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.
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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.
These datasets contain 100 continuous grids of ice thickness, bed topography, and topographic adjustments to geothermal heat flow in the region surrounding Dome Fuji, East Antarctica. Continuous ice thickness grids were created using publicly available measurement data and sequential gaussian simulation to generate statistically likely values between measurements. The simulation was run 100 times to create the ice thickness grids, which were then used to calculate bed elevation by subtracting from REMA ice surface elevations, and the local topographic impacts on background geothermal heat flow. The results are in raster format (.tif) and are projected in an EPSG: 3031 Antarctic Polar Stereographic coordinate system. The spatial extent is 596000 m to 1020000 m Easting and 816000 m to 1240000 m Northing with cell size 500 m x 500 m (848 columns, 848 rows). Ice-thicknesses are provided in meters and bed elevations are in meters referenced to the WGS84 Ellipsoid.
This dataset contains annual polygon shapefiles of complete Svalbard coastlines, produced as a part of the project Copernicus Glacier Service.
The dataset is planned to be updated with new coastlines every autumn.
Quality
This product has been generated by combining the S100 coastline (standard map product) with annual glacier calving fronts (separate dataset). Only glacier fronts have been updated annually, so land-based coastlines refer to the standard map products in most areas or to summer 2020 Sentinel-2 imagery for areas that have changed nearby glacier fronts. The reference data for glacier fronts are mainly Sentinel-2 or Landsat-8 imagery acquired in the period 15 Aug. to 15 Sept. each year.
Digital geological map of Svalbard at the scale of 1:250000.
Subdivision of geology is according to stratigraphic group, subgroup or formation, depending on which is best applicable to the given scale. Where no formations are defined in parts of the geological basement, lithological units are defined instead.
Quality
Spatial Reference: WGS84/UTM zone 33N (EPSG: 32633)
Conductivity-Temperature-Depth (CTD) profiles with auxiliary sensor data from Norwegian Polar Institute cruise Arctic Ocean 2023 - 2 from north of Svalbard, across the shelf slope, and into the deep Nansen Basin of the Arctic Ocean between 10-29 August 2023. Three stations - 182, 216, and 221 - were part of the A-DBO (https://arcticpassion.eu/adbo/) network. The dataset includes profiles of sensor temperature, conductivity, uncalibrated dissolved oxygen, chlorophyll fluorescence, colored dissolved organic matter (CDOM) fluorescence (voltage only), beam attenuation, and calculated practical salinity (EOS-80). Profile data are from down casts only and available in a 1 decibar vertical resolution (i.e. averaged into 1-decibar bins). Chlorophyll fluorescence was calibrated against sample bottles using linear regression through the origin, excluding values larger than 8 mg/m3 (Figure 1 in summary_CTD_AO-II-2023_CTD.pdf). The salinity was verified against sample bottle salinities (Figure 2 in summary_CTD_AO-II-2023_CTD.pdf). Additionally, parameters for temperature, conductivity, salinity, chlorophyll, and beam attenuation are provided for the sampled bottle depths (named NISKIN_*).
The data are contained in a single, self-documenting netCDF file. Profile data are organized in arrays with one column per cast and one row per pressure bin (BIN_*). Data corresponding to the bottle depths are organized similarly, with one column per cast and one row per Niskin bottle. For stations 179-192 and 215-221 a rosette with 24 bottles was used and for stations 193, 195-214 a rosette with 12 Niskin bottles. For the latter, maximum of 12 topmost rows in the array are filled. 1-dimensional metadata such as time and position are organized in a row-vector with one value per cast. All variables have the same number of columns, equal to the total number of CTD casts. For more information on the sampling routines, please refer to the AO-II-2023 cruise report (https://hdl.handle.net/11250/3114227). The CTD post-cruise processing included the removal of salinity spikes. The primary conductivity sensor was of better quality than the secondary sensor and data from the primary sensors were selected to be included.
This dataset consists of three MetOcean SVP (Surface velocity profilers, MetOcean 2014) buoys deployed on Arctic sea ice during the CIRFA 2022 cruise in western Fram Strait (see Figure 1). At the time of the deployment the sea ice was stationary (fast ice) due to connection to grounded icebergs. Later (June 5, 2022, for SVP #1; June 20, 2022, for SVP #2 and SVP #3) the fast ice disconnected and started drifting. Each SVP includes a GPS, air pressure and temperature sensors connected to an Iridium modem and mounted inside a waterproof ruggedized buoy.
