Kooperativer Bibliotheksverbund

Berlin Brandenburg

and
and

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Language: English
    In: Earth System Science Data, 2018, Vol.10(1), pp.355-390
    Description: Most permafrost is located in the Arctic, where frozen organic carbon makes it an important component of the global climate system. Despite the fact that the Arctic climate changes more rapidly than the rest of the globe, observational data density in the region is low. Permafrost thaw and carbon release to the atmosphere are a positive feedback mechanism that can exacerbate global warming. This positive feedback functions via changing land–atmosphere energy and mass exchanges. There is thus a great need to understand links between the energy balance, which can vary rapidly over hourly to annual timescales, and permafrost, which changes slowly over long time periods. This understanding thus mandates long-term observational data sets. Such a data set is available from the Bayelva site at Ny-Ålesund, Svalbard, where meteorology, energy balance components and subsurface observations have been made for the last 20 years. Additional data include a high-resolution digital elevation model (DEM) that can be used together with the snow physical information for snowpack modeling and a panchromatic image. This paper presents the data set produced so far, explains instrumentation, calibration, processing and data quality control, as well as the sources for various resulting data sets. The resulting data set is unique in the Arctic and serves as a baseline for future studies. The mean permafrost temperature is −2.8 °C, with a zero-amplitude depth at 5.5 m (2009-2017). Since the data provide observations of temporally variable parameters that mitigate energy fluxes between permafrost and atmosphere, such as snow depth and soil moisture content, they are suitable for use in integrating, calibrating and testing permafrost as a component in earth system models.The presented data are available in the Supplement for this paper (time series) and through the PANGAEA and Zenodo data portals: time series (〈a href="https://doi.org/10.1594/PANGAEA.880120" target="_blank"〉https://doi.org/10.1594/PANGAEA.880120〈/a〉, 〈a href="https://zenodo.org/record/1139714" target="_blank"〉https://zenodo.org/record/1139714〈/a〉) and HRSC-AX data products (〈a href="https://doi.org/10.1594/PANGAEA.884730" target="_blank"〉https://doi.org/10.1594/PANGAEA.884730〈/a〉, 〈a href="https://zenodo.org/record/1145373" target="_blank"〉https://zenodo.org/record/1145373〈/a〉).
    Keywords: Geology;
    ISSN: Earth System Science Data
    ISSN: 18663508
    E-ISSN: 1866-3516
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages