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, 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: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Thickness Change (from geodetic method) from observation series of RECIO glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Thickness Change (from geodetic method) from observation series of UNNAMED 17547 glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Thickness Change (from geodetic method) from observation series of UNNAMED 13028 glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Thickness Change (from geodetic method) from observation series of SHOKALSKIY (TIEN SHAN) glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
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.
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.
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre, Natural Environment Research Council
Last metadata update: 2020-01-29T00:00:00Z
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Abstract:
Seventy-nine Antarctic ice core snow accumulation records were gathered as part of a community led project coordinated by the PAGES Antarctica 2k working group. Individual ice core records (kg m2 yr-1) were normalised relative to a reference period (1960-1990). The normalised records were separated into seven geographical regions and averaged together to form the regional composites. The seven geographical regions are: East Antarctica; Wilkes Land Coast; Weddell Sea Coast; Antarctic Peninsula; West Antarctic Ice Sheet; Victoria Land; and Dronning Maud Land. Full data description and methods can be found in Thomas et al., 2017.
This record also includes the original data, from which the composite records were produced.
Due to erroneous data contained in the files, this dataset has been superseded by a corrected version. Please use that corrected dataset in preference to this one to avoid the problem. The DOI for the updated data is: 10.5285/cc1d42de-dfe6-40aa-a1a6-d45cb2fc8293
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2019-04-29T00:00:00Z
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Abstract:
A dataset of acclimation potential of terrestrial, freshwater and marine ectotherms across latitudes collected from the literature spanning the time period 1960 to 2015 with the aim to test the importance of physiological acclimation as a mechanism to buffer species against climate warming.
The projected rate of environmental warming is used to calculate how many years and generations acclimation capacity will afford each species before it will exceed its thermal maximum. Acclimation capacity, generation time, latitudinal range extent and projected rate of warming are then combined into an index of vulnerability. This data together with critical thermal maxima of the ectotherms are presented here.
Institutions: British Antarctic Survey, British Antarctic Survey, NERC EDS UK Polar Data Centre
Last metadata update: 2021-10-20T00:00:00Z
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Abstract:
This dataset contains occurrence records and associated metadata for the zooplankton species Calanus finmarchicus that were compiled from multiple open access databases. A file containing the corresponding background points is provided, along with gridded environmental variables for each season (Jan-Feb-Mar, Apr-May-Jun, Jul-Aug-Sep, Oct-Nov-Dec) and era (1955-1984, 1985-2017) that were assessed in this study. Together these data were used as input files for the MaxEnt ecological niche model within the peer reviewed article: Freer JJ, Daase, M, Tarling GA, (2021) Modelling the biogeographic boundary shift of Calanus finmarchicus reveals drivers of Arctic Atlantification by subarctic zooplankton, Global Change Biology. Finally, an R Markdown document is provided to enable data users to replicate the model optimisation and prediction steps using the input data files within this repository.
Funding was provided by:
UKRI Natural Environment Research Council (NERC): DIAPOD (NE/P006213/1),
NERC and the German Federal Ministry of Education and Research (BMBF): CHASE (NE/R012687/1),
Norwegian Research Council: Deep Impact project (300333).
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Thickness Change (from geodetic method) from observation series of NO-12145 glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Special Event (e.g. surge, calving, avalanche) from observation series of UNNAMED (4*8ABD41) glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Thickness Change (from geodetic method) from observation series of GHULKIN glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)
Institutions: World Glacier Monitoring Service, University of Zurich
Last metadata update: 2018-07-26T00:00:00Z
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Abstract:
The Mass Balance (from glaciological method) from observation series of CHHOTA SHIGRI glacier is derived from the WGMS Fluctuations of Glaciers (FoG) database (doi:10.5904/wgms-fog-2018-06)