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 and phrases embedded in quotation marks. Logical operators include AND, OR and NOT. Remember to add space around operators. Text strings that are not quoted are trated as separate words and will match any of the words (i.e. assuming the OR operator). E.g. in order to find WMO synoptic weather station data from Verlegenhuken use the search phrase: [synop AND verlegenhuken]. Searches are case insensitive.
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.
Collections
Collections allows the user to search in subsets of the existing catalogue. The collections are primarily data management projects that have been incorporated in the ADC catalogue after the project has ended. In this context the ADC is the long term access solution for these data. The collections currently served through ADC include (datasets may belong to multiple data collections):
ADC is the full collection of this service CC is the CryoClim collection
In order to search a specific data collection select that collection. If no data collection is selected all collections are searched.
AeN are data related to the Nansen Legacy project and are better explored through the SIOS Data Access Point using the collection defined there which is available through this URL.
SIOS, InfraNOR, SIOSCD, SIOSAP, SESS_* are collections related to SIOS. These are better explored through the SIOS Data Access Portal
Some cleaning is pending between InfraNOR and SIOSIN, for some of the SESS collections.
Citation of data and service
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)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
If you use data retrieved through this portal, please acknowledge the Norwegian Meteorological Institute/Arctic Data Centre.
The data have been collected during with RV Lance 30 July-2 August 2017. Samples have been collected using baited traps in the glacier bay in front of Kronebreen in the inner part of Kongsfjorden.
Quality
Sampling method:
Benthic amphipods were caught in baited traps, in strings of five traps each deployed overnight from Polarcirkel at different locations in the glacial bay outside Kronebreen in. The baited traps consisted of plastic pipe (20 cm long, 10 cm in diameter) with a funnel attached to one end and a removable net (mesh size: 1 mm) on the other. Bait was raw chicken meat packed in fine-mesh bags to prevent the amphipods from getting access to it.
Analyse method:
The collected species were identified under a stereomicroscope.
Header name index
- fieldNumber: sample ID
- expedition: cruise name
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z)
- locationID: station name
- locationID_trap: location number for traps
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- gearType: the gear used to take the sample
- deploymentTimeInDays: duration of the deployment of the traps in days
- trap: The number of the traps
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained.
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the identification.
- organismQuantity: the quantity of the organism per volume water in the environment
- organismQuantityType: ind/trap days
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Monthly mean sea ice draft from the Fram Strait Arctic Outflow Observatory since 1990.
We acknowledge scientists that previously had leading roles with ULS NPI data, Torgny Vinje, Terje Brink Løyning, Edmond Hansen, and Gunnar Spreen. Structure of the data file is described in README.txt in the zip file.
Quality
The sea ice draft is obtained from Upward Looking Sonars (ULS) and Ice Profiling Sonars (IPS) deployed on an east-west oriented mooring array in the western Fram Strait. The section longitude varies from 78.8°N to 79.2°N (except for 1990), depending on year and location of each mooring. Zonal positions of the moorings are approximately 3° W (F11), 4° W (F12), 5° W (F13), and 6.5 / 7.0° W (F14), whereas the exact longitude slightly changes year to year. The exact position of each mooring in each year can be found in each data file as an attribute of the data object. The original data gained from ULS/IPSs are travel times of sound reflected at the bottom of floating sea ice. The raw data are processed to sea ice draft data by ASL Environmental Science Inc., following standard procedures described in Melling et al. (1995) and Fissel et al. (2008). A screening of erroneous data records and sound speed correction was done by ASL Environmental Science Inc. The original ice drift data are averaged over each daily period and then monthly mean ice draft is calculated. Temporal coverage of the daily data are taken into account when calculating the monthly mean draft.
Reference: Melling, H., Johnston, P. H. and Riedel, D. D. Measurements of the Underside Topography of Sea Ice by Moored Subsea Sonar, J. Atmos. Oceanic Technol., 12 (3), 589 – 602, https://doi.org/10.1175/1520-0426(1995)012<0589:MOTUTO>2.0.CO;2 (1995) . Fissel, D.B., Marko, J.R. and Melling, H. Advances in upward looking sonar technology for studying the processes of change in Arctic Ocean ice climate, Journal of Operational Oceanography, 1(1), 9-18, DOI: 10.1080/1755876X.2008.11081884 (2008). ASL Environmental Sciences Inc., Data Processing and analysis of ice keel depths, Fram Strait, 2006-2007. Report for Norsk Polarinstitutt, Tromsø, Norway by ASL Environmental Sciences Inc., Victoria, B.C. Canada (2009).