Data are time series and include time, latitude, longitude, air temperature inside buoy (°C), air pressure (mbar), pressure tendency (mbar), and battery voltage (V) for each of the three buoys after they were deployed (see Table 1). The measurement interval was initially 60 minutes, then changed in July 2022 to 30 minutes, later in November 2022 changed to one reading per 24 hours or 48 hours (see Table 2). The time series ended when the buoys became stationary (75.1°N for SVP #1, Sep 26, 2022; 65.8°N for SVP #2, Oct 30, 2022) or reached positions further south than 52.3°N for SVP #3 (Jan 17, 2023) / reaching 58.1°N f (Mar 29, 2023).
The average snow depth upon installation was 29 cm for SVP #1 site, 26 cm for SVP #2 site, and 12 cm for SVP #3 site. Temperature might be biased because of solar radiation; the sensor is neither ventilated nor placed in a radiation shield. SVP #1 IMEI 300234064770040; SVP #2 IMEI 300234064772040; SVP #3 IMEI 300234064776030.
Conductivity-Temperature-Depth (CTD) profiles from Norwegian Polar Institute cruise AO-I-2023 to the Fram Strait. The dataset includes profiles of sensor temperature, conductivity, dissolved oxygen, chlorophyll fluorescence, coloured dissolved organic matter fluorescence, beam attenuation, and calculated practical salinity (EOS-80). Profile data are from down casts only and made available in a vertical resolution of 1 decibar (i.e. averaged into 1-decibar bins). The dataset also includes laboratory measurements of salinity and chlorophyll a from Niskin bottle samples. Laboratory results for several core parameters are to be added successively. The data are contained in a single, self-documenting netCDF file. Profile data are organised in arrays with one column per cast and one row per depth bin (pressure bin). Bottle data are organised in arrays with one column per cast and one row per Niskin bottle. One-dimensional metadata (such as time and position) are organised as a single row with one column per cast. Two-dimensional metadata (such as sample number) relate to Niskin bottle data and are organised in arrays with one column per cast and one row per Niskin bottle. All variables have the same number of columns, equal to the total number of CTD casts. For full information on the sampling and processing routines, please refer to the AO-I-2023 cruise report (https://hdl.handle.net/11250/3089166) and the CTD post-cruise processing report (included as file here).
Svalbardreinen anses å være forholdsvis stasjonær, og opptrer i mer eller mindre isolerte delbestander på Svalbard. I sin forvaltning finner Sysselmannen det i dag hensiktsmessig å dele Svalbard inn i 13 slike enheter, som vil være gjenstand for endring når ny kunnskap tilsier det.
Datasettet viser områder med begrensninger på jakt utover dei generelle reglane i Svalbardmiljølova på Svalbard.
Rundt Longyearbyen er forskrift om skyteforbud på høring i 2012. Planlagt utvidelse av skyteforbudssonendenne sonen. Følgjande forskrifter regulerer forbudsområder for jakt på Svalbard:
- Skyteforbudssone rundt Longyearbyen
- Alt vilt freda (=jaktforbud) i naturreservat på østsvalbard og i fuglereservat
- Rypejakt tillatt etter søknad i Sør-Spitsbergen, Forlandet og Nordvest-Spitsbergen nasjonalparker
- Bjørnøya naturreservat
- Hopen naturreservat
- Moffen naturreservat
- Midterhuken Reinsjakt og fangst av fjellrev er kun tillatt i nærmere bestemte områder.
Endringer i jaktforbudsområder krever i de fleste tilfeller endring av forskrifter.
Quality
Scale Range: Maximum (zoomed in) 1:5000; Minimum (zoomed out) 1:150000000 Spatial Reference: WGS84/UTM zone 33N (EPSG: 32633)
The Climate Change Tower Integrated Project (CCT-IP) represents the guide lines of the italian research in the arctic and aims to study the interaction between all the components of the climate system in the Arctic. The Amundsen-Nobile Climate Change Tower (CCT) is the key infrastructure of the project, and provides continuous acquisition of the atmospheric parameters at different heights as well as at the interface between the surface and the atmosphere.
