Functional outline of the data portal search interface.
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)
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, Danish Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-07-14T09:27:43Z
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Abstract:
A 9 month ice drift data set based on VIS and IR data
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, Danish Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-07-14T09:06:28Z
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Abstract:
A 9 month ice drift data set based on VIS and IR data
International Polar Year, Integrated Arctic Ocean Observing System - Norway, Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies (IPY, iAOOS-Norway, DAMOCLES)
Institutions: Norwegian Polar Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-08-14T15:28:42Z
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Abstract:
Radiation measurements made during the spring 2008 cruise to the Fram Strait. Transmission of light through ice, measured by divers on day 4 of fifth floe. At fourth site, approx. 20 m from ice edge, 0.42 m snow on 1.04 m ice. Each measurement type (incident, reflected, etc) was made with a different TriOS Ramses spectroradiometer. These are known to have calibration issues at the longest and shortest wavelengths for which data are reported; we recommend using only data from about 350 to 920 nm. No significant quality control has been done to these data.
Snow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. The global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. Ref: Nagler, T.; Schwaizer, G.; Mölg, N.; Keuris, L.; Hetzenecker, M.; Metsämäki, S. (2022): ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2020), version 2.0. NERC EDS Centre for Environmental Data Analysis, 23 March 2022. doi:10.5285/8847a05eeda646a29da58b42bdf2a87c. http://dx.doi.org/10.5285/8847a05eeda646a29da58b42bdf2a87c
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, AWI
Last metadata update: 2023-06-29T11:12:39Z
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Abstract:
These CMIP5 model data show interpolated results in Arctic only. Original data
were cut and interpolated for internal use of the EU funded project ACCESS.
Institutions: NORCE Tromsø, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-05T13:18:30Z
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Abstract:
Sentinel-1 Wet snow product: The warming climate on Svalbard impacts the amounts of wet snow significantly. Sentinel-1 is sensitive to wet snow as compared with dry snow or bare soil, and the current dataset provides up to daily maps over Svalbard of the spatial distribution of wet snow. The maps are derived from three SAR instriments (Envisat ASAR 2004-2012, Radarsat-2 2012-2014, and Sentinel-1 A/B from 2014-2020). Grid cells are classified with codes where 20=water, 30=nodata, 100=bare ground, 200=dry snow, 205=wetsnow
Institutions: Norwegian Computing Center, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-24T19:38:41Z
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Abstract:
The CryoClim FSC product provides daily information on fractional snow cover(0-100 %) per grid cell for global land areas except permanent snow and iceareas with 5 km grid size. The product is based on multi-sensor/time-series fusion of AVHRR, SMMR, SSM/I and SSMIS data eliminating cloud cover and polar night, resulting in a temporally consistent snow map.
Institutions: Norwegian Computing Center, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-24T23:12:54Z
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Abstract:
The CryoClim FSC product provides daily information on fractional snow cover(0-100 %) per grid cell for global land areas except permanent snow and iceareas with 5 km grid size. The product is based on multi-sensor/time-series fusion of AVHRR, SMMR, SSM/I and SSMIS data eliminating cloud cover and polar night, resulting in a temporally consistent snow map.
Automatic weather station (AWS) on Etonbreen glacier, an outlet from the Austfonna ice cap in North-East Svalbard. The AWS is located at approx 360 m a.s.l. near the long term equilibrium line altitude. The AWS records variables needed for an energy balance assessment. The AWS records Air Temperature, Relative Humidity, Wind Direction and Speed, Air Pressure, Snow Height, Longwave and Shortwave radiations. Data are transferred by Iridium. The extended AWS is the same type of station with heated and ventilated radiation in addition.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99927. Data are climate consistent following a number of automated and manual quality control routines.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute
Last metadata update: 2023-10-26T11:47:12Z
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Abstract:
Quality controlled timeseries from Norwegian weather station 0-578-0-99710. Data are climate consistent following a number of automated and manual quality control routines.
SPUB Hornsund, RIS-ID: 11029 LONG-TERM OCEANOGRAPHIC MONITORING IN HORNSUND REGION
Institutions: Institute of Geophysics, Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2021-11-10T08:53:37Z
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Abstract:
A set of inter calibrated temperature in-depth profiles in Hornsund Fjord.We used all of our CTD sensors (Valeport: 1 CTD; RBR: 3 CTD, 2TD, 6 T; SeaBird 1CT; SAIV A/S: 1 CTD), at the same time in a stable position at stable depths for 24 hours measurement. SAIV A/S conductivity data was different from the rest. Because for CTD in-depth profile Valeport and SAIV A/S were used we made comparable CTD in-depths profiles for these two CTD sensors. Based on comparison plots for temperature and conductivity from the same depths for all comparable in-depth profiles for these two sensors we add linear correction for temperature and conductivity data from SAIV A/S. After losing SAIV A/S sensor we made the same procedure for the new. Depth (UNESCO Technical Papers in Marine Science No. 44), salinity (UNESCO 1983), density (Millero and Poisson 1981, UNESCO 1981) were calculated based on a commonly used formula from pressure, temperature, and conductivity after data inter-calibration.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available satellite data and insitu observations and provides a gridded map. It is a continuation of the previous sea ice chart which basically identified the ice edge.
Institutions: Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T15:00:52Z
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Abstract:
The product is based on a manual interpolation of available insitu observations. This dataset is the predecessor of the gridded ice charts based on satellite data and other sources. This dataset primarily identifies the sea ice edge.