The data has been collected during the Nansen Legacy Seasonal Study Q3 from 5 - 27 August 2019 on research vessel RV Kronprins Haakon (cruise number 2019706), along a transect in the northern Barents Sea from 76N to 82N. The dataset contains abundance of pelagic marine protists, including phytoplankton (autotrophic) and protozooplankton (heterotrophic). Protists were identified and counted with light microscopy using the Utermöhl method and the result are given as cells per liter (cells/L) called organismQuantity.
Quality
Sampling method:
The samples were collected with Niskin bottles attached to a CTD rosette at the following depths: 5, 10, 30, 60, 90 m and deep chlorophyll max (DCM). The samples were preserved using an aldehyde mixture of glutaraldehyde and hexamethylenetetramine-buffered formalin at final concentrations of 0.1% and 1% respectively.
Analyse method:
All samples have been analysed at Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under an inverted microscope according to the Utermöhl method.
Header name index - events
- expedition: cruise number for R/V Kronprins Haakon
- eventID: UUID for the sample
- parentID: UUID for the gear deployment (each Niskin has a unique parentID)
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- fieldNumber: human-readable sample ID (e.g. PHT-001)
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. Niskin bottle
- samplingDepthInMeters: depth sampled
- sampleType: description of the sample type according to a standard list
- recordedBy: name of the person who took the samples
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Thalassiosira hyalina).
- identificationQualifier: A standard term (sp., spp., and indet.) to express uncertainty in identification.
- lifeStage: the life stage (e.g. resting spore) of the organism.
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in µm.
- organismRemark: indicates e.g. varieties, colony type
- identificationRemarks: a free text field for adding information relevant to the analysis
- identifiedBy: person who did the lab-analyse
- fieldsInCount: Number of fields counted in the microscope
- magnificationMicroscope: The magnification setting used during analysis. Selected from a drop-down menu linked to vocab-sheet
- maxFields: Number of fields in the entire sedimentation chamber (Related to magnification used)
- takenVolumeML: The volume taken for sedimentation in the Utermöhl chamber (the sub-sample taken for analysis)
- identifiedBy: Drop-down menu linked to list in people-sheet
- dateIdentified: Date for the analysis
- sampleSizeValue=(fieldsInCount/maxFields)*(takenVolumeML/convertionMLtoL)*dilutionFactorFormaldehyde), dilutionFactorFormaldehyde = 0.95
- sampleSizeUnit: liter (l)
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: cells/l
Funding:
The Nansen Legacy is funded by the Research Council of Norway and the Norwegian Ministry of Education and Research. They provide 50% of the budget while the participating institutions contribute 50% in-kind. The total budget for the Nansen Legacy project is 740 mill. NOK.
The data set consists of digital elevation models (DEM) of subglacial topography, ice thickness, bathymetry and ice surface elevation of Kongsfjorden, northwestern Svalbard, near Ny-Ålesund (78.9 deg N, 12.4 deg E). The DEMs cover five tide-water glaciers with a grid size of 150 m. The data have a total area of ~1100 km^2 and cover the glaciers Blomstrandbreen, Conwaybreen, Kongsbreen, Kronebreen, and Kongsvegen, including the ice fields Holtedahlfonna and Isachsenfonna. A 50 m resolution DEM is also available for Kronebreen. The compiled data set covers one of the most studied regions in Svalbard and can be valuable for studies of glacier dynamics, geology, hydrology and fjord circulation. For further details see Lindbäck et al. (2018, https://doi.org/10.5194/essd-2018-37).
If you use the data set in presentations and publications please also refer to the peer-reviewed paper (Lindbäck et al., 2018, https://doi.org/10.5194/essd-2018-37). The data set will be updated when the quality of the data is improved or if new data sets become available.
