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.
Centre for Sustainable Arctic Marine and Coastal Technology, Arctic Offshore and Coastal Engineering in a Changing Climate, Programme for International Partnerships for Excellent Education, Research, and Innovation, Dynamics of Floating Ice, Large-scale Programme for Petroleum Research, Survey to assess harp and hooded seal pup production in the Greenland sea pack-ice in 2018, Integrated System for Operations in Polar Seas, Nansen Legacy, Dynamics of Floating ice, Australian Antarctic Program projects 4593 and 4506, Joyce Lambert Antarctic Research Fund grant no. 604086, Research Council of Norway grant no. 280625, Fram 2020, Arctic Challenge for Sustainability II, JSPS KAKENHI Grant Numbers JP 19H00801, 19H05512, 21K14357 and 22H00241, Survey to assess harp and hooded seal pup production in the Greenland sea pack-ice in 2022, SURVEYS TO ASSESS HARP AND HOODED SEAL PUP PRODUCTION IN THE GREENLAND SEA PACK-ICE IN 2022 (SAMCoT, AOCEC, INTPART, DOFI, PTEROMAKS2, ISOPS, AeN, ArCS II)
Institutions: Norwegian Meteorological Institute (MET), University of Melbourne, College of Fisheries and Ocean Sciences, University of Tokyo, Havforskningsinstituttet, Norwegian Meteorological Institute / Arctic Data Centre
Sea ice drift trajectories and waves in sea ice data collected over the period 2017-2022 by a consortium of researchers, both in the Arctic and the Antarctic.
As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. This dataset contains the CTD, PAR and fluorescence data from Kongsfjorden 2017-2018. Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. No post-recovery processing of light data (to correct for fouling) has been performed. The observatory layout is available in the mooring diagram provided.
The A-TWAIN cruise onboard R/V Lance in September 2017 covered the region north of Svalbard for mooring deployments and transects across the Atlantic Water inflow along the continental slope. Vertical profiles of temperature, salinity and Chlorophyll a (Chla) fluorescence were taken using the ship-board CTD consisting of a SBE911+ and Wetlab ECO-AFL/FL fluorometer mounted on a rosette frame. Water samples were taken from the CTD rosette at 11-12 depths throughout the water column for determination of Chla, and inorganic nutrients (nitrate plus nitrite (NO3− plus NO2−), phosphate (PO43-) and silicic acid (Si(OH)4 )/silicate (SiO2);concentrations in mmol m−3) For Chla, triplicates of 200 ml were filtered onto GF/F glass microfiber filters (Whatman, England) and 10 µm Isopore membrane polycarbonate filters (Millipore, USA) and frozen until further processing back in the laboratory at UiT The Arctic University of Norway. At UiT, samples were extracted in 5ml of methanol in darkness at 4C for ca. 24 h (Holm-Hansen and Riemann, 1978) and measured with a 10-AU Turner fluorometer (Turner, USA). CTD fluorometer measurements were calibrated against these in situ Chlorophyll a measurement using linear regression to derive vertical profiles of absolute Chlorophyll a concentrations. For inorganic nutrients, water samples of 200 mL were collected in acid-washed plastic bottles or in new and rinsed falcon tubes (3x 50 ml) and immediately frozen at -20C until further processing. Following standard methods (Grasshoff et al., 2009) back in the laboratory at UIT The Arctic University of Norway (Tromsø), three replicates were analyzed for each sample. Samples were measured with a Flow Solution IV Analyser (OI Analytical, USA) calibrated with reference sea water (Ocean Scientific International Ltd., UK). The detection limits were 0.02 mmol m−3 for nitrate plus nitrite, 00.1 mmol m−3 for phosphate and 0.07 mmol m−3 for silicic acid. The study was funded by the Fram Centre project A-TWAIN, project no. 66050.
Holm-Hansen, O., Riemann, B., 1978. Chlorophyll a determination: improvements in methodology. Oikos 30, 438–447. https://doi.org/10.2307/3543338. Grasshoff, K., Kremling, K., Ehrhardt, M., 2009. Methods of Seawater Analysis. John Wiley&Sons, Edition 3, pp. 632
Datasets collected during TW-ICE cruise to Kongsfjorden in July 2017. The datasets contain measurements close to glacier fronts taken with a research vessel and helicopter, and have been published in Halbach et al. (2019; see the “Citation Custom” field).
