Measurements in soil and air at Bayelva Station

• Main Authors: Boike, Julia, Juszak, Inge, Lange, Stephan, Chadburn, Sarah, Burke, Eleanor, Overduin, Pier Paul, Roth, Kurt, Ippisch, Olaf, Bornemann, Niko, Stern, Lielle, Gouttevin, Isabelle, Hauber, Ernst, Westermann, Sebastian
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2018
• Subjects: Bayelva; Svalbard; time series; permafrost; Ny Ålesund; Ny-Ålesund
• Online Access: https://doi.org/10.1594/PANGAEA.880120

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 climate 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 time scales, 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 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 a baseline for future studies. 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 data set also includes a high resolution digital elevation model that can be used together with the snow physical information for snow pack modeling. Further years will be updated on https://doi.pangaea.de/10.1594/PANGAEA.880120