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.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
Underlying dataset for the Lavergne et al. (2020) manuscript in EGU The Cryosphere Discussion. Processed from GCOM-W1 AMSR2 36.5 GHz (Ka-band) imagery. See the manuscript for more details.
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.
a) Sea bed mapping and b) Glacial geological and paleo climatic research.Acustical profile data from seismic, penetration echo sounder and side-scanning sonar.
The Nansen Legacy cruise Q1 was part of the seasonal investigation of the northern Barents Sea and adjacent Arctic Basin. The cruise was conducted in 2-24 March 2021 onboard R/V Kronprins Haakon, and focused on studying the physical, chemical and biological conditions along the Nansen Legacy main transect in open waters and within the sea ice. While in sea ice we conducted ten regional scale sea ice helicopter-borne surveys of ice conditions along the Nansen Legacy transect using a helicopter-borne electromagnetic instrument (HEM) EM-bird. This dataset presents processed EM-bird data on total snow and sea-ice thickness along the flight tracks.
This is a contribution to the Research Council of Norway project “Nansen Legacy” (https://arvenetternansen.com/), WP RF-1 “Physical drivers”.
Quality
See the attached docuement “AeN_Q1_202103_HEM_icethickness_metadata_v1.0.pdf” for details on the data acqusition, processing and structure.
The dataset includes water column measurements of spectral beam attenuation and absorption coefficients by non-water constituents. Measurements were collected in May 2021 during cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. The WET Labs ac-s spectrophotometer (Seabird Scientific) were used to collect in situ profiles, with a constant descent velocity (∼0.3 m/s) down to a depth of 350 m, or ~10 m below the ocean floor. Measurements were corrected for temperature and salinity effects. The proportional method was used to correct the scattering error of the absorption measurements, assuming zero absorption at 709 nm. The measurements were binned with 2.0 m (dbar) spacing, applying the median to average the data. See the referenced article for more information.
Ocean data from two ocean moorings, M1 and M2. Both were Nansen Legacy gateway moorings deployed in the northern Barents Sea at potential “gateways” of ocean exchange with the north and east. The moorings were equipped with ADCPs measuring ocean currents, and temperature and conductivity-temperature-pressure sensors at various points along the mooring line:
- Conductivity, temperature, and pressure from RBR Concerto and SBE16plus v2 instruments.
- Temperature from RBR Solo instruments.
- Near-surface ocean currents from upward-looking Nortek Signature 500 kHz ADCP instruments.
- Water column currents from upward-looking RDI 150 kHz ADCP instruments.
The current version of the dataset (V1) contains data from the two first deployments of M1 and M2, covering the period from October 2018 to September 2020.
The document “M1_M2_data_processing_details_2018_2020.pdf” contains further details about the data and processing, as well as important information for users of the data.
The Norwegian Polar Institute is the owner of all the instrumentation described in this document, and was responsible for data processing and documentation. Data are freely available under a CC-BY 4.0 license.
VERSION HISTORY:
V1 (27-07-2022): Created dataset, uploaded raw and processed data for M1 and M2 (2018-2020) with documentation.
Processed data are organized per mooring and deployment. E.g., “m1_2.zip” contain processed data from deployment 2 (2019-2020) of the M1 mooring, etc. All raw data are collected in “raw_m1m2_2018_2020.zip”.
Quality
Data are available both in raw form and as netCDF files with processed data. The document “M1_M2_data_processing_details_2018_2020.pdf” contains further details about the data and processing, as well as important information for users.
Inherent optical data collected in Storfjorden (Svalbard) in June 2020 onboard the coast guard vessel KV Svalbard during the Useful Arctic Knowledge project summer school. This data was collected as part of the Nansen Legacy project. Optical data collected includes in situ measurements of absorption and attenuation, accompanied by in situ profiles of salinity, temperature, pressure (CTD) and dissolved organic matter fluorescence (3-channel fluorometer).
Water samples were collected for measurements of dissolved (colored dissolved organic matter, CDOM) absorption, and material was collected on filters for determination of particulate absorption by phytoplankton and non-algal particles, and the stable oxygen isotopic composition of seawater.
The data is available in netcdf files or individual CSV files.
