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.
As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. This dataset contains the CTD, PAR and fluorescence data from Kongsfjorden 2015-2016. Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. No post-recovery processing of light data (to correct for fouling) has been performed. The observatory layout is available in the mooring diagram provided. For this deployment a RAS500 water sampler and a SUNA nitrate sensor were deployed for a specific project, data are not part of the long-term monitoring efforts and are available upon request.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
Green Network of Excellence Program - Arctic Climate Change Research Project
Last metadata update: 2016-02-26T00:00:00Z
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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 2015. We can access semi-real time data check on HP of Cryosalon. We made site description on moss/lichen communities along a chronosequence of stand replacement fire. Additional forest census plot for stand reconstruction analysis using tree ring data were measured.
Arctic Challenge for Sustainability, The Arctic Challenge for Sustainability II
Last metadata update: 2018-12-12T00:00:00Z
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Abstract:
Plant phenology timings, such as spring green-up and autumn senescence, are essential state information characterizing biological responses and terrestrial carbon cycles. Current efforts for the in-situ reflectance measurements are not enough to obtain the exact interpretation of how seasonal spectral signature responds to phenological stages in boreal evergreen needleleaf forests. This data set shows the in situ continuous measurements of spectral reflectance in a boreal forest in interior Alaska. We deployed two field-based spectroradiometer systems in an open black spruce forest. These two spectroradiometer systems were used to obtain canopy scale (overstory + understory) and understory reflectances. The data set includes the overstory and understory incoming and reflected hemispherical spectral irradiance data (Level 1), and spectral reflectance computed by the in- and out-going spectral data (Level 2). Because the reflected hemispherical irradiance contains the reflection from tower structure for overstory measurements. The further reflectance correction was applied for the measurements at the tower top level (Level 3).
Dome Fuji, Antarctica Ice Core DF2 1-cm Electrical Conductivity Measurements (ECM) at -20C for depth range 875 - 2200m.The climatic record from the 2nd Dome Fuji (Antarctica) ice core (DF2 core as 3035m deep ice core) was analyzed using ECM (electrical conductivity measurements). The DF2 core, reaching nearly to the ice sheet bed, was drilled in the period 2004-2007 at a site ~43 m away from the DF1 borehole. Mothod of the ECM measurement is as follows. After equilibrating for 1 day at the cold-room temperature at Dome F, all core sections, which were 93mm in diameter and about 1.5m long, were cut parallel to their central axes. The cut surfaces were further finished with a microtome knife to make fresh, smooth surfaces. Immediately after a surface was cut and finished, two ECM electrodes were dragged along the surface with a 400V d.c. potential difference. Although the signal was sampled every 2mm, we provide only 10mm running averages of the data to remove noise. The ECM electrodes were automatically dragged along the ice with a moter module. The electrodes were aligned perpendicular to the core axis and 15mm apart. The effective resolution of the electrodes approximately equaled the distance between the electrodes (15mm); based on a physical principle that the electrical field decreases inversely proportional to the distance from a given location to each electrode. Within this distance, about 65% of the lines of electrical force cross. Measurement temperature is -20C.In 2015, Fujita, Parrenin et al. (2015) volcanically synchronized two deep ice cores, Dome Fuji (DF) and EPICA Dome C (EDC), drilled at remote dome summits in Antarctica, to improve our understanding of their chronologies. For their study, the ECM data of the DF2 core were used from a limited depth range 875 - 2200m. Here, we open these data to the public. The data have two information of the depth. The first column is the depth of the DF2 core. The third column is the DF2 depths converted into equivalent depths of the DF1 core. The second column is the electrical current between the electrodes. Note that, in this version of the data, no actions for noise cleaning were done. Except the averaging for every 10mm, data is still a kind of raw data.
To clarify the mass and heat balance, snow depositional condition on ice sheet, AWS was installed at H128. The H128 Automatic Weather Station (AWS) Data Graph provides a variety of real-time data, including air temperature, relative humidity, wind speed, wind direction, up and down shortwave radiation, up and down longwave radiation, surface air pressure, snow height, snow temperature, and more. The H128 site is located on coastal Dronning Maud Land, East Antarctica (69.4S, 41.57E, 1380 m a.s.l). This AWS is maintained and operated by JARE/NIPR.
GREen Network of Excellence - Arctic Climate Change Research Project
Last metadata update: 2016-03-15T00:00:00Z
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Abstract:
Number of seawater spray particles on 06 deck of the icebreaker Shirase. Observational periods: from 14 Feb. to 9 Mar, 2015. (return voyage of 56th Japanese Antarctic Research Expedition)
Green Network of Excellence Program - Arctic Climate Change Research Project
Last metadata update: 2016-04-05T00:00:00Z
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Abstract:
This data was measured by an shipborne Electromagnetic induction (EM) sensor which mountaed on the CCGS Louis S. St. Laurent. The observation started from 22 September to 5 October 2015 along the Canada basin from/to Kugluktuk.