The core partner data centres that are integrated in NorDataNet are listed in https://www.nordatanet.no/en/node/69. In addition to this NorDataNet harvests information on relevant datasets from a number of other data centres. The data centre responsible for the data presented is usually (but not always) listed in the discovery metadata. In essence NorDataNet is an aggregating service that combines information from a number of existing data centres.
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source:
Research Council of Norway, project number 245967/F50, Norwegian Scientific Data Network.
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)
All partner repositories of NorDataNet support Digital Object Identifiers (DOI), but not all datasets are minted. Whether or not minted depends often on source of the data (e.g. operational data are often yet not minted). However, all data centres support persistent identifiers according to local systems. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
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 identified in the drop down menu with and phrases embedded in quotation marks. Prefixing a phrase with '-' negates the phrase (i.e. should not occur in the results). 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. The combination of search fields (including facets) is based on a logical "AND" combination of the fields, i.e. all conditions are fulfilled for the results provided.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Arctic ABC Development, Deep Impact, Centre for Autonomous Marine Operations and Systems (NFR grant 245929, NFR project no 300333, NFR project no 223254)
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
Last metadata update: 2022-11-15T15:30:23Z
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Abstract:
UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of an array of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors is mounted on a tripod under a transparent dome. This dataset contains the data of the hyperspectral radiometer USSIMO (In-situ Marine Optics, Perth, WA, Australia), converted to E(PAR) by the following equation: PAR is approximated as an integral of micromolespersec=(uirr/(h*c/(lambda*1e-9)))/microavo for wavelengths(lambda) in range from 400 to 700nm, where: uirr = USSIMO irradiance for wavelength equal to lambda, h=6.63e-34 [Js], c=3.00e+08 [m/s], microavo=6.022e17. The sensor is equipped with a Zeiss MMS1 UV-VIS NIR detector with National Institute of Standards and Technology, USA traceable radiometric calibration between 380 and 900 nm. This instrument is used for time-series measurement of down-welling spectral irradiance in energy Wm-2 nm-1. Spectral resolution is 10 nm (3.3 nm pixel spacing) and a cosine-corrected polytetrafluoroethylene (PTFE) light diffusor with cosine error: <3% (0 - 60°), <10% (60 - 87.5°), is fitted. The device acquired measurements with a 16 bit analogue to digital converter. It samples continuously internally. Integration time is controlled by the sensor depending on the light intensity, with a maximum of 6 seconds. Actual integration time is stored with the data in each sample. The sensor output is saved on a PC with custom software which records 30 seconds of output data every 29:30 min. The number of samples collected in that period depends on the USSIMO integration time. The sensor is equipped with a pitch and roll sensor which is used to ensure that the spectroradiometer remains in the fixed position throughout the time-series acquisition. For re-use of the data, please refer to the dataset and the original publication. This is an aggregated dataset that combines the invidual datasets into a continous timeseries. For details check out https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00039,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00044,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00045 and https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00046.
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
Last metadata update: 2022-11-15T15:30:23Z
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Abstract:
UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of a range of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors, including the camera, is mounted on a tripod under a transparent dome. This dataset contains the E(PAR) data derived from pictures taken during 2017 at hourly intervals by the all-sky-camera. The camera (Canon EOS 5D Mark III) is equipped with a fish-eye lens with a focal length set to 8 mm with aperture manually set to open (f/4) to ensure maximum sensitivity (Canon EF 8-15mm f/4L), providing a 180° image of the atmosphere (only possible with a full-size sensor). Both shutter speed (exposure time, ranging from 0.000125 to 30 seconds) and ISO (sensitivity, ranging from 100 at Midnight Sun period and up to 6400 during Polar Night) are set to auto. White balance manually set to “day light”. It is remotely controlled by a PC, pictures were stored in a cloud storage. Short gaps in the time series are due to power failures. In this dataset there are two large gaps: 2019-01-09 to 2019-03-08 and 2019-06-24 to 2019-09-25 caused by a crash of the controlling PC which was not monitored at that time. The equations for the picture-to-E(PAR) conversion can be found in: Johnsen et al 2021, An all-sky camera system providing high temporal resolution annual time-series of irradiance in the Arctic, Applied Optics. The pictures on which this dataset is based on can be found at . For re-use of the data, please refer to the dataset and the original publication. this is an aggregated dataset where the individual timeseries have been combined into a continous timeseries. For details on the dataset please check https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00040,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00041,https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00042 and https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2021.00043.