File format: GeoTIFF and ASCII Spatial reference: WGS-1984 UTM Zone 33W
Contact person: Jack Kohler (jack.kohler@npolar.no)
This work was part of the TIGRIF (Tidewater Glacier Retreat Impact on Fjord circulation and ecosystems) project, funded by the Research Council of Norway.
The data has been collected during the Nansen Legacy Joint Cruise 2-1 from 12 - 29 July 2021 on the research vessel RV Kronprins Haakon (cruise number 2021708), along a transect in the northern Barents Sea from 76N to 82N. The dataset contains abundance of ice algae marine protists, including ice algae (autotrophic) and protozoa (heterotrophic). Protists were identified and counted with light microscopy using the Utermöhl method and the result are given as cells per liter (cells/L) called organismQuantity.
Quality
Sampling method:
The samples were collected with Kovacs ice corer 9 cm diameter (Kovacs Enterprise). The samples were collected from the bottom part of the ice core at the following dept layers: 0-3 cm, 3-10 cm, 10-20 cm & 20-30 cm. The ice cores were transferred to a clean bucket and 100mL filtered sea water were added per 1 cm of sea ice and melted at 4°C. When the ice core was melted, 95 mL of the sample was transferred into 100 ml brown glass bottle. The samples were preserved using an aldehyde mixture of glutaraldehyde and hexamethylenetetramine-buffered formalin at final concentrations of 0.1% and 1% respectively.
Analyse method:
All samples have been analysed at Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under an inverted microscope according to the Utermöhl method.
Header name index - events
- expedition: cruise number for R/V Kronprins Haakon
- eventID: UUID for the sample
- parentID: UUID for the gear deployment (each ice core has a unique parentID)
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- fieldNumber: human-readable sample ID (e.g. IAT-001)
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- maximumDepthInCentimeters: bottom depth of the core section in cm
- minimumDepthInCentimeters: upper depth of the core section in cm
- eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. Ice corer 9 cm
- samplingDepthInMeters: depth sampled
- sampleType: description of the sample type according to a standard list
- recordedBy: name of the person who took the samples
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Nitzschia frigida).
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the Identification.
- lifeStage: the life stage (e.g. resting spore) of the organism
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in µm.
- organismRemark: indicates e.g. varieties, colony type
- identificationRemarks: a free text field for adding information relevant to the analysis
- identifiedBy: person who did the lab-analyse
- identifiedBy: Drop-down menu linked to list in people-sheet
- dateIdentified: Date for the analysis
- fieldsInCount: Number of fields counted in the microscope
- magnificationMicroscope: The magnification setting used during analysis. Selected from a drop-down menu linked to vocab-sheet
- maxFields: Number of fields in the entire sedimentation chamber (Related to magnification used)
- takenVolumeML: The volume taken for sedimentation in the Utermöhl chamber (the sub-sample taken for analysis)
- totalMeltedVolumeL: The total melted volume in L recorded during sampling.
- addedFSWvolumeL: Volume in L of filtered sea water added to the sample during melting.
- initialVolumeL: The total volume in L of the melted core, measured during sampling. If it wasn’t measured one can use the theoretical calculated core volume based on diameter of the core. initialVolumeL=(totalMeltedVolumeL-addedFSWvolumeL)) or teoreticalCoreVolumeL = coreAreM*(maxDepthCM-minDepthCM)
- sampleSizeValue=((fieldsInCount/maxFields)(takenVolumeML/conversionMLtoL))(dilutionFactorFormaldehyde*dilutionFactorFSW)), dilutionFactorFormaldehyde = 0.95, dilutionFactorFSW=
- sampleSizeUnit: liter (l)
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: cells/l
- cellsPerM2: The quantity (number of cells) of the organism per area (m2). cellsPerM2 = ((individualCount/(sampleSizeValue/initialVolumeL))/coreAreaM
Funding:
The Nansen Legacy is funded by the Research Council of Norway and the Norwegian Ministry of Education and Research. They provide 50% of the budget while the participating institutions contribute 50% in-kind. The total budget for the Nansen Legacy project is 740 mill. NOK.
