10.2981/wlb.00239
We used an extensive dataset of GPS-collared adult Svalbard reindeer females (2009–2018; N = 268 individual-years) to model summer and winter habitat selection as a function of remotely sensed environmental variables, and subsequently built habitat suitability models using an ensemble modelling framework. The predictor variables used in the final ensemble models were total biomass, curvature, elevation, distance from bird cliff, NDVI, slope, vegetation type and ruggedness. The raster values in the final winter (mean_winter9vars) and summer (mean_summer9vars) habitat suitability maps range from 0-1 where values close to 0 indicate low habitat suitability and values closer to 1 indicate high habitat suitability. The spatial resolution for both maps is 30 m. The raster layers are provided with the coordinate system UTM 33N WGS 84 (CRS: 32633). For more information see Pedersen et al. (2023).
Å.Ø. Pedersen, E.M. Soininen, B.B. Hansen, M. Le Moullec, L.E. Loe, I.M.G. Paulsen, I. Eischeid, S.R. Karlsen, E. Ropstad, A. Stien, A. Tarroux,H. Tømmervik, and V. Ravolainen. 2023. High seasonal overlap in habitat suitability in a non-migratory High Arctic ungulate. Global Ecology and Conservation 45: e02528. DOI: 10.1016/j.gecco.2023.e02528
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.
Snow Core Data (SnowCorD)
Project start: 2021-05-01 - end: 2025-12-31
The estimation of the Fractional Snow-Covered Area in the Brøgger Peninsula ensambling processed imagery located at different sites with different spatial resolutions. This dataset will be aimed to support the estimation of cryospheric information using remotely sensed data. The Ensembled FSCA retrievals are obtained, at the moment, by terrestrial photography applications established at the Amundsen-Nobile Climate Change Tower, at the Zeppelin observatory and at the Gruvebadet Snow Research Site in the Kongsfjorden area.
Dissolved inorganic nutrients (nitrate, phosphate and silicic acid) from the combined Nansen Legacy and A-TWAIN cruise Mooring service cruise 2021 (cruise 2021713).
The cruise 2021713 in November 2021 aboard the Research Vessel Kronprins Haakon is part of the projects A-TWAIN and the Nansen LEGACY. The A-TWAIN project is focusing on monitoring of the Atlantic Water boundary current north of Svalbard. The Nansen LEGACY is the Norwegian Arctic research community’s joint effort to establish a holistic understanding of a changing marine Arctic climate and ecosystem.
Water column temperature and salinity profiles were obtained with a conductivity-temperature-depth (CTD) sensor system Sea-Bird SBE 911+ mounted on a General Oceanics rosette sampler equipped with 24 Niskin bottles used for seawater sampling of chemical variables in the water column. Samples for the determination of dissolved inorganic nutrients were collected from full water column at a total of six stations starting from the shelf northern Barents Sea to the Nansen Basin along the moored A-TWAIN line. The seawater samples were collected from Niskin bottles in 20 ml plastic HDPE vials (rinsed three times) and preserved with 250 µL chloroform and stored +4C and dark until post-cruise analysis of nitrite (NO2), nitrate (NO3-), phosphate (PO43-), and silicate (Si(OH)4), using spectrophotometry according to standard protocols (Grasshoff et al., 2009; Gundersen et al., 2022) at the chemical laboratory at Institute of Marine Research, Bergen, Norway. Three replicates were analyzed for each sample. The detection limits based on QUASIMEME ring-test are 0.06 µmol/L, 0.5 µmol/L, 0.06 µmol/L and 0.7 µmol/L for NO2, NO3-, PO43-, and Si(OH)4, respectively. The sampling and sample analysis were supported by the Research Council of Norway through the projects The Nansen LEGACY (RCN #276730) and SIOS-InfraNor (RCN #269927).
This dataset is a collection of averaged acid-corrected Chlorophyll a (Chla) and phaeopigments, and inorganic nutrient measurements taken as part of the combined Nansen Legacy and A-TWAIN mooring service cruise onboard RV Kronprins Haakon in November 2019, covering the northern Barents Sea and the Atlantic Water inflow region north of Svalbard. Water samples were taken from the CTD rosette at 11-12 depths throughout the water column for determination of Chla, and inorganic nutrients (nitrate plus nitrite (NO3− plus NO2−), phosphate (PO43-) and silicic acid (Si(OH)4 )/silicate (SiO2);concentrations in mmol m−3). For Chla, triplicates of 200 ml were filtered onto GF/F glass microfiber filters (Whatman, England) and frozen until further processing back in the laboratory at UiT The Arctic University of Norway. At UiT, samples were extracted in 5ml of methanol in darkness at 4C for ca. 24 h (Holm-Hansen and Riemann, 1978) and measured with a Turner Triology (Turner, USA). For inorganic nutrients, water samples of 200 mL were collected in acid-washed plastic bottles or in new and rinsed falcon tubes (3x 50 ml) and immediately frozen at -20C until further processing. Following standard methods (Grasshoff et al., 2009) back in the laboratory at UIT The Arctic University of Norway (Tromsø), three replicates were analyzed for each sample. Samples were analysed with a QuAAtro39 AutoAnalyzer (SEAL Analytical), calibrated with reference sea water (Ocean Scientific International Ltd., UK), with detection limits of 0.02 mmol m−3 for nitrate plus nitrite, 0.01 mmol m−3 for nitrite, 0.004 mmol m−3 for phosphate and 0.02 mmol m−3 for silicate (SiO2). The sampling and sample analysis were supported by the Research Council of Norway through the projects The Nansen LEGACY (RCN #276730) and SIOS-InfraNor (RCN #269927), and the Fram Centre project A-TWAIN, project no. 66050.
Holm-Hansen, O., Riemann, B., 1978. Chlorophyll a determination: improvements in methodology. Oikos 30, 438–447. https://doi.org/10.2307/3543338. Grasshoff, K., Kremling, K., Ehrhardt, M., 2009. Methods of Seawater Analysis. John Wiley&Sons, Edition 3, pp. 632