The datasets are compiled following files:
Nutrient data.csv Nutrient measurements together with station metadata. Columns: station = station name; vessel = either the research vessel (Lance) or helicopter; lon = longitude as decimal degrees (WGS84); lat = latitude as decimal degrees (WGS84); date = date in ISO8601 format; area = zone used in the article; dist = distance from the closest glacier front in km; depth = bottom depth in m at the station; from = the water depth from which the sample was collected in m; sal = salinity from the closest CTD; temp = water temperature from the closest CTD; type = water type classification based on salinity and temperature (see the article); ctd.name = name of the closest CTD cast; chla = chlorophyll a in mg m-3; phaeo = phaeophytin in mg m-3; tsm = total suspended matter in g m-3; no2 = nitrite concentration in mmol m-3; no3 = nitrate concentration in mmol m-3; sioh4 = silicate concentration in mmol m-3; po4 = phosphate concentration in mmol m-3; nh4 = ammonium concentration in mmol m-3; urea = urea concentration in mmol m-3.
Phytoplankton data.csv Phytoplankton taxonomy data together with station metadata. Columns: station = station name; lon = longitude as decimal degrees (WGS84); lat = latitude as decimal degrees (WGS84); date = date in ISO8601 format; area = zone used in the article; dist = distance from the closest glacier front in km; depth = bottom depth in m at the station; from = the water depth from which the sample was collected in m; sal = salinity from the closest CTD; temp = water temperature from the closest CTD; type = water type classification based on salinity and temperature (see the article); ctd.name = name of the closest CTD cast; group = coarse functional grouping; species = species or taxa; abundance = abundance of the species in cells dm-3.
CTD data.json CTD data in a list format. See the oce-class (https://www.rdocumentation.org/packages/oce/versions/1.0-1/topics/ctd-class) documentation for the oce R package for further details on formatting. The results are from a Sea-Bird SBE 9 (Lance) and Hydro-Bios Multi-Water-Sampler (helicopter).
Water type data.csv Water type classification data together with station metadata. Columns: row_id = unique ID for a CTD cast; station = station name; vessel = either the research vessel (Lance) or helicopter; lon = longitude as decimal degrees (WGS84); lat = latitude as decimal degrees (WGS84); date = date in ISO8601 format; area = zone used in the article; depth = bottom depth in m at the station; ctd.name = name of the closest CTD cast; type = water type classification based on salinity and temperature (see the article); freq = frequency of 1 decibar bins containing the given water type; per = percentage of 1 decibar bins containing the given water type as compared to total number of bins for a CTD cast.
Mixed layer data.csv Mixed layer data. Columns: station = station name; ctd.name = name of the closest CTD cast; pres = pressure of the maximum N2 bin in decibars; sal = salinity at the maximum N2 depth; temp = water temperature at the maximum N2 depth in Celsius; rho = potential water density at the maximum N2 depth; n2 = the maximum Brunt-Väisälä-frequency during CTD cast close to the surface; mld = estimated mixed layer depth based on maximum N2 in m.
Euphotic depth data.csv Euphotic depth data. Columns: station = station name; depth = depth of the estimated euphotic depth in m; par = photosynthetically active radiation at the euphotic depth; spar = photosynthetically active radiation on the surface; per = percentage ratio between par and spar.
Power Spectral Densities were calculated using the PAMGuide package (Merchant et al. 2015) in MATLAB. The analysis was performed for the frequency band 10-4000 Hz (1 Hz resolution, 60s spectral averages, 50% overlap, Hanning window). The file is the raw output format provided by PAMGuide so it can be manipulated and visualized using the PAMGuide package in MATLAB.
Time-series data from moorings covering the Svalbard Branch of the Atlantic Water inflow over the upper continental slope north of Svalbard, Sep 2017 to Nov 2019. The data comprise temperature, salinity and other parameters from CTDs, and water currents from ADCPs.
Data are published as individual time-series files from the different instruments. Both raw (RDI .000 format) and processed (netCDF) ADCP data are published.
Quality
Data processed with standard software from the instrument manufacturers plus additional quality controls to remove bad data points. Details of ADCP processing and quality control are described in the documentation PDF.
Hydrographic and current time series data from outside the northern side of the Isfjorden Mouth during 5 October 2017 to 24 August 2018 at 78°10.911’ N; 013°23.350’ E, and 242 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor outflow from Isfjorden and the hydrographic differences between the northern and southern part of the mouth. It was equipped with two Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and three VEMCO mini temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2020).
Reference: Skogseth R., Olivier L.L.A., Nilsen F., Falck E., Fraser N., Tverberg V., Ledang A.B., Vader A., Jonassen M.O., Søreide J., Cottier F., Berge J., Ivanov B.V., and Falk-Petersen S. (2020). Variability and decadal trends in the Isfjorden (Svalbard) ocean climate and circulation – an indicator for climate change in the European Arctic, Progress in Oceanography, 187, DOI: doi.org/10.1016/j.pocean.2020.102394.