Biomarker (HBIs) and stable isotope data (d18O, d13C) from sediment cores HH15-06GC and JR142-11GC. The data originates from two marine sediment cores northeast of Svalbard. Core JR142-11GC was obtained using a gravity corer during a cruise with RSS “James Clark Ross” carried out by British Antarctic Survey in 2006. Core HH15-06GC was also obtained using a gravity corer during a cruise with RV “Helmer Hanssen” carried out by University Centre in Svalbard 2015. The research aims were 1) to investigate cryosphere-ocean linkages during the final decline of the Barents Sea Ice Sheet (BSIS) which may serve as an analogue of modern West Antarctic Ice Sheet (WAIS), and 2) obtain baseline values for natural fluctuations of ocean temperature and sea-ice evolution in northern Barents Sea – Svalbard region.
This dataset contains the primary elevation change and mass balance results for Svalbard from swath processing of CryoSat-2 radar altimetry, 2011-2017 (Morris et al. 2020, J. Geophys. Res.). Svalbard is divided into six subregions: Austfonna (Aust), Vestfonna (Vest), Barentsøya and Edgeøya (BarEd), Northeast Spitsbergen (NESbn), Northwest Spitsbergen (NWSbn), and Southern Spitsbergen (SoSbn). The .csv files contain monthly cumulative mass change for surging, non-surging and all ice in each subregion and the archipelago as a whole (displayed in figures 4 and 5 of the manuscript). The underlying elevation estimates are not corrected for penetration bias, see the manuscript for further discussion. GeoTIFFs in UTM zone 33N projection contain extrapolated and unextrapolated maps of elevation change rate (m/yr), the division of the archipelago into the subregions (1:NESbn, 2:Vest, 3:NWSbn, 4:Aust, 5:SoSbn, 6:BarEd), the fractional ice coverage (0 to 1) on a 1km grid, and a surge mask (1:surge).
The archipelago of Svalbard presently contains approximately 33,200 km2 of glaciers, with a large number of small valley glaciers as well as large areas of contiguous ice fields and ice caps. While a first glacier inventory was compiled in 1993, there has not been a readily available digital version. Here we present a new digital glacier database, which will be available through the GLIMS project. Glacier outlines have been created for the years 1936, 1966-71, 1990, and 2001-2010. For most glaciers, outlines are available from more than one of these years. A complete coverage of Svalbard is available for the 2001-2010 dataset. Glacier outlines were created using cartographic data from the original Norwegian Polar Institute topographic map series of Svalbard as basis by delineating individual glaciers and ice streams, assigning unique identification codes relating to the hydrological watersheds, digitizing center-lines, and providing a number of attributes for each glacier mask. The 2001-2010 glacier outlines are derived from orthorectified satellite images acquired from the SPOT-5 and ASTER satellite sensors. In areas where coverage for all time periods is available, the overwhelming majority of glaciers are observed to be in sustained retreat over the period from 1936-2010.
This study was conducted in a collaboration between the Department of Geoscience, University of Oslo, and the Norwegian Polar Institute, it was supported by the European Space Agency (ESA) through the projects Glaciers_CCI (4000101778/10/I-AM) and Cryoclim, which is also supported by the Norwegian Space Centre.
The dataset contains high resolution seismic reflection profiles from the inner part of Kongsfjorden, printed on paper, with selected profiles photocopied. The profiles were taken in summer 1974 during an investigation into glacial processes and the glacial history of Svalbard by G.S.Boulton. There was no attempt to systematically cover the whole of Kongsfjorden but to establish some profiles in what were judged to be critical or representative locations. It was hoped that the profiling would provide a seismic stratigraphy.
The dataset and data collection methods are described in the attached data report. The printed profiles are in storage at the Norwegian Polar Institute (geology archive).
Quality
The profiling system was based on a multi-electrode sparker. It was an analogue system with real time display of the profiling results, and no recording of the data to enable post acquisition processing. Adjustments to get optimum quality had to be done whist operating in the field situation, sometimes a quite difficult - and frustrating - task. Recording parameters could be quite sensitive.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99938. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99840. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99935. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99740. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99927. Data are climate consistent following a number of automated and manual quality control routines.