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.
The data set comprises a collection of 5 digital terrains models (DTMs) showing the sea ice surface topography for ponded first year ice during the 2012 July–August ICE12/ACCESS cruise north of Svalbard onboard R/V “Lance” in the southwestern Nansen Basin (82.3◦ N, 21.5◦ E). ICE12 drift north of Svalbard in July-August 2015. ICE12 featured an eight-day ice station, 26 July to 3 August 2012, in an area of very close, 9/10 concentration, drift ice. The ice floe that “Lance” was moored to during the drift had a diameter of approximately 600 m and a modal ice thickness of 0.8 m. The surface topography for 5 segments of ICE12 floe is derived using photogrammetry from the series of images acquired by ICE camera setup during survey flights on 28.07.2012 and 31.07.12. Data are presented on a regular 2 cm mesh in UTM coordinates and covers the areas from 11000 to 14000 m2 per segment . As an output formats the ascii XYZ table is used.
The dataset provides supplementary materials (Table 3) for the following publication: Fors, A.S., Divine, D.V., Doulgeris, A.P., Renner, A.H.H., and Gerland, S.: “Signature of Arctic first-year ice melt pond fraction in X-band SAR imagery”, The Cryosphere, doi:10.5194/tc-2016-125
Quality
For more detailes on the dataset and methods used please see Divine, D.V., Pedersen, C. A., Karlsen, T. I., Granskog, M. A., Aas, H.F., Hudson, S. R., and Gerland, S., 2016: “Photogrammetric retrieval and analysis of small scale sea ice topography during summer melt”, Cold Regions Science and Technology, 129 , 77–84, 10.1016/j.coldregions.2016.06.006.
The data associated with this entry have been obtained while working on a drift ice station occupied from 26 July to 3 August 2012 and initially situated at 82.5° N, 21° E north of Svalbard during the Centre for Ice, Climate and Ecosystem (ICE) cruise (22 July - 07 August 2012). The data set includes the following variables: chlrophyll a, particulate organic carbon and nitrogen, biomass estimates of ice algal aggregates, and species composition of ice algal aggregates. The main scientific findings are summarized below.
During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year.
The data set presents regional scale ( about 150 km) morphological properties of a relatively thin, 70–90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The data comprises fractions of three surface types (bare ice, melt ponds, and open water) along the flight tracks calculated from images acquired by a helicopter-borne camera system during ice-survey flights.The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3 N, from 26 July to 3 August 2012. The data set is based on >10 000 classified images covering about 28 km2 in the study area.
The data are presented as .mat (Matlab) files with structure arrays containg the relative fractions of three main surface types: bare ice, melt ponds, and open water derived for 6 flights during the peirod of the drift experiment. Details on the flights are found in Table 1 in the original publication. In addition to the surface properties, the mat files contain the image central coordinates and the area covered are provided.
Quality
Details on the setup and methods used are provided in the original publication: Divine, D. V., Granskog, M. A., Hudson, S. R., Pedersen, C. A., Karlsen, T. I., Divina, S. A., Renner, A. H. H., and Gerland, S.: Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer, The Cryosphere, 9, 255-268, doi:10.5194/tc-9-255-2015, 2015.
Kinematic GPS measurements provide in-situ data crucial for measuring the surface elevation change of glaciers. Owing to their accuracy, which is generally better than half meter, surface elevations derived from kinematic GPS surveys are useful and essential for generating precise digital elevation models (DEMs) and evaluating geometry changes of glaciers. We present a surface elevation data set derived from kinematic GPS measurements covering the lower 5 km of Qaanaaq and Bowdoin Glaciers in northwestern Greenland. The data includes elevations over ice-free terrain nearby the glaciers, important for calibrating remote sensing data. More than 600,000 GPS survey data points were processed to produce a 1-m resolution mesh grid of elevation data in a CSV file format. Based on our error analysis, the accuracies of the elevation data are better than 0.2 and 0.3 m in horizontal and vertical directions, respectively. This dataset can be utilized to investigate glacier surface elevation changes by comparing it making comparison with DEMs that may be obtained in the past, and from future from remote sensing and in-situ observations.
Institutions: GB05L, ACRG, University of Bristol, School of Chemistry, Cantocks Close, BS8 1TS, Bristol, United Kingdom, UNIVBRIS, Cantocks Close,, BS8 1TS, Bristol, United Kingdom, GB05L, ACRG, University of Bristol, School of Chemistry, Cantocks Close, BS8 1TS, Bristol, United Kingdom, UNIVBRIS, Cantocks Close,, BS8 1TS, Bristol, United Kingdom
Last metadata update: 2021-02-11T00:00:00Z
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Abstract:
Ground based in situ observations of online_crds at Tacolneston (GB0057R). These measurements are gathered as a part of the following projects GAW-WDCGG-node, UK_DECC and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), methane in air (mass_fraction_of_methane_in_air)
License : GAW-WDCGG-node: , UK_DECC: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy).
Institutions: GB05L, ACRG, University of Bristol, School of Chemistry, Cantocks Close, BS8 1TS, Bristol, United Kingdom, UNIVBRIS, Cantocks Close,, BS8 1TS, Bristol, United Kingdom, GB05L, ACRG, University of Bristol, School of Chemistry, Cantocks Close, BS8 1TS, Bristol, United Kingdom, UNIVBRIS, Cantocks Close,, BS8 1TS, Bristol, United Kingdom
Last metadata update: 2021-02-11T00:00:00Z
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Abstract:
Ground based in situ observations of online_crds at Tacolneston (GB0057R). These measurements are gathered as a part of the following projects GAW-WDCGG-node, UK_DECC and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: carbon_dioxide in air (mass_fraction_of_carbon_dioxide_in_air), methane in air (mass_fraction_of_methane_in_air)
License : GAW-WDCGG-node: , UK_DECC: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy).
Institutions: GB05L, ACRG, University of Bristol, School of Chemistry, Cantocks Close, BS8 1TS, Bristol, United Kingdom, UNIVBRIS, Cantocks Close,, BS8 1TS, Bristol, United Kingdom, GB05L, ACRG, University of Bristol, School of Chemistry, Cantocks Close, BS8 1TS, Bristol, United Kingdom, UNIVBRIS, Cantocks Close,, BS8 1TS, Bristol, United Kingdom
Last metadata update: 2021-02-11T00:00:00Z
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Abstract:
Ground based in situ observations of online_gc at Tacolneston (GB0057R). These measurements are gathered as a part of the following projects GAW-WDCGG-node, UK_DECC and they are stored in the EBAS database (http://ebas.nilu.no/). Parameters measured are: dinitrogen_monoxide in air (mass_fraction_of_dinitrogen_monoxide_in_air), hydrogen in air (mass_fraction_of_molecular_hydrogen_in_air), sulfur_hexafluoride in air (mass_fraction_of_sulfur_hexafluoride_in_air)
License : GAW-WDCGG-node: , UK_DECC: Public open access. We encourage contacting data originators if substatial use of individual time series is planned (fair use data policy).