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.
Green Network of Excellence Program - Arctic Climate Change Research Project
Last metadata update: 2015-05-14T00:00:00Z
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Abstract:
Woodbuffalo national Park is suitable for ecological studied on carbon dynamics. There are three main forest types. Jack pine forests dominate on the higher terrace with sandy glaciolacustrine deposit. Black spruce stands locate on lower topograpy or around bog site. Trembling aspen is dominant species on the terrrace with fine-grained silty sediments. We settled automatic meteorological data logging system using satelite phone in June 2014. Additional maintenance for whole-year monitoring has been done in September 2014. We can access semi-real time data check on HP of Cryosalon. A chronosequence of stand replacement fire of black spruce stands was settled in WBNP, and soil characteristics of younger site was surveyed. Profile showed waterlooged soil condition through the year.
Japanese Antarctic Research Expedition, The Japanese-Swedish Antarctic Expedition 2007-2008
Last metadata update: 2022-07-22T00:00:00Z
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Abstract:
This dataset contains the ice thickness data recorded by ground-based radio echo sounding experiment carried out along a traverse route from Dome Fuji, the second highest dome in East Antarctica, to the JASE Meeting point along the ice sheet ridge. The data were recorded in the joint Japanese-Swedish JASE traverse survey by NIPR (the 48th and 49th Japanese Antarctic Research Expedition (JARE48 and JARE49)) and Stockholm University. PIs of the joint survey are Shuji Fujita (NIPR, Japan) and Per Holmlund (Stockholm University, Sweden). JARE used a pulse-modulated VHF radar sounder with a peak transmission power of 1 kW, a center frequency of 179 MHz and a transmitter pulse width of 500 ns. Position of sites is accurate (~20 m) using continuous GPS measurements. Fujita et al. (2011) and Fujita et al. (2012) are the original papers for the data. Later, based on validation by Tsutaki et al. (2021), a correction (+37 m) was applied to all the data. Thickness data with a number "-9999" means that bed echo could not be identified in the A-scope, which means that ice is thicker than our detection limit (from 2900 m to 3500 m depending on locations).
Ecosystem properties (surrogate index for ecosystem functioning) and species inventories for multiple taxa (Vascular plant, soil animal, and soil microbial) were measured in low arctic region along the Hudson Bay in Salluit, Quebec, Canada.
Map compilation from aerial photographs of 1969, 1975 and from result of control point survey implemented by Japanese Antarctic Research Expeditions 1974-1976.The numbered grid lines are 1km intervals of the UTM-grid (Zone 37). Coordinates of the origin of projection (39E, 0S) correspond to 500kmE and 10,000kmN on this grid.
Green Network of Excellence Program - Arctic Climate Change Research Project
Last metadata update: 2015-05-12T00:00:00Z
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Abstract:
High ice production in coastal polynyas over the continental shelves in the Arctic Ocean is responsible for the formation of cold saline water, which contributes to the maintenance of the Arctic Ocean halocline. The accurate detection of coastal polynyas, including an estimate of thin ice thickness, is essential for the estimation of sea ice production. We have developed an algorithm that estimates thin ice thickness using Special Sensor Microwave/Imager (SSM/I) data in the Arctic Ocean. Detection and estimation of sea ice thicknesses of <0.15 m are based on the SSM/I 85 and 37 GHz polarization ratios (PR85 and PR37) through a comparison with sea ice thicknesses estimated from the advanced very high resolution radiometer (AVHRR) data in the three different Arctic coastal polynyas. Thus, for the entire Arctic Ocean, the algorithm can be used for the detection of coastal polynyas and for the estimation of sea ice production through combination with heat-flux calculation. We provide the first circumpolar mapping of sea ice production in coastal polynyas over the entire Arctic Ocean.
Stable isotope data (d18O and dD) and temperature reconstruction from Dome Fuji ice cores, Antarctica for the past 360,000 years. Data from core DF1 are deltaD (Uemura et al., 2004) and delta18O (Watanabe et al., 2003). The data-set is corrected and updated in Uemura et al. (2012). Data from core DF2 includes deltaD and delta18O (Uemura et al., 2012). Temperature estimates are based on combined isotope data from both cores (Uemura et al., 2012). The age scale adopted here is the Dome Fuji Ice Core O2/N2 timescale (DFO-2006) (Kawamura et al., 2007).
