This presentation was held at the DUE Permafrost 2014 workshop, 12th of Febuary 2014, Frascati, Italy
Workshop: climate-cryosphere.org/meetings/due-permafrost-2014

Peter, Maria
University of Oslo, University of Leipzig, Oslo Norway
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Permafrost soils of the climatically sensitive region of the northeast Siberian lowlands contain large amounts of carbon, but monitoring the thermal ground conditions and predicting its future is challenging for such vast areas. Recently, a permafrost modeling scheme based on remote sensing data has been demonstrated for the Samoylov Island permafrost observatory (Langer et al. 2013). We extend this scheme to the entire Lena River Delta, in a first step focusing on the current state of permafrost temperatures. The transient permafrost model CryoGrid2 (Westermann et al. 2013) based on the heat transfer equation is used to calculate the evolution of the soil temperature profile for each grid cell. The model is forced with MODIS land surface temperature (1x1 km) and snow depth (1x1 km) compiled from the Snow extent product of MODIS (0.5x0.5 km) and the Snow water equivalent (SWE) product of GlobSnow (25x25 km). For the soil domain of the model we identified three stratigraphic classes that differ in volumetric mineral, water/ice and organic content and porosity. The sources for the construction of this stratigraphic classification are publications on sedimentology, geomorphology and geology of the Lena River Delta, as well as vegetation classification studies. After evaluating the results for Lena River Delta the study area will be extended to the lowland areas of Northeast Siberia, an area of on the order of 106 sqkm.

References:
- Langer, M., Westermann, S., Heikenfeld, M., Dorn, W., Boike, J.: Satellite-based modeling of permafrost temperatures in a tundra lowland landscape, Remote Sensing of Environment, 135, 12-24, 2013.
- Westermann, S., Schuler, T. V., Gisnås, K., and Etzelmüller, B.: Transient thermal modeling of permafrost conditions in Southern Norway, The Cryosphere, 7, 719-739, doi:10.5194/tc-7-719-2013, 2013.

Keywords: permafrost remote sensing MODIS GlobSnow numerical modeling soil science

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