Turbulent parameters are measured at the Amundsen-Nobile Climate Change Tower (CCT) by means of a Gill R3 sonic anemometer installed at 7.5 m from the ground since 2010. It measures the three components of the wind (u, v and w) and the sonic temperature at a rate of 20 Hz. These micro-meteorological measurements are complemented by standard meteorological ones at 4 levels: 2, 5, 10 and 33 m (acquisition time step equal to 1 minute). From these measurements, sensible heat flux, friction velocity and roughness length are calculated.
Wind components and sonic temperature measurements were used to estimate friction velocity and kinematic heat flux. Before computing the micrometeorological parameters, a preliminary analysis is applied in order to assess the data quality and to remove low quality records. After the quality analysis application, mean values of the turbulence statistics were computed following two coordinate rotations to ensure the mean lateral and vertical velocities were zero (McMillen, 1988). Half-hour turbulent statistics (heat fluxes and friction velocity) were derived using two time-scales: a standard averaging time of 30 min and a reduced one (2 min) necessary for filtering out submeso motions contributions that can greatly alter the estimation of turbulent fluxes in a strong and long-lived stable BL. The short averaging time scale was evaluated on the basis of spectral analysis of data in order to include all turbulent scales, but excluding submeso motions (larger than turbulence). The turbulent statistics evaluated over the short subsets and then re-averaged over 30 min following Vickers and Mahrt (2006).
Turbulent parameter relative to unfavorable wind direction ([150÷270] degrees) for which the tower was upwind of the sonic anemometer were not discarded but are flagged (flagdir=1) in the final dataset. More, the percentage of NaNs relative to each run is indicated.
The wind speed vertical profile measured by slow response standard meteorological anemometers at 2, 5, 10 and 33 m was used for estimating the roughness length assuming a typical log wind profile under statically neutral conditions.
Mahrt, L., 1998. Flux Sampling Errors for aircraft and towers. J. Atmos. Ocean. Technol. 15, 416-429.
Mc Millen, R.T., 1988. An Eddy correlation technique with extended applicability to non-simple terrain. Boundary-Layer Meteorol. 43, 231-245.
Vickers D, Mahrt L. 2006. A solution for flux contamination by mesoscale motions with very weak turbulence. Boundary-Layer Meteorol. 118: 431–447. https://doi.org/10.1007/s10546-005-9003-y.
Zahn, E., Chor, T.L., Dias, N. L., 2016. A Simple Methodology for Quality Control of Micrometeorological Datasets. American Journal of Environmental Engineering 6(4A): 135-142 DOI: 10.5923/s.ajee.201601.20.
Observing earth critical zone processes in the bayelva basin (CZO@Bayelva)
Data represents the average values and the corresponding standard deviation obtained from each plots at different site along the transect CCT-airport. Each average value is obtained as a mean over a set of more than 20 point measures for each plot and each sampling date. Flux data are complemented by measurements of soil temperature and volumetric water content. data obtain using accumulation chamber and portable probe.
The Climate Change Tower Integrated Project (CCT-IP) represents the guide lines of the italian research in the arctic and aims to study the interaction between all the components of the climate system in the Arctic. The Amundsen-Nobile Climate Change Tower (CCT) is the key infrastructure of the project, and provides continuous acquisition of the atmospheric parameters at different heights as well as at the interface between the surface and the atmosphere.
The sensor used to measure the radiation budget and energy fluxes is a CNR1 net radiometer at 33 m of height and a CM11 and a CG4 at 25 m to measure the upwelling radiation from the surface.
30 minutes average (μ) and standard deviation (σ) of radiation data as well as products such as total net radiation average and shortwave albedo are available for the download.
Data at resolution of 1 minute are available for online visualization and downloadable under request.
The automated nivological station was installed in November 2020 in a flat area over the tundra about 80 meters far from the Gruvebadet Atmospheric Laboratory and nearby a snow sampling site from where weekly snow samples are collected for chemical analysis. Sensors have been calibrated by their companies before installation and are connected to a datalogger for continuous acquisition. For all the parameters, data are logged with 10-minute time resolution and then averaged over 1 hour. This activity is carried out by the Aldo Pontremoli Centre part of the Joint Research Agreement ENI-CNR.