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 SAON Data Portal.
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 through the drop down menu above the text field. Text strings that are not quoted are treated as separate words and will match any of the words (i.e. assuming the OR operator). Phrases may be prefixed with '-' to indicate no occurence of the phrase in the results.
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.
Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are daily composites of merged sensor (MERIS, MODIS Aqua, SeaWiFS LAC & GAC, VIIRS, OLCI) products. MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007. VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2013; and at the third stage OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30. VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA/s l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.12 (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with polymer. The Rrs were binned to a sinusoidal 1km level-3 grid, and later to 1km geographic projection, by Brockmann Consult/s SNAP. Derived products were generally computed with the standard algorithmsthrough SeaDAS. QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting. The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships. Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated accorsing to Jackson et al. (in prep).
Institutions: UNIS, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-02-28T13:00:00Z
Show more...
Abstract:
Wave observations from a buoy located in Isfjorden at Svalbard. This dataset contains several sub datasets representing different variables and time periods.
Near-surface remote sensing techniques including hyperspectral sensors are essential monitoring tools to provide spatial and temporal resolution. More frequent and finer scale observations help to monitor specific plant communities and accurately time the phenological stages of vegetation and snow cover, A Hyperspectral field sensor (FloX) was installed as an integral part of an automatic system for monitoring vegetation and environmental seasonal changes (phenology) on Svalbard (AsMoVEn) funded by SIOS. The fluorescence box (FloX) is a unique instrument, enabling continuous observation of sun-induced chlorophyll fluorescence (SIF). FLoX measures spectral data of extremely high resolution, The FloX is specifically designed to passively measure chlorophyll fluorescence under natural light conditions. The core of the system is the QEPro spectrometer from Ocean Optics covering the Red/Near Infrared region (650 – 800 nm) with a spectral resolution (FWHM) of 0.3 nm. This is the spectral range where chlorophyll fluorescence is emitted and where the two atmospheric oxygen absorption bands (O2B and O2A, at 689 nm and 760 nm respectively) are used to measure it. The FLoX has an additional spectrometer measuring in visible and NIR-region (400– 950 nm) with a spectral resolution (FWHM) of 1.5 nm allowing extraction of different vegetation indices from the visible and near-infrared region.
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
Show more...
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
Show more...
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.
Geophone and Hydrophone deployments in Svalbard 2022, to measure the vibrations in sea ice following the appearance of cracks. For more information, see https://github.com/jvoermans/Geophone_Logger .
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
Show more...
Abstract:
The daily analysis of sea ice concentration is obtained from
operational satellite images of the polar regions. It is based on
atmospherically corrected signal and a carefully selected sea ice
concentration algorithm. This product is freely available from the
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI
SAF). The Eumetsat identifier for the product is OSI-401.
License : All intellectual property rights of the OSI SAF products belong to EUMETSAT. The use of these products is granted to every interested user, free of charge. If you wish to use these products, EUMETSAT's copyright credit must be shown by displaying the words "copyright (year) EUMETSAT" on each of the products used.
Access: Open
EUMETSAT Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)
Institutions: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2024-05-02T11:12:00Z
Show more...
Abstract:
The daily analysis of sea ice concentration is obtained from
operational satellite images of the polar regions. It is based on
atmospherically corrected signal and a carefully selected sea ice
concentration algorithm. This product is freely available from the
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI
SAF). The Eumetsat identifier for this product is OSI-401.
License : All intellectual property rights of the OSI SAF products belong to EUMETSAT. The use of these products is granted to every interested user, free of charge. If you wish to use these products, EUMETSAT's copyright credit must be shown by displaying the words "copyright (year) EUMETSAT" on each of the products used.
Access: Open
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway
Last metadata update: 2024-01-19T11:29:43Z
Show more...
Abstract:
An X-ray scan of Priapulopsis bicaudatus. Sample collected by Bodil Bluhm in field (2019-08-16), preserved in 70% EtOH, then stored as a voucher specimen at The Arctic University Museum of Norway with collection number TSZY 427. Before scanning the specimen was encapsuled in wax, then imaged in a Zeiss Xradia Versa 620.
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.
On Svalbard, the long-lasting snow cover and the timing of the snowmelt is a crucial factor in the yearly cycle of all land ecosystems. To monitor the timing and patterns of snow melt, automatic camera systems have been set up at three locations overlooking key research areas near Ny-Ålesund, Svalbard. All images are provided in daily resolution, and the date coded in the filename as yyyy-MM-dd. This work was funded by SMACS (project no. 236768 / E10; Svalbard Science Forum, Research Council of Norway). ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.846617"!
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegain Infrastructure for Research Data (NIRD)
A set of auroral all-sky images captured over Svalbard in 2019-2020. Images contain auroral emission and have been automatically classified for auroral morphology. Morphological classes are included.
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2023-10-30T11:07:22Z
Show more...
Abstract:
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