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Earth System Dynamics An interactive open-access journal of the European Geosciences Union

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Earth Syst. Dynam., 4, 187-198, 2013
https://doi.org/10.5194/esd-4-187-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
11 Jul 2013
A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams
F. Cresto Aleina1,2, V. Brovkin2, S. Muster3, J. Boike3, L. Kutzbach4, T. Sachs5, and S. Zuyev6 1International Max Planck Research School for Earth System Modelling, Hamburg, Germany
2Max Planck Institute for Meteorology, Hamburg, Germany
3Alfred Wegener Institute for Polar and Marine Research, Research Unit Potsdam, Potsdam, Germany
4Institute of Soil Science, Klima-Kampus, University of Hamburg, Hamburg, Germany
5Deutsches GeoForschungsZentrum, Helmholtz-Zentrum, Potsdam, Germany
6Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
Abstract. Subgrid processes occur in various ecosystems and landscapes but, because of their small scale, they are not represented or poorly parameterized in climate models. These local heterogeneities are often important or even fundamental for energy and carbon balances. This is especially true for northern peatlands and in particular for the polygonal tundra, where methane emissions are strongly influenced by spatial soil heterogeneities. We present a stochastic model for the surface topography of polygonal tundra using Poisson–Voronoi diagrams and we compare the results with available recent field studies. We analyze seasonal dynamics of water table variations and the landscape response under different scenarios of precipitation income. We upscale methane fluxes by using a simple idealized model for methane emission. Hydraulic interconnectivities and large-scale drainage may also be investigated through percolation properties and thresholds in the Voronoi graph. The model captures the main statistical characteristics of the landscape topography, such as polygon area and surface properties as well as the water balance. This approach enables us to statistically relate large-scale properties of the system to the main small-scale processes within the single polygons.

Citation: Cresto Aleina, F., Brovkin, V., Muster, S., Boike, J., Kutzbach, L., Sachs, T., and Zuyev, S.: A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams, Earth Syst. Dynam., 4, 187-198, https://doi.org/10.5194/esd-4-187-2013, 2013.
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