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.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
The file contains time series of meteorological near-surface parameters measured on a temporary meteorological mast on the southern side of the coast of Adventdalen, Svalbard, from July to August 2022: Both temperature, humidity, wind speed, wind direction were measured at two levels.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, University of Bergen, University of Bergen, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
A scanning Doppler Lidar was placed in Adventdalen (Central Spitsbergen, Svalbard, Norway) close to the permanent weather mast SN99870. The Lidar measured between 4 July and 23 August 2022 with different scanning patterns in an hourly cycle. The cycle consisted of three Plan Position Indicator (PPI) scans at 1, 5 and 10 degree from xx:00 to xx:10, Range Height Indicator (RHI) scans alternating between up-valley and down-valley direction from xx:10 to xx:50, Doppler-Beam-Swinging (DBS) technique from xx:50 to xy:00. The radial resolution was 10 m with overlapping range gates of 50 m. Short periods of power cuts were encountered. Frequently there were conditions with little backscatter and low carrier-to-noise ratio, especially in light down-valley winds.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre (NO/MET/ADC)
The Isfjorden Weather Information Network provides standard meteorological near-surface measurements from the Isfjorden region in Svalbard. The network includes weather stations permanently installed on lighthouses around the fjord and onboard small tourist cruise ships trafficking the fjord from the spring to the autumn. Data is available since August 2021 and new observations become available here in near real-time.
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, SU Stockholm University, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
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Abstract:
Arctic Ocean Experiment 2001 AOE-2001 was an icebreaker based field experiment
with a target on the formation of low clouds in the central Arctic summer during
July and August 2001. A main portion of the 2-moth experiment was a 3-week ice
drift from 89 to 88 degN. Main components of the meteorology part of the
experiment were surface-based remote- sensing observations, general meteorology
observations (weather staion and soundings) and boundary-layer observations on
the ice. For a complete review of the experiment and a full list of instruments,
see Tjernström et al. 2004 ("The summertime Arctic atmosphere: Meteorological
measurements during the Arctic Ocean Experiment (AOE-2001)" in Bulletin of the
American Meteorological Society, 85, 1305 - 1321, and its on-line supplement
"Experimental equipment: A supplement to The summertime Arctic atmosphere:
Meteorological measurements during the Arctic Ocean Experiment (AOE-2001)").
Observations included in the dataset:
Observations from 2D-wind sonic anemometer on the mast of Oden during AOE-2001. Beware of flow distortion from the ship.
One-hour averaged cloud base observations from cloud base lidar and cloud radar during AOE-2001
Instant cloud-top observations from S-band cloud radar operating in two modes, a low-range high-resolution and a high-range low-resolution mode, respectively, obtained during AOE-2001. The presented data is the highest cloud top altitude observed.
Various meteorological observations from a mast placed on an ice-floe during AOE-2001
Turbulence statistics from sonic anemometer at 15 meters on the mast averaged over 15 minute obtained during AOE-2001
Turbulence statistics from sonic anemometer at 5 meters on the mast averaged over 15 minute obtained during AOE-2001
Various meteorological observations from Odens weather station situated at 35 metres ASL during AOE-2001. Winds may be subject to considerable flow distortion. Precipitation is in arbitrary units.
One-hour averaged precipitation from present-weather-sensor, which measures no. of precip particles falling past the sensor, during AOE-2001
Wind profile data from 915 MHz profiler on foredeck of Oden obtained during AOE-2001
Atmospheric baloon sounding data obtained during AOE-2001. The observations are interpolated to a fixed grid for plotting purposes.
Measurements from the high range of the S-band cloud radar obtained during AOE-2001. The variables presented are radar reflectivity and hydro-meteor fall velocity.
Measurements from the low range of the S-band cloud radar obtained during AOE-2001. The variables presented are radar reflectivity and hydro-meteor fall velocity.
Temperature profiles measured by a scanning radiometer obtained during AOE-2001.
Measurements from the sodar obtained during AOE-2001. Note that the altitude for each record varies in time.
Observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Observations 5 metres AGL from mobile ISSF PAM station 2 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Observations 5 metres AGL from mobile ISSF PAM station 3 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
One-hour averaged visibility observations from back-scatter sensor during AOE-2001.
Snow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. The global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. Ref: Nagler, T.; Schwaizer, G.; Mölg, N.; Keuris, L.; Hetzenecker, M.; Metsämäki, S. (2022): ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2020), version 2.0. NERC EDS Centre for Environmental Data Analysis, 23 March 2022. doi:10.5285/8847a05eeda646a29da58b42bdf2a87c. http://dx.doi.org/10.5285/8847a05eeda646a29da58b42bdf2a87c
Institutions: NORCE Tromsø, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-05T13:18:30Z
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Abstract:
Sentinel-1 Wet snow product: The warming climate on Svalbard impacts the amounts of wet snow significantly. Sentinel-1 is sensitive to wet snow as compared with dry snow or bare soil, and the current dataset provides up to daily maps over Svalbard of the spatial distribution of wet snow. The maps are derived from three SAR instriments (Envisat ASAR 2004-2012, Radarsat-2 2012-2014, and Sentinel-1 A/B from 2014-2020). Grid cells are classified with codes where 20=water, 30=nodata, 100=bare ground, 200=dry snow, 205=wetsnow
Institutions: Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T13:56:05Z
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Abstract:
The climate in Svalbard has been warming dramatically compared with the global average for the last few decades. Seasonal snow cover, which is sensitive to temperature and precipitation changes, is therefore expected to undergo both spatial and temporal changes in response to the changing climate in Svalbard. This dataset contains a daily snow cover fraction maps for the Svalbard archipelago, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra data.
Time series from March 19th 2012 of solar radiation and photosynthetic active radiation (PAR)
from data loggers located at the roof of the University Centre in Svalbard (UNIS) in Longyearbyen, Norway. Location 78o13’21’’N/15o39’9’’E,
20 m above sea level. Measurements were recorded every 10 minutes
Institutions: NILU, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-16T12:14:40Z
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Abstract:
Remote-sensing observations performed using the Differential Optical Absorption Spectroscopy (DOAS) technique to quantify the abundance of NO2. The dataset ranges from 2020-03-13T09:22:02 to 2021-10-02T13:57:40, and contains the variables altitude_instrument, angle_solar_azimuth, angle_solar_zenith_astronomical, latitude, longitude, no2_column_absorption_solar, no2_column_absorption_solar_amf, no2_column_absorption_solar_flag, no2_column_absorption_solar_uncertainty_combined_standard, no2_column_absorption_solar_uncertainty_mixed_standard, no2_column_absorption_solar_uncertainty_random_standard, no2_column_absorption_solar_uncertainty_systematic_standard, temperature_effective_no2, temperature_effective_no2_uncertainty_combined_standard, temperature_effective_no2_uncertainty_mixed_standard, temperature_effective_no2_uncertainty_random_standard and temperature_effective_no2_uncertainty_systematic_standard. The datset is provided by Ann Mari Fjaeraa,NILU.
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.
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.
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
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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