A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2013-07-01
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| Series: | Earth System Dynamics |
| Online Access: | http://www.earth-syst-dynam.net/4/187/2013/esd-4-187-2013.pdf |
| _version_ | 1819264318869340160 |
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| author | F. Cresto Aleina V. Brovkin S. Muster J. Boike L. Kutzbach T. Sachs S. Zuyev |
| author_facet | F. Cresto Aleina V. Brovkin S. Muster J. Boike L. Kutzbach T. Sachs S. Zuyev |
| author_sort | F. Cresto Aleina |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-23T20:27:35Z |
| format | Article |
| id | doaj.art-972eecb429254773b7065dd04b9cf835 |
| institution | Directory Open Access Journal |
| issn | 2190-4979 2190-4987 |
| language | English |
| last_indexed | 2024-12-23T20:27:35Z |
| publishDate | 2013-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Dynamics |
| spelling | doaj.art-972eecb429254773b7065dd04b9cf8352022-12-21T17:32:20ZengCopernicus PublicationsEarth System Dynamics2190-49792190-49872013-07-014218719810.5194/esd-4-187-2013A stochastic model for the polygonal tundra based on Poisson–Voronoi diagramsF. Cresto Aleina0V. Brovkin1S. Muster2J. Boike3L. Kutzbach4T. Sachs5S. Zuyev6International Max Planck Research School for Earth System Modelling, Hamburg, GermanyMax Planck Institute for Meteorology, Hamburg, GermanyAlfred Wegener Institute for Polar and Marine Research, Research Unit Potsdam, Potsdam, GermanyAlfred Wegener Institute for Polar and Marine Research, Research Unit Potsdam, Potsdam, GermanyInstitute of Soil Science, Klima-Kampus, University of Hamburg, Hamburg, GermanyDeutsches GeoForschungsZentrum, Helmholtz-Zentrum, Potsdam, GermanyDepartment of Mathematical Sciences, Chalmers University of Technology, Gothenburg, SwedenSubgrid 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.http://www.earth-syst-dynam.net/4/187/2013/esd-4-187-2013.pdf |
| spellingShingle | F. Cresto Aleina V. Brovkin S. Muster J. Boike L. Kutzbach T. Sachs S. Zuyev A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams Earth System Dynamics |
| title | A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams |
| title_full | A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams |
| title_fullStr | A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams |
| title_full_unstemmed | A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams |
| title_short | A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams |
| title_sort | stochastic model for the polygonal tundra based on poisson voronoi diagrams |
| url | http://www.earth-syst-dynam.net/4/187/2013/esd-4-187-2013.pdf |
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