Quality
Pressure, temperature and salinity data have been despiked with a window size of 60 and a standard deviation of 2. Temperature and salinity data have been calibrated against nearby SBE 911+ CTD profiles taken during the deployment period. At the same time, care was taken to keep the water column stable. No pressure and conductivity data on SBE 37 10963, and no pressure data on AADI Seaguard 1705.
The data set contains daily sea ice concentrations for each of the 42 Nansen Legacy stations for the period 2017-2021 derived from AMSR-2 and AMSR-E sea ice concentrations products. The data set is complemented with local sea ice concentration from visual bridge-based observations of the state of sea ice pack conducted following ASSIST Ice Watch protocol during some of the Nansen Legacy cruises to the study area.
This is a contribution to the Research Council of Norway project “Nansen Legacy” (https://arvenetternansen.com/), WP RF-1 “Physical drivers”.
Quality
For details on the data product see the attached file NL_stations_ice_concentration_2017-2021_metadata.pdf
The data has been collected during a cruise with RV Lance from 30 July to 2 August 2017. Samples have been collected from in front of tidewater glaciers by use of MIK nets and baited traps.
The dataset contains stable isotope ratios as d13C (‰) and d15N (‰) and trophic level. For the fish species the stomach content, stomach content wet weight and the degree of filling are also recorded.
Quality
Sampling method:
Zooplankton and fish were collected from RV Lance using a Methot-Isaac-Kidd (MIK) ring net (3.15 m2 opening, 13-m long net with 1500 μm pore size and a 500 μm mesh in the last metre), fitted with a 10-L cod end. Benthic amphipods were collected with baited traps in strings of five traps each deployed overnight at different locations in the glacial bay outside Kronebreen.
Analyse method:
All samples have been analysed at Institute for Energy Technology (IFE) according to their standard procedure, described briefly here:
- Lipids and non-dietary carbon (i.e. carbonates) are removed from samples prior to analyses since lipids have a high turnover and are depleted in 13C relative to other body compounds. The removal of lipids will also reduce differences in stable isotope composition due to variations in body lipid content, and therefore make the C:N ratios more comparable among species.
- Lipids are removed by Soxhlet extraction with CH2Cl2 : 7% CH3OH for approx. 2h, washing with 2N HCl and distilled water to neutral pH. The samples are dried at 80°C for 12h, weighed and transferred into 9*15 mm tin capsules. Approximately 1 mg of the sample was used.
- The sample was combusted in the presence of O2 and CrO3 at 1700°C in a Eurovector element analyser. Reduction of NOx to N2 was done in Cu oven at 650 °C.
- H2O was removed in a chemical trap of KMnO4.
- N2 and CO2 were separated on a 2 m Poraplot Q GC column.
- The C/N ratio was quantified on basis of TCD results from the GC
- N2 and CO2 were directly injected on-line to Nu Instrument Horizon, Isotope Ration Mass Spectrometer for determination of δ13C and δ15N.
Accuracy & precision:
The accuracy and precision of δ13C and δ15N analyses are tested by replicate analysis of an internal standard (IFE trout) every 10 samples.
Presentation of results
Stable isotope ratios are expressed as the deviation from standards in ppt (‰) according to the following equation:
δX=[(R”sample” /Rstandard)*1000]
X = 13C or 15N and R = the corresponding ration 13C/12C or 15N/14N International standards, Pee Dee Belemnite for δ13C (PDB: USGS 24), and atmospheric air for δ 15N (IAEA-N-1 and 2,) were used to determine R standard.
Data structure:
The data is following Darwin Core nomenclature as far as possible but also includes variables that aren’t supported by Darwin Core. All information about the sampling such as eventDate, latitude, longitude, depts etc is located in event file while the result such as N, C etc. are found in the stable isotope file. The fieldNumber would be the link between the stable isotope and event files.
Header name index - events
- fieldNumber: sample ID (e.g. SI-044)
- expedition: cruise name
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- area: the area groups used in the publication “Tidewater glaciers as “climate refugia” for zooplankton-dependent food web in Kongsfjorden, Svalbard”
- 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. MultiNet 180 µm
- maximumDepthInMeters: bottom depth of the sampled layer
- minimumDepthInMeters: top depth of the sampled layer
- 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 – stable isotope
- 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
- lifeStage: the age class, life stage, or life form/morph of the organism.
- sizeGroup: the size group in mm.
