A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams.
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dc.contributor.author | Cresto-Aleina, Fabio | |
dc.contributor.author | Brovkin, Victor | |
dc.contributor.author | Muster, Sina | |
dc.contributor.author | Boike, Julia | |
dc.contributor.author | Kutzbach, Lars | |
dc.contributor.author | Sachs, Torsten | |
dc.contributor.author | Zuyev, Sergey | |
dc.coverage.spatial | LATITUDE: 72.373760 * LONGITUDE: 126.488430 | |
dc.date.accessioned | 2019-11-23T02:00:46Z | |
dc.date.available | 2019-11-23T02:00:46Z | |
dc.date.issued | 2013-08-22 | |
dc.identifier | https://doi.pangaea.de/10.1594/PANGAEA.818292 | |
dc.identifier | https://doi.org/10.1594/PANGAEA.818292 | |
dc.identifier.citation | Cresto-Aleina, Fabio; Brovkin, Victor; Muster, Sina; Boike, Julia; Kutzbach, Lars; Sachs, Torsten; Zuyev, Sergey (2013): A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams. Earth System Dynamics, 4(2), 187-198, https://doi.org/10.5194/esd-4-187-2013 | |
dc.identifier.uri | https://repository.geologyscience.ru/handle/123456789/7028 | |
dc.description.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. | |
dc.format | text/tab-separated-values, 4 data points | |
dc.language.iso | en | |
dc.publisher | PANGAEA | |
dc.relation | Overview image, distance between polygon centroids (URI: hdl:10013/epic.41957.d003) | |
dc.rights | CC-BY-3.0: Creative Commons Attribution 3.0 Unported | |
dc.rights | Access constraints: unrestricted | |
dc.source | Supplement to: Cresto-Aleina, Fabio; Brovkin, Victor; Muster, Sina; Boike, Julia; Kutzbach, Lars; Sachs, Torsten; Zuyev, Sergey (2013): A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams. Earth System Dynamics, 4(2), 187-198, https://doi.org/10.5194/esd-4-187-2013 | |
dc.subject | AWI_PerDyn | |
dc.subject | File content | |
dc.subject | MULT | |
dc.subject | Permafrost Research (Periglacial Dynamics) @ AWI | |
dc.subject | Samoylov_Island_Cresto | |
dc.subject | Samoylov Island, Lena Delta, Siberia | |
dc.subject | Uniform resource locator/link to file | |
dc.title | A stochastic model for the polygonal tundra based on Poisson–Voronoi diagrams. | |
dc.title.alternative | Wet tundra polygon centers and distance between polygon centroids on Samoylov Island, Lena Delta, Siberia, Russia, with links to shape files | |
dc.type | Dataset |
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