Absorption_Cruise_UAK2020.nc: contains the measurements of CDOM and particulate absorption from water samples. In_Situ_Absorption_Attenution_Cruise_UAK2020: contains the in situ measurements of spectral absorption and attenuation
The CSV files in this collection include the spectral measurements of optical properties as follows:
icam_aphy.csv: Phytoplankton absorption coefficient (in 1/m) as measured with the QFT-ICAM technique
icam_anap.csv: Non-algal particle absorption coefficient (in 1/m) as measured with the QFT-ICAM technique
Perkin_ap.csv: Total particle absorption coefficient (1/m) as measured with the QFT_Perkin technique
O18.csv: Oxygen isotope ratio (δ18O, in ‰ against VSMOW)
acs_fdom_ctd: High vertical resolution in situ cast data: total non-water absorption (1/m) and attenuation (1/m), Fluorescence by Dissolved Organic Matter (FDOM, raw digital signal counts), water salinity (practical salinity scale) and temperature (degrees Celsius).
FDOM was measured at three excitation/emission pairs as follows: Channel 1 (Ch1, 310/450 nm) that represents marine ultraviolet humic-like and marine humic-like material; for Channel 2 (Ch2, 280/450 nm) represents terrestrial humic-like material; and for Channel 3 (Ch3, 280/350 nm) represents protein-like tryptophane type material.
The details of the data processing are described in the published paper (see link below).
M2 acoustic presence of marine mammals and anthropogenic noise manually counted for the period 2019-2020
Quality
Daily acoustic presence of the different sound sources (marine mammals, vessels and airguns) manually identified (except blue and fin whale, automatically detected using spectrogram correlation in Ishmael) during the manual inspection of spectrograms from each acoustic file (one file per hour) for the available data period 2019/2020 in M2, Svalbard. The M2 AURAL recorder sampled 12 min each hour during the given data period.
Variables: dt: date Month: Categorical variable with the name of the month Week: number of week since beginning of the study period Bowhead: acoustic presence of Balaena mysticetus Bowsong: acoustic presence of Balaena mysticetus songs Narwhal: acoustic presence of Monodon monoceros Narwhistle: acoustic presence of Monodon monoceros tonal sounds Walrus: acoustic presence of Odobenus rosmarus Bearded: acoustic presence of Erignathus barbatus Vessel: acoustic presence of vessel noise Odontocete: acoustic presence of odontocete-like whistle and tonal sounds non idetinfied to spp. level Airgun: acoustic presence of airgun blasts Harp: acoustic presence of Pagophilus groenlandicus Humpback: acoustic presence of Megaptera novaeangliae Blue: acoustic presence of Balaenoptera musculus Fin: acoustic presence of Balaenoptera physalus
Root Mean Squared (RMS) Sound Pressure Levels (SPL) were calculated for the one-Third Octave Level (TOL) bands centered at 63 Hz, 125 Hz and 250 Hz; and for the broadband 50-1000 Hz using PAMGuide package (Merchant et al. 2015) and custom-made MATLAB code. One RMS SPL value per file was obtained, averaging 12 min of recording in M2.
Variables: time: datetime TOL63HZ: Sound Pressure Level for the third-octave level band centered at 63 Hz TOL125HZ: Sound Pressure Level for the third-octave level band centered at 125 Hz TOL250HZ: Sound Pressure Level for the third-octave level band centered at 250 Hz BB501000: Sound Pressure Level for the broadband 50-1000 Hz
The dataset includes spectral absorption coefficients of colored dissolved organic matter (CDOM), ’particulate matter and non-algal particles in seawater. Samples were collected in May 2021 as part of cruise 2021704, Q2, in the northern Barents Sea as part of the Nansen Legacy project. Sea water was sampled using Niskin bottles attached to a rosette onboard R/V Kronprins Haakon. CDOM samples were filtered through a 0.22 μm cartridge filter, and measured on a 1 m liquid waveguide capillary cell (LWCC). Particulate absorption measured on 0.7 μm pore size GFF filters (25 mm diameter, nominally 1 liter filtered volume), and measured on a Lambda 950 UV-Vis-NIR spectrophotometer and QFT-ICAM absorption meter. Non-algal particle absorption is measured after bleaching the filters using H2O2.
Fatty acid-specific stable isotopes of the fatty acids 16:1(n-7), 20:5(n-3) and 22:6(n-3) in pelagic particulate organic matter (PPOM), ice-associated particulate organic matter (IPOM) and pelagic zooplankton species (copepods, krill, amphipods, chaetognaths, appendicularians) collected from the Barents Sea during Nansen Legacy seasonal cruise Q3 in August 2019