- tissue: the tissue of the sample used for stable isotope analysis
- d13C (‰): stable isotope ratios of carbon expressed as the deviation from standards in ppt (‰)
- d15N (‰): stable isotope ratios of nitrogen expressed as the deviation from standards in ppt (‰)
- trophicLevel: The trophic level of a consumer can be calculated as the difference between δ 15N and the food web baseline assuming a constant fractionation between trophic levels according to the following equation: TL= α+ (δ15 N consumer/δ15 Nbase)/∆N
- W% C: Dry Weight % Carbon
- W% N: Dry Weight % Nitrogen
- C/N ratio: The ration of carbon to nitrogen
- IFE Lab ID: ID used at Institute for Energy Technology (IFE) when analysing the samples The following terms are recorded only for fish samples:
- stomachContent: The species found in the stomach
- stomachContent_wetWeight (mg): The wet weight (mg) of the stomach content
- stomachFilling: The percentage filling of th estomach
Conductivity-Temperature-Depth (CTD) profiles from Norwegian Polar Institute (NPI) cruise FS2017 to the Fram Strait including auxiliary sensors. Fram Strait cruises are repeated annually, and a new data set is published for each cruise.
Please refer to the FS2017 cruise report for full information. Profiles were collected with a SBE911+ CTD system deployed over the side of research vessel Lance. Temperature profiles were measured using dual SBE 03 temperature sensors. Conductivity profiles were measured using dual SBE 04 conductivity sensors. Salinity profiles were calculated from temperature and salinity profiles. CDOM was measured using a WETLabs CDOM fluorometer (single sensor).
Profile data is from down casts only and made available in 1 decibar bins. Spurious data collected during the surface soak were removed before binning.
Data are made available as a single, self-documented netCDF file. Profile data are organised in tables with one column per cast and one row per depth bin. 1-dimensional metadata (such as time and position) are organised as a single row with one column per cast. All variables have the same number of columns, equal to the total number of CTD casts.
Kongsfjorden acoustic presence of marine mammals and anthropogenic noise manually counted for the period 2017-2018
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 2017/2018 in Kongsfjorden, Svalbard. The Kongsfjorden AURAL recorder sampled 15 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 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 Humpback: acoustic presence of Megaptera novaeangliae Sperm: acoustic presence of Physeter macrocephalus Blue: acoustic presence of Balaenoptera musculus Fin: acoustic presence of Balaenoptera physalus Sei: acoustic presence of Balaenoptera borealis
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 15 min of recording in Kongsfjorden.
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
Hydrographic and current time series data from outside the southern side of the Isfjorden Mouth during 5 October 2017 to 25 August 2018 at 78°03.653’ N; 013°31.346’ E, and 202 m depth. The mooring was deployed by the University Centre in Svalbard (UNIS) as a part of the AGF course “Polar Ocean Climate” to monitor inflow of Atlantic Water to Isfjorden, and was equipped with three Aanderaa Instruments recoding current meters (RCMs) with auxiliary CTD sensors covering the upper, the intermediate, and the bottom layer. Additionally, three SBE 37 MicroCAT CTDs and five VEMCO mini temperature loggers were evenly distributed over the water column. For further details of the mooring and data, see Skogseth et al. (2020).
Reference: Skogseth R., Olivier L.L.A., Nilsen F., Falck E., Fraser N., Tverberg V., Ledang A.B., Vader A., Jonassen M.O., Søreide J., Cottier F., Berge J., Ivanov B.V., and Falk-Petersen S. (2020). Variability and decadal trends in the Isfjorden (Svalbard) ocean climate and circulation – an indicator for climate change in the European Arctic, Progress in Oceanography, 187, DOI: doi.org/10.1016/j.pocean.2020.102394.
Quality
Pressure, temperature and salinity data have been despiked with a window size of 60 and a standard deviation of 2. Temperature and salinity data have been calibrated against nearby SBE 911+ CTD profiles taken during the deployment period. At the same time, care was taken to keep the water column stable.
MET Norway's operational ocean model ROMS is run on the NorKyst-800m
grid, a polar-stereographic grid covering the Norwegian coastal zone
with 800 m grid spacing. The model is run daily (00UTC) with
atmospheric forcing from Arome2.5km, vertical boundary conditions
from Nordic-4km, and tides from TPXO 7.2, to provide forecasts to
+66 hrs.
The daily operational runs are joined into a long timeseries using a
best estimate approach.
Institutions: UiT The Arctic University of Norway, UiT The Arctic University of Norway, UiT The Arctic University of Norway, Norwegain Infrastructure for Research Data (NIRD)
This dataset includes taxonomy and daily vertical export rates of planktonic protist cells, planktonic protist carbon (PPC), and zooplankton abundance and biomass fluxes. Samples were collected from long-term sediment traps deployed on moorings north and northeast of Svalbard from October 2017 to October 2018, as part of the Nansen Legacy (UiT, NO) and Arctic PRIZE (SAMS, UK).