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.
Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are daily composites of merged sensor (MERIS, MODIS Aqua, SeaWiFS LAC & GAC, VIIRS, OLCI) products. MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007. VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2013; and at the third stage OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30. VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA/s l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.12 (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with polymer. The Rrs were binned to a sinusoidal 1km level-3 grid, and later to 1km geographic projection, by Brockmann Consult/s SNAP. Derived products were generally computed with the standard algorithmsthrough SeaDAS. QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting. The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships. Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated accorsing to Jackson et al. (in prep).
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios.The CMIP5 model selection is based on their ability to reconstruct the present (1971–2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized.
Simulations of the seasonal mass balance and runoff for glaciers in Svalbard from the CryoGrid model. The model is forced by AROME ARCTIC. The spatial resolution is 2.5 x 2.5 km. This dataset contains daily means.
Simulations of the seasonal mass balance and runoff for glaciers in Svalbard from the CryoGrid model. The model is forced by AROME-ARCTIC. The spatial resolution is 2.5 x 2.5 km. This dataset contains monthly means.
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).
Arctic Challenge for Sustainability, The Arctic Challenge for Sustainability II
Last metadata update: 2022-12-15T00:00:00Z
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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).
10-day sea ice forecast was conducted using ocean-ice coupled model IcePOM (e.g., De Silva et al., 2020, Polar Geography) with the aim of supporting the Arctic cruise of R/V Mirai in 2022. For initialization of the model, ocean and ice variables are nudged to RIOPS analysis by ECCC. The forecast simulation is conducted each day using ECMWF 10-day atmospheric forecast for the boundary condition. The 10-day forecast is issued each day from Aug 5, 2022 to Sep 19, 2022.
Institutions: Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2022-04-29T13:30:00Z
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Abstract:
Seismic data recorded by a permanent seismological station located in Spitsbergen. Seismic records can be used for seismological and cryoseismological studies, data is gathered continuously and access is open.
The facility in Adventdalen can determine atmospheric parameters such as winds and turbulence from a few km altitude to over 100km and at a wide variety of spatial and temporal resolutions (which parameters are derived depends on altitude of the measurement).
The Sousy Svalbard Radar (SSR), is a so-called "mesosphere-stratosphere-troposphere" (MST) radar, operates at 53.5 MHz and is located in Adventdalen approximately 10km SW of Longyearbyen. The system is of the phased array type and as such has a low visual impact on the environment. Typical average power is only 200W - and thus a negligible radiation hazard (think of looking at 2 or 3 lightbulbs from several kilometers away). The MST radar is complemented with a meteor detection system extending the set of parameters.