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
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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
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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.
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 .
These data have been collected from an Arctic desert site (latitude 78o57'29N, longitude 12o27'42E), Broeggerhalvoya in western Spitsbergen, 10 km NW from Ny Alesund, 45 m above sea level, 2 km from the shore. This is a low relief tip of a bedrock peninsula covered with several meters of glacial drift and reworked raised beach ridges. The measurements are obtained in the site of well developed patterned ground, sorted polygons, where the influence of plants, including thermal insulation and transpiration, is negligible. The 1985-1986 period was average. Mean annual air temperature was -6.6 C, 0.4 C colder than the long-term (1975-1990) mean, but well within the mean variability. Mean winter air temperature is relatively warm (mean of coldest month, February, is -14.6 C). Annual precipitation was 17 % greater than the ong-term mean (372 mm); however, the number of rain-on-snow events was less (3) than average (5.5). Overall, the reference period is close to long-term averages.
A program of automated soil temperature recordings was initiated in the summer of 1984, at a patterned ground field site Thermistors were placed approximately 0.1 m apart in an epoxy-filled PVC rod (18 mm outside diameter), buried in the center of a fine-grained domain of a sorted circle, down to 1.14 m below the ground surface. The data presented here covers 7/1/85-7/1/86, once a day (6 am), at two levels (0.0 m, 1.145 m below surface). The resolution of the thermistors is 0.004 C, and the accuracy is estimated to be 0.02 C near 0 C. Missing data accounts for less than 7 %. The gaps are filled with simple average of the beginning and end of the gap values. For a detailed description of the field site and data analysis see Putkonen (1997) and Hallet and Prestrud (1986). These data are presented on the CAPS Version 1.0 CD-ROM, June 1998.
Geomorphological mapping was used to prepare a morphodynamic map of Wedel Jarlsberg Land, Svalbard. Zones, profiles, and sites for detailed measurements were selected to determine slope processes in qualitative and quantitative terms. Indices of relief degradation were determined using quantitative data characterizing the intensity of present-day morphogenetic processes and postglacial palaeogeographic information. Data were collected during summer seasons only.
Snow and soil temperature records for January 1988 - May 1996 are presented. Included are snow depth and weight measurements, snow density (calculated), active layer depth in the frost tubes, weight of wet and dried soil samples from unknown depth within the active layer (water content calculated), and soil temperature at the surface (0.05 cm) and to the depths of 3 to 4 meters at 3 sites. The sites are 1) on a road covered by 1 m of gravel underlain by clay; 2) outside a building on piles, (sensors are placed 1 to 2 m from the building wall); and 3) under the building between piles. In addition, air temperature was measured inside the building or between the piles (documentation is not clear on this point.) There are several gaps in temperature measurements (January 1991 to May 1992). These data are presented on the CAPS CD-ROM version 1.0, June 1998.
Air temperature, wind direction, and temperature were measured at 5, 20, 50, 100, 150, and 200 cm below the tundra surface at an undisturbed site; and at 5, 20, 50, 100, 150, 200 cm, and 3 m and 8 m below the concrete surface of a building. Incoming radiation, outgoing radiation, temperature of the heat flux instrument, global radiation, heat flux, wind speed, wind speed maximum, average wind speed, and temperature inside the building were measured since 1993 with data loggers. All data are recorded for July 1987 - February 1996.
This data set consists of Upward Looking Sonar (ULS) data from 11 moorings in the Greenland Sea. Parameters in the processed data files include ice draft, water pressure, and water temperature. Raw data files with sonar travel time, and files with draft frequency of occurrence, are available as well. A single statistical file for each mooring summarizes that mooring's record. These data were contributed by the Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany, in 2002 and 2004, as a contribution to the World Climate Research Programme's Arctic Climate System Study/Climate and Cryosphere (ACSYS/CliC) Project. Data are available via FTP.
NSIDC strongly encourages you to register as a user of this data product. As a registered user, you will be notified of updates and corrections. When registering, please include the title of this data set, AWI Moored ULS Data, Greenland Sea and Fram Strait, 1991-2002.
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2023-12-28T00:00:00Z
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Abstract:
Ground based in situ observations of online_crds at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects EMEP_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), methane in air (mole_fraction_of_methane_in_air), methane in air (mole_fraction_of_methane_in_air)
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2024-02-04T00:00:00Z
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Abstract:
Ground based in situ observations of online_crds at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects EMEP_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), methane in air (mole_fraction_of_methane_in_air), methane in air (mole_fraction_of_methane_in_air)
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2023-12-08T00:00:00Z
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Abstract:
Ground based in situ observations of online_crds at Zeppelin mountain (Ny-Ålesund) (NO0042G). These measurements are gathered as a part of the following projects EMEP_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), carbon_monoxide in air (mass_fraction_of_carbon_monoxide_in_air), methane in air (mole_fraction_of_methane_in_air), methane in air (mole_fraction_of_methane_in_air)
Institutions: NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway, NO01L, Norwegian Institute for Air Research, NILU, Instituttveien 18, 2007, Kjeller, Norway
Last metadata update: 2023-12-19T00:00:00Z
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Abstract:
Ground based in situ observations of ozone at Zeppelin mountain (Ny-Ålesund) (NO0042G) using uv_abs. These measurements are gathered as a part of the following projects EMEP_NRT, GAW-WDCRG_NRT, NILU_NRT and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: ozone in air (mole_fraction_of_ozone_in_air), ozone in air (mass_concentration_of_ozone_in_air)