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 data set contains daily sea ice concentrations for each of the 42 Nansen Legacy stations for the period 2017-2021 derived from AMSR-2 and AMSR-E sea ice concentrations products. The data set is complemented with local sea ice concentration from visual bridge-based observations of the state of sea ice pack conducted following ASSIST Ice Watch protocol during some of the Nansen Legacy cruises to the study area.
This is a contribution to the Research Council of Norway project “Nansen Legacy” (https://arvenetternansen.com/), WP RF-1 “Physical drivers”.
Quality
For details on the data product see the attached file NL_stations_ice_concentration_2017-2021_metadata.pdf
Sea ice salinity and temperature mesured on ice cores collected on the Nansen Legacy seasonal cruises in the Barents Sea and Nansen Basin. The sea ice cores were collected on seven Nansen Legacy research cruises (Q1, Q2, Q3, Q4, JC1-2, JC2-1, JC3) onboard RV Kronprins Haakon between February and December in 2018-2022.
Quality
Data of salinity and temperature measured on sea ice cores collected on seven Nansen Legacy research cruises (Q1, Q2, Q3, Q4, JC1-2, JC2-1, JC3) onboard RV Kronprins Haakon between February and December in 2018-2022, covering seasonal data in the Barents Sea and Nansen Basin. The ice stations followed Nansen Legacy standard stations (P, M, NLEG, PICE, SICE) on a south-north (76N-83N) repeated transect. Method: Sea ice cores were collected using a Kovacs corer (Ø=9cm) and ice temperature (WVR temperature sensor) was meaured at every 5 cm of the core. The core was cut into 10 cm pieces, melted and salinity (WTW 3310 conductivity sensor) was measured in the lab onboard. Different cores were used in this data set; “chem core” is the main core, “alkalinity core” is extra core and “NaN” is mostly due to collection by the sea ice physics team.
Centre for Sustainable Arctic Marine and Coastal Technology, Arctic Offshore and Coastal Engineering in a Changing Climate, Programme for International Partnerships for Excellent Education, Research, and Innovation, Dynamics of Floating Ice, Large-scale Programme for Petroleum Research, Survey to assess harp and hooded seal pup production in the Greenland sea pack-ice in 2018, Integrated System for Operations in Polar Seas, Nansen Legacy, Dynamics of Floating ice, Australian Antarctic Program projects 4593 and 4506, Joyce Lambert Antarctic Research Fund grant no. 604086, Research Council of Norway grant no. 280625, Fram 2020, Arctic Challenge for Sustainability II, JSPS KAKENHI Grant Numbers JP 19H00801, 19H05512, 21K14357 and 22H00241, Survey to assess harp and hooded seal pup production in the Greenland sea pack-ice in 2022, SURVEYS TO ASSESS HARP AND HOODED SEAL PUP PRODUCTION IN THE GREENLAND SEA PACK-ICE IN 2022 (SAMCoT, AOCEC, INTPART, DOFI, PTEROMAKS2, ISOPS, AeN, ArCS II)
Institutions: Norwegian Meteorological Institute (MET), University of Melbourne, College of Fisheries and Ocean Sciences, University of Tokyo, Havforskningsinstituttet, Norwegian Meteorological Institute / Arctic Data Centre
Sea ice drift trajectories and waves in sea ice data collected over the period 2017-2022 by a consortium of researchers, both in the Arctic and the Antarctic.
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
This dataset includes concentrations of Particulate Organic Carbon (POC) and Particulate Organic Nitrogen (PON) from the sea water and sea ice. Samples were collected in February and March 2022 as part of cruise 2022702, JC3, in the northern Barents Sea as part of the Nansen Legacy project. Sea water was sampled at seven different stations using Niskin bottles attached to a rosette onboard R/V Kronprins Haakon. At three of these stations we also conducted sea ice work and sampled sea ice cores (gear: Kovacs ice corer 9cm) and under-ice water (gear: Niskin bottle) for POC/PON analysis. For sea water water triplicate subsamples (1000–2000 mL) were filtered on pre-combusted Whatman GF/F filters, the limited volume of melted sea ice allowed only one but occasionally triplicates subsamples (250-2000 mL). Filters were stored at −20 °C, and analyzed within 1 years on a Leeman Lab CHN Analyzer according to the procedures described by Reigstad et al. (2008). Presented are averaged POC and PON values (in mg m-3), standard deviations and the C:N ratio. PON values < 3x blank values were excluded from the dataset.
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).
The Nansen Legacy/Synoptic Arctic Survey Joint Cruise 2 (JC2-2) was part of the seasonal investigation of the northern Barents Sea and adjacent Arctic Basin. The multidisciplinary cruise was conducted in Aug 24 – Sep 25 of 2021 onboard R/V Kronprins Haakon, and focused on studying the physical, chemical and biological conditions in ocean, atmosphere and sea ice. While in sea ice, we conducted ten regional scale sea ice helicopter-borne surveys of ice conditions 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 document “AeN_JC22_2021_09_EMB.pdf” for details on the data acquisition, processing and structure.
Ocean microstructure profiles from a physical oceanography cruise in August-September 2021, in the Nansen and Amundsen Basin on R/V Kronprins Haakon, KH2021710. The data set includes 80 profiles of 1-decibar vertically averaged dissipation rate of turbulent kinetic energy, in situ temperature (ITS-90 scale) and salinity (practical salinity scale).
