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 by changing the operators used in the text field and prefixing words with '+' and '-' to indicate whether they have to be present or should not be present 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.
Citation of data and service
If you use data retrieved through this portal, please acknowledge the efforts of the data portal and the data centres contributing.
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
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)
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from HAY RIVER A, NWT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from FORT SMITH A, NWT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from INUVIK AWOS A, NWT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from FORT SIMPSON A, NWT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from FARO (AUT), YT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from DAWSON, YT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from CAPE PARRY A, NWT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
WMO Year of Polar Prediction, Svalbard Integrated Arctic Earth Observing System (YOPP, APPLICATE, SIOS)
Institutions: Norwegian Meteorological Institute
Last metadata update: 2022-11-15T14:48:52Z
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Abstract:
Synoptic meteorological measurements from SHINGLE POINT A, YT
extracted from the WMO Global Telecommunication System (GTS).
Data are not quality controlled after extraction from GTS.
These data have been collected from an Arctic desert site (latitude 78o57'29N, longitude 12o27'42E), Broeggerhalvoya in western Spitsbergen, 10 km NW from Ny Alesund, 45 m above sea level, 2 km from the shore. This is a low relief tip of a bedrock peninsula covered with several meters of glacial drift and reworked raised beach ridges. The measurements are obtained in the site of well developed patterned ground, sorted polygons, where the influence of plants, including thermal insulation and transpiration, is negligible. The 1985-1986 period was average. Mean annual air temperature was -6.6 C, 0.4 C colder than the long-term (1975-1990) mean, but well within the mean variability. Mean winter air temperature is relatively warm (mean of coldest month, February, is -14.6 C). Annual precipitation was 17 % greater than the ong-term mean (372 mm); however, the number of rain-on-snow events was less (3) than average (5.5). Overall, the reference period is close to long-term averages.
A program of automated soil temperature recordings was initiated in the summer of 1984, at a patterned ground field site Thermistors were placed approximately 0.1 m apart in an epoxy-filled PVC rod (18 mm outside diameter), buried in the center of a fine-grained domain of a sorted circle, down to 1.14 m below the ground surface. The data presented here covers 7/1/85-7/1/86, once a day (6 am), at two levels (0.0 m, 1.145 m below surface). The resolution of the thermistors is 0.004 C, and the accuracy is estimated to be 0.02 C near 0 C. Missing data accounts for less than 7 %. The gaps are filled with simple average of the beginning and end of the gap values. For a detailed description of the field site and data analysis see Putkonen (1997) and Hallet and Prestrud (1986). These data are presented on the CAPS Version 1.0 CD-ROM, June 1998.
Geomorphological mapping was used to prepare a morphodynamic map of Wedel Jarlsberg Land, Svalbard. Zones, profiles, and sites for detailed measurements were selected to determine slope processes in qualitative and quantitative terms. Indices of relief degradation were determined using quantitative data characterizing the intensity of present-day morphogenetic processes and postglacial palaeogeographic information. Data were collected during summer seasons only.
Snow and soil temperature records for January 1988 - May 1996 are presented. Included are snow depth and weight measurements, snow density (calculated), active layer depth in the frost tubes, weight of wet and dried soil samples from unknown depth within the active layer (water content calculated), and soil temperature at the surface (0.05 cm) and to the depths of 3 to 4 meters at 3 sites. The sites are 1) on a road covered by 1 m of gravel underlain by clay; 2) outside a building on piles, (sensors are placed 1 to 2 m from the building wall); and 3) under the building between piles. In addition, air temperature was measured inside the building or between the piles (documentation is not clear on this point.) There are several gaps in temperature measurements (January 1991 to May 1992). These data are presented on the CAPS CD-ROM version 1.0, June 1998.
Air temperature, wind direction, and temperature were measured at 5, 20, 50, 100, 150, and 200 cm below the tundra surface at an undisturbed site; and at 5, 20, 50, 100, 150, 200 cm, and 3 m and 8 m below the concrete surface of a building. Incoming radiation, outgoing radiation, temperature of the heat flux instrument, global radiation, heat flux, wind speed, wind speed maximum, average wind speed, and temperature inside the building were measured since 1993 with data loggers. All data are recorded for July 1987 - February 1996.
This data set consists of Upward Looking Sonar (ULS) data from 11 moorings in the Greenland Sea. Parameters in the processed data files include ice draft, water pressure, and water temperature. Raw data files with sonar travel time, and files with draft frequency of occurrence, are available as well. A single statistical file for each mooring summarizes that mooring's record. These data were contributed by the Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany, in 2002 and 2004, as a contribution to the World Climate Research Programme's Arctic Climate System Study/Climate and Cryosphere (ACSYS/CliC) Project. Data are available via FTP.
NSIDC strongly encourages you to register as a user of this data product. As a registered user, you will be notified of updates and corrections. When registering, please include the title of this data set, AWI Moored ULS Data, Greenland Sea and Fram Strait, 1991-2002.
Institutions: British Antarctic Survey, British Antarctic Survey, UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation
Last metadata update: 2020-06-04T00:00:00Z
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Abstract:
This dataset consists of a bed DEM and four velocity maps of Kongsvegen, a surge-type glacier in Svalbard. The bed DEM was generated from ground-penetrating radar surveys in spring 2016 and 2018, and the velocity maps span the period Dec 2017 to Feb 2019. The velocity maps show the initial speed-up of the glacier as it transitions from quiescence to surge.
Data acquisition was funded by NERC Urgency Grant NE/R018243/1 REBUS (Resolving Enthalpy Budget to Understand Surges).
This dataset includes ground temperature data from coarse morainal (till) soil in a tundra area, on a 2-degree slope with rapid drainage, 45 m asl, at an undisturbed site with about 10 percent vegetation cover. A data logger was used with a sampling rate of 60 days; 1-day averaging period of individual measurements.