Map compilation from aerial photographs of 1969, 1970, 1975 and from result of control point survey implemented by Japanese Antarctic Research Expeditions 1974-1976.The numbered grid lines are 1km intervals of the UTM-grid (Zone 37). Coordinates of the origin of projection (39E, 0S) correspond to 500kmE and 10,000kmN on this grid.
Map compilation from aerial photographs of 1969 and from result of control point survey implemented by Japanese Antarctic Research Expeditions 1974-1976.The numbered grid lines are 1km intervals of the UTM-grid (Zone 37). Coordinates of the origin of projection (39E, 0S) correspond to 500kmE and 10,000kmN on this grid.
Green Network of Excellence Program - Arctic Climate Change Research Project
Last metadata update: 2015-10-20T00:00:00Z
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Abstract:
Our research area is located near Chokurdakh (71N, 148E) in Northeastern Siberia, Russia, about 150 km inland from the Arctic sea coast along the Indigirka River. Carbon and energy fluxes were observed at Kodac station which is situated in a forest-tundra landscape. The observations using 3m flux tower (sensors are installed at 2.55m height) include carbon dioxide, latent heat and sensible heat flux monitorings.
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it.There are two types of data available: (data1: geometrically corrected data) and (data2: raw image data).
Green Network of Excellence Program - Arctic Climate Change Research Project
Last metadata update: 2015-05-14T00:00:00Z
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Abstract:
It is the result of chemical analysis of meltwater of the glacier. The samples were obtained at July 2012. It is composed by the result about Li, Na, NH4, K, Mg, Ca, F, Cl, NO2, Br, NO3, PO4 and SO4.
This dataset contains the ice thickness data recorded in the Dome Fuji region, East Antarctica. The data was recorded by the 59th Japanese Antarctic Research Expedition (JARE59) using a pulse-modulated POL radar sounder with a peak transmission power of 1kW, a center frequency of 179 MHz and a transmitter pulse width of 500, 100 or 60 ns.
Black carbon (BC) aerosol deposited in and onto Arctic snow increases the snow's absorption of sunlight and accelerates snowmelt. Wet removal of BC from the atmosphere plays a key role in determining its abundance in the Arctic atmosphere and in Arctic snow. However, this process is poorly understood, mainly due to the scarcity of relevant measurements. To reveal characteristic features of the wet deposition of BC, we made measurements of mass concentration of BC in snow and rain (C_MBC) with relatively high (16%) accuracy and mass concentration of BC in air (M_BC) at the Barrow Atmospheric Baseline Observatory, Alaska, from July 2013 to August 2017 and analyzed them along with routinely measured meteorological parameters from Barrow. Monthly mean M_BC near the surface and C_MBC were poorly correlated from midwinter to early spring, when C_MBC was close to the annual median while M_BC was at its annual peak. Seasonal variations in the altitude distribution of M_BC may lead to these differences in seasonal variation of M_BC near the surface and C_MBC. About 50% of the annual wet deposition of BC occurred in the three months of summer, associated with high values of total precipitation and BC originating from biomass burning. Size distributions of BC in snow and rain were stable throughout the year, suggesting that the size distribution of BC in the lower troposphere was similarly stable. Calculations by two global models reproduced the observed seasonal variations of C_MBC and showed that BC from biomass burning dominated C_MBC in summer.
The Arctic Challenge for Sustainability II, Arctic Challenge for Sustainability
Last metadata update: 2022-04-13T00:00:00Z
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Abstract:
Time-series data of an automatic weather station (AWS) operated at the SIGMA-B site on the Ice cap of Greenland since July 2012. The AWS measures the meteorological parameters every hour, which are air temperature, relative humidity, wind speed, wind direction, atmospheric pressure, shortwave radiation, longwave radiation, and snow height. This dataset (data level: 1.2) has been applied brief data masking procedures discriminating apparent erroneous data records. Detailed information of the data level definition is referred to "readme_SIGMA-B_Level_1.2.txt".