Quality
Profiles are collected using Sea and Sun Technology vertical microstructure profiler (MSS90L). The first 9 profiles are made with MSS053, the next ones with MSS046. The MSS90L is loosely tethered and is deployed using a winch, electric on board and maunal on the sea ice. Dissipation rate is measured using two airfoil shear probes. 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. Careful corrections for temperature/conductivity sensor time lag and thermal lag were made. Temperature and salinity were corrected after comparison with the ship CTD. An offset of +0.055 is applied for profiles 28:80. Only downcasts from MSS90L are processed using the Sea and Sun technology routines. Resulting profiles are quality controlled, but still require caution from the user. More details are provided in the cruise report.
This dataset includes concentrations of Particulate Organic Carbon (POC) and Particulate Organic Nitrogen (PON) from the sea water and sea ice. Samples were collected in August and September 2021 as part of cruise 2021710, JC2-2, in the northern Barents Sea and the Arctic basin as part of the Nansen Legacy project. Sea water was sampled at seven different stations using Niskin bottles attached to a rosette onboard R/V Kronprins Haakon. At three of these stations we also conducted sea ice work and sampled sea ice cores (gear: Kovacs ice corer 9cm) and under-ice water (gear: Niskin bottle) from a hole in the ice and water from meltponds (gear: bucket) for POC/PON analysis. For sea water water triplicate subsamples (1000–9500 mL) were filtered on pre-combusted Whatman GF/F filters, the limited volume of melted sea ice allowed only one but occasionally triplicates subsamples (290-2350 mL). Filters were stored at −20 °C, and analyzed within 1 years on a Leeman Lab CHN Analyzer according to the procedures described by Reigstad et al. (2008). Presented are averaged POC and PON values (in mg m-3), standard deviations and the C:N ratio. PON values < 3x blank values were excluded from the dataset.
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).
This dataset includes concentrations of Particulate Organic Carbon (POC) and Particulate Organic Nitrogen (PON) from the sea water and sea ice. Samples were collected in April-May 2021 as part of cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. Sea water was sampled at seven different stations using Niskin bottles attached to a rosette onboard R/V Kronprins Haakon. At three of these stations we also conducted sea ice work and sampled sea ice cores (gear: Kovacs ice corer 9cm) and under-ice water (gear: Niskin bottle) from a hole in the ice for POC/PON analysis. For sea water triplicate subsamples (500–1500 mL) were filtered on pre-combusted Whatman GF/F filters, the limited volume of melted sea ice allowed only one but occasionally triplicates subsamples (200-2000 mL). Filters were stored at −20 °C, and analyzed within 1 years on a Leeman Lab CHN Analyzer according to the procedures described by Reigstad et al. (2008). Presented are averaged POC and PON values (in mg m-3), standard deviations and the C:N ratio. PON values < 3x blank values were excluded from the dataset
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
Show more...
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).
The dataset includes water column measurements of spectral beam attenuation and absorption coefficients by non-water constituents. Measurements were collected in May 2021 during cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. The WET Labs ac-s spectrophotometer (Seabird Scientific) were used to collect in situ profiles, with a constant descent velocity (∼0.3 m/s) down to a depth of 350 m, or ~10 m below the ocean floor. Measurements were corrected for temperature and salinity effects. The proportional method was used to correct the scattering error of the absorption measurements, assuming zero absorption at 709 nm. The measurements were binned with 2.0 m (dbar) spacing, applying the median to average the data. See the referenced article for more information.
The dataset includes spectral absorption coefficients of colored dissolved organic matter (CDOM), ’particulate matter and non-algal particles in seawater. Samples were collected in May 2021 as part of cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. Sea water was sampled using Niskin bottles attached to a rosette onboard R/V Kronprins Haakon. CDOM samples were filtered through a 0.22 μm cartridge filter, and measured on a 1 m liquid waveguide capillary cell (LWCC). Particulate absorption measured on 0.7 μm pore size GFF filters (25 mm diameter, nominally 1 liter filtered volume), and measured on a Lambda 950 UV-Vis-NIR spectrophotometer and QFT-ICAM absorption meter. Non-algal particle absorption is measured after bleaching the filters using H2O2.
This dataset includes concentrations of Particulate Organic Carbon (POC) and Particulate Organic Nitrogen (PON) from the sea water and sea ice. Samples were collected in April-May 2021 as part of cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. Sea water was sampled at seven different stations using Niskin bottles attached to a rosette onboard R/V Kronprins Haakon. At three of these stations we also conducted sea ice work and sampled sea ice cores (gear: Kovacs ice corer 9cm) and under-ice water (gear: Niskin bottle) from a hole in the ice for POC/PON analysis. For sea water triplicate subsamples (500–1500 mL) were filtered on pre-combusted Whatman GF/F filters, the limited volume of melted sea ice allowed only one but occasionally triplicates subsamples (200-2000 mL). Filters were stored at −20 °C, and analyzed within 1 years on a Leeman Lab CHN Analyzer according to the procedures described by Reigstad et al. (2008). Presented are averaged POC and PON values (in mg m-3), standard deviations and the C:N ratio. PON values < 3x blank values were excluded from the dataset.