Abstract
Abstract. 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 (https://doi.org/10.1594/PANGAEA.880120, https://zenodo.org/record/1139714) and HRSC-AX data products (https://doi.org/10.1594/PANGAEA.884730, https://zenodo.org/record/1145373).
Highlights
Permafrost, which is defined as ground that has remained frozen continuously for 2 years or more, covers large parts of the land surface in the Northern Hemisphere, amounting to about 15 million km2 (Brown et al, 1998)
The seasonal snow cover in Arctic permafrost regions insulates the permafrost surface for many months of the year and has an important effect on the thermal regime of permafrost (Langer et al, 2013; López-Moreno et al, 2016)
The soil’s water content determines its hydrologic and thermal properties, and the amount of latent heat that is either required for the seasonal thaw in spring or produced during fall. In view of these dependencies, the data sets, ideally at the same resolution as any meteorological input data, will be of great value for evaluating permafrost models
Summary
Permafrost, which is defined as ground that has remained frozen continuously for 2 years or more, covers large parts of the land surface in the Northern Hemisphere, amounting to about 15 million km (Brown et al, 1998). The soil’s water content determines its hydrologic and thermal properties, and the amount of latent heat that is either required for the seasonal thaw in spring or produced during fall In view of these dependencies, the data sets (including snow cover and the thermal state of the soil and permafrost), ideally at the same resolution as any meteorological input data, will be of great value for evaluating permafrost models (or land surface models intended for permafrost regions). A permafrost maximum, minimum and average temperature with depth (trumpet curve) was shown for data for 1 year (August 2009–August 2010) by Boike et al (2012) The data from this Bayelva site have been used in earth system modeling (Ekici et al, 2014, 2015). The average total phytomass in this subzone is lower than 3 t ha−1 and the net annual production is lower than 0.3 t ha−1
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