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 Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available insitu observations. This dataset is the predecessor of the gridded ice charts based on satellite data and other sources. This dataset primarily identifies the sea ice edge.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available satellite data and insitu observations and provides a gridded map. It is a continuation of the previous sea ice chart which basically identified the ice edge.
Institutions: Norwegian Computing Center, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-24T19:38:41Z
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Abstract:
The CryoClim FSC product provides daily information on fractional snow cover(0-100 %) per grid cell for global land areas except permanent snow and iceareas with 5 km grid size. The product is based on multi-sensor/time-series fusion of AVHRR, SMMR, SSM/I and SSMIS data eliminating cloud cover and polar night, resulting in a temporally consistent snow map.
Institutions: Norwegian Computing Center, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-24T23:12:54Z
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Abstract:
The CryoClim FSC product provides daily information on fractional snow cover(0-100 %) per grid cell for global land areas except permanent snow and iceareas with 5 km grid size. The product is based on multi-sensor/time-series fusion of AVHRR, SMMR, SSM/I and SSMIS data eliminating cloud cover and polar night, resulting in a temporally consistent snow map.
Institutions: UGOT Göteborg University Department of Oceanography - Earth Sciences Centre, Norwegian Meteorological Institute / Arctic Data Centre, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
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Abstract:
Surface pCO2 data in the Arctic Ocean collected during: ARKIV3 87, IAOE 1991,
AOS94, ACSYS96, JOIS97, AO02 and Beringia 2005. The pCO2 data is computed from
total alkalinity and total dissolved inorganic carbon.
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.
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.
Institutions: AWI Alfred Wegener Institute for Polar and Marine Research, Norwegian Meteorological Institute / Arctic Data Centre, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-08-25T10:27:10Z
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Abstract:
Data of drop sondes released from an aircraft during cold-air outbreaks over the Fram Strait (4 March 1993). 7 profiles of temperature, humidity and wind are available as a function of distance to the pack ice edge. Details in Lüpkes and Schlünzen 1996, BLM, 79,107-130.
Institutions: Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T13:56:05Z
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Abstract:
The climate in Svalbard has been warming dramatically compared with the global average for the last few decades. Seasonal snow cover, which is sensitive to temperature and precipitation changes, is therefore expected to undergo both spatial and temporal changes in response to the changing climate in Svalbard. This dataset contains a daily snow cover fraction maps for the Svalbard archipelago, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra data.
Institutions: Geological Survey of Denmark and Greenland (GEUS), Geological Survey of Denmark and Greenland (GEUS), Norwegian Meteorological Institute / Arctic Data Centre
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, SU Stockholm University, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
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Abstract:
Arctic Ocean Experiment 2001 AOE-2001 was an icebreaker based field experiment
with a target on the formation of low clouds in the central Arctic summer during
July and August 2001. A main portion of the 2-moth experiment was a 3-week ice
drift from 89 to 88 degN. Main components of the meteorology part of the
experiment were surface-based remote- sensing observations, general meteorology
observations (weather staion and soundings) and boundary-layer observations on
the ice. For a complete review of the experiment and a full list of instruments,
see Tjernström et al. 2004 ("The summertime Arctic atmosphere: Meteorological
measurements during the Arctic Ocean Experiment (AOE-2001)" in Bulletin of the
American Meteorological Society, 85, 1305 - 1321, and its on-line supplement
"Experimental equipment: A supplement to The summertime Arctic atmosphere:
Meteorological measurements during the Arctic Ocean Experiment (AOE-2001)").
Observations included in the dataset:
Observations from 2D-wind sonic anemometer on the mast of Oden during AOE-2001. Beware of flow distortion from the ship.
One-hour averaged cloud base observations from cloud base lidar and cloud radar during AOE-2001
Instant cloud-top observations from S-band cloud radar operating in two modes, a low-range high-resolution and a high-range low-resolution mode, respectively, obtained during AOE-2001. The presented data is the highest cloud top altitude observed.
Various meteorological observations from a mast placed on an ice-floe during AOE-2001
Turbulence statistics from sonic anemometer at 15 meters on the mast averaged over 15 minute obtained during AOE-2001
Turbulence statistics from sonic anemometer at 5 meters on the mast averaged over 15 minute obtained during AOE-2001
Various meteorological observations from Odens weather station situated at 35 metres ASL during AOE-2001. Winds may be subject to considerable flow distortion. Precipitation is in arbitrary units.
One-hour averaged precipitation from present-weather-sensor, which measures no. of precip particles falling past the sensor, during AOE-2001
Wind profile data from 915 MHz profiler on foredeck of Oden obtained during AOE-2001
Atmospheric baloon sounding data obtained during AOE-2001. The observations are interpolated to a fixed grid for plotting purposes.
Measurements from the high range of the S-band cloud radar obtained during AOE-2001. The variables presented are radar reflectivity and hydro-meteor fall velocity.
Measurements from the low range of the S-band cloud radar obtained during AOE-2001. The variables presented are radar reflectivity and hydro-meteor fall velocity.
Temperature profiles measured by a scanning radiometer obtained during AOE-2001.
Measurements from the sodar obtained during AOE-2001. Note that the altitude for each record varies in time.
Observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Observations 5 metres AGL from mobile ISSF PAM station 2 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Observations 5 metres AGL from mobile ISSF PAM station 3 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
One-hour averaged visibility observations from back-scatter sensor during AOE-2001.
Institutions: IOPAS, IOPAS, Tropos, PMOD/WRC, PMOD/WRC, NILU, AWI, UVa-GOA, IGFPAS, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
High resolution aerosol optical depth from Sverdrup Station in Ny Ålesund (instruments: PFR, lunar PFR), AWIPEV Station in Ny-Ålesund (instruments: SP1A, Cimel), Polish Polar Station at Hornsund (instrument: Cimel), RV Oceania and RV Polarstern (instrument: Microtops), as part of the ReHearsol Project.
Institutions: NORCE Tromsø, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-05T13:18:30Z
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Abstract:
Sentinel-1 Wet snow product: The warming climate on Svalbard impacts the amounts of wet snow significantly. Sentinel-1 is sensitive to wet snow as compared with dry snow or bare soil, and the current dataset provides up to daily maps over Svalbard of the spatial distribution of wet snow. The maps are derived from three SAR instriments (Envisat ASAR 2004-2012, Radarsat-2 2012-2014, and Sentinel-1 A/B from 2014-2020). Grid cells are classified with codes where 20=water, 30=nodata, 100=bare ground, 200=dry snow, 205=wetsnow
Automatic weather station (AWS) on Etonbreen glacier, an outlet from the Austfonna ice cap in North-East Svalbard. The AWS is located at approx 360 m a.s.l. near the long term equilibrium line altitude. The AWS records variables needed for an energy balance assessment. The AWS records Air Temperature, Relative Humidity, Wind Direction and Speed, Air Pressure, Snow Height, Longwave and Shortwave radiations. Data are transferred by Iridium. The extended AWS is the same type of station with heated and ventilated radiation in addition.