Journal cover Journal topic
Earth System Science Data The Data Publishing Journal

Journal metrics

  • IF value: 8.286 IF 8.286
  • CiteScore<br/> value: 7.07 CiteScore
  • SNIP value: 2.755 SNIP 2.755
  • SJR value: 5.363 SJR 5.363
  • IPP value: 6.509 IPP 6.509
  • h5-index value: 23 h5-index 23
Earth Syst. Sci. Data, 7, 245-259, 2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review article
14 Sep 2015
The new database of the Global Terrestrial Network for Permafrost (GTN-P)
B. K. Biskaborn1, J.-P. Lanckman2, H. Lantuit1,3, K. Elger4, D. A. Streletskiy5, W. L. Cable6, and V. E. Romanovsky6,7 1Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
2Arctic Portal, Akureyri, Iceland
3Institute for Earth and Environmental Sciences, University of Potsdam, Potsdam, Germany
4Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany
5Department of Geography, The George Washington University, Washington, USA
6Geophysical Institute, University of Alaska Fairbanks, Fairbanks, USA
7Earth Cryosphere Institute, Tyumen, Russia
Abstract. The Global Terrestrial Network for Permafrost (GTN-P) provides the first dynamic database associated with the Thermal State of Permafrost (TSP) and the Circumpolar Active Layer Monitoring (CALM) programs, which extensively collect permafrost temperature and active layer thickness (ALT) data from Arctic, Antarctic and mountain permafrost regions. The purpose of GTN-P is to establish an early warning system for the consequences of climate change in permafrost regions and to provide standardized thermal permafrost data to global models. In this paper we introduce the GTN-P database and perform statistical analysis of the GTN-P metadata to identify and quantify the spatial gaps in the site distribution in relation to climate-effective environmental parameters. We describe the concept and structure of the data management system in regard to user operability, data transfer and data policy. We outline data sources and data processing including quality control strategies based on national correspondents. Assessment of the metadata and data quality reveals 63 % metadata completeness at active layer sites and 50 % metadata completeness for boreholes.

Voronoi tessellation analysis on the spatial sample distribution of boreholes and active layer measurement sites quantifies the distribution inhomogeneity and provides a potential method to locate additional permafrost research sites by improving the representativeness of thermal monitoring across areas underlain by permafrost. The depth distribution of the boreholes reveals that 73 % are shallower than 25 m and 27 % are deeper, reaching a maximum of 1 km depth. Comparison of the GTN-P site distribution with permafrost zones, soil organic carbon contents and vegetation types exhibits different local to regional monitoring situations, which are illustrated with maps. Preferential slope orientation at the sites most likely causes a bias in the temperature monitoring and should be taken into account when using the data for global models. The distribution of GTN-P sites within zones of projected temperature change show a high representation of areas with smaller expected temperature rise but a lower number of sites within Arctic areas where climate models project extreme temperature increase.

GTN-P metadata used in this paper are available at doi:10.1594/PANGAEA.842821.

Citation: Biskaborn, B. K., Lanckman, J.-P., Lantuit, H., Elger, K., Streletskiy, D. A., Cable, W. L., and Romanovsky, V. E.: The new database of the Global Terrestrial Network for Permafrost (GTN-P), Earth Syst. Sci. Data, 7, 245-259, doi:10.5194/essd-7-245-2015, 2015.
Short summary
This paper introduces the new database of the Global Terrestrial Network for Permafrost (GTN-P) on permafrost temperature and active layer thickness data. It describes the operability of the Data Management System and the data quality. By applying statistics on GTN-P metadata, we analyze the spatial sample representation of permafrost monitoring sites. Comparison with environmental variables and climate projection data enable identification of potential future research locations.
This paper introduces the new database of the Global Terrestrial Network for Permafrost (GTN-P)...