The dataset contains 2 archives. The first archive contains all data (saved as netCDF files) relative to the Figures presented in Boutin et al. (2023). The second archive contains monthly averaged fields (saved as netCDF files) of the simulation described in Boutin et al. (2023). They include quantities relative to sea ice properties (icemod files) and to the mass balance (ice growth/melt etc... simba files). They cover the north Atlantic and the Arctic Ocean (north of Bering Strait) for the period 2000-2018.
icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018.Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment).transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport.In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2023-10-30T11:07:22Z
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During the accumulation season, snow samples were collected from the Hansbreen glacier. Few times per season. Snow samples are collected to the polyethylene sterile bags and are taken to the Polish Polar Station Hornsund. After melting at room temperature, the pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical laboratory. Snow chemical composition: major ions, HCO3-, pH, conductivity
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2023-10-30T11:07:22Z
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Since 2004, snow and rain samples have been collected in the Fuglebekken catchment in close vicinity of the Polish Polar Station Hornsund.The rain and snow samples are collected after every event.The pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical laboratory.The rain gauge is checked approximately once a day.
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2023-10-30T11:07:25Z
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Since 2020, during the accumulation season, snow samples are collected from the Ariebreen glacier a few times per season. Snow samples are collected to the polyethylene sterile bags and are taken to the Polish Polar Station Hornsund. After melting at room temperature, the pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical. Site Information Ariebreen - 0.5 km long glacier between Skoddefjellet and the northern part of Ariekammen, southernmost in Wedel Jarlsberg Land.
Instrument/method: Very Broad Band seismological station (VBB-Station) (Operated by: Alfred Wegener Institute for Polar and Marine Research and Univ. of Bergen)
Geosystem monitoring at the Polish Polar Station Hornsund
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2022-04-29T13:30:00Z
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In-house developed time-lapse cameras are installed along the coast of Isbjornhamna, on Ariekammen slopes and in front of the Hansbreen. Imagery is mainly used for calving observations, icebergs tracking and sea ice concentration monitoring. Only raw imagery is avilable.
Institutions: GFZ German Research Center for Geosciences
Last metadata update: 2022-04-29T13:30:00Z
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Seismic data recorded by a permanent seismological station located in Spitsbergen. Seismic records can be used for seismological and cryoseismological studies, data is gathered continuously and access is open.
The data is used in the paper "Dynamic response of a high Arctic glacier to melt and runoff variations", published in Geophysical Research Letters. For more details about the data we refer to the paper (https://doi.org/10.1029/2018GL077252).
The dataset contains a concentration of organochlorine persistent organic pollutants in snow samples collected from top layer of snow, which corresponded to fresh snowfall in most cases (except DS location, where there was a 20 cm top layer sampled weekly). All snow samples have been collected within one month during spring 2019, in the vicinity of the Polish Polar Station Hornsund. Snow sample location names ending in .1, .2 and .3 are local replicates of the same sample, i.e. the snow sampled according to the same protocol, samples taken within the spacing of 1-3 m from one another. Sample locations H, R, F and DS refer to: Hans glacier, Revdalen (valley), Fugleberget slope, and the Environmental hut (chamber) of the Polish Polar Station, respectively. All concentrations are given in ng/L of melted snow (water), i.e. ng/kg snow. Compound names are given at the top of columns denoting concentrations, for which an average of 3 analytical replicates and a standard deviation of those replicates is reported.The dataset is part of a project funded by SIOS (Svalbard Integrated Arctic Earth Observing System) Research Infrastructure Access Project 2018_0009 Sval-POPs: Spatial VAriabiLity: VALidation dataset on POPs concentrations in snow.
Data belonging to the manuscript: "Individual particle characteristics, optical properties and evolution of an extreme long range transported biomass burning event in the European Arctic (Ny-Ålesund, Svalbard Islands)" Journal of Geophysical Research: Atmospheres, 125(5), e2019JD031535
Results of the geochemical and magnetic studies on natural mineral aerosol deposited and trapped in glaciers (cryodust). Samples were collected from glacial cores taken from five glaciers of Southern Spitsbergen (Svalbard, Norway). The samples were collected by means of a hand-operated Kovacs Enterprise® Mark II coring system. Samples (90 mm in diameter) were packed into polyethylene bags, secured, and transported to the Polish Polar Station Hornsund. The core samples were rinsed using deionized water (Polwater DL100; Norm PN-EN ISO 117 3696:1999; conductivity <0.06 μS/cm) and melted at room temperature in the closed new polyethylene bags. After melting samples were filtered through pre-rinsed sterile Millipore Mixed Cellulose Esters filters (white gridded and 0.45 𝜇𝜇m pore size). After filtration, the filters with residuum were dryer at the temperature of 60oC.Solid particulates of cryodust were subjected to analysis by Electron MicroProbe (EMP) with special attention paid to their internal structure. A scanning electron microscope (SEM) fitted with a backscattered electron (BSE) detector was used to trace grains topography and composition. Special attention was given to monazite chemical dating. Magnetic methods comprised analyses of magnetic susceptibility κ vs temperature T variations and determination of magnetic hysteresis parameters.More about the methodology, analyses and results can be found here: https://doi.org/10.3390/atmos11121325