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2018WCRPspon col July2018 01 1

S Westermann: Large-­‐scale monitoring of ground thermal condiFons through data fusion of remote sensing products


This presentation was held at the DUE Permafrost 2014 workshop, 11 Febuary 2014, Frascati, Italy


Westermann, Sebastian
Department of Geosciences, University of Oslo, Oslo Norway

Remote sensing of permafrost has mainly focused on the evaluation of surface features to indirectly assess its state, e.g. through detection of thaw slumps in VNIR or radar images. Recently, Langer et al. (2013) presented a scheme that can quantify the physical variables ground temperature and thaw depth based on global data sets from remote sensors and atmospheric modeling. This data fusion approach employing MODIS land surface temperatures (LST), MODIS snow extent (SE), and GlobSnow snow water equivalent (SWE) has now been operationalized for large areas at a spatial scale of 1 km by using the thermal subsurface model CryoGrid 2 (Westermann et al. 2013). First model runs are available for the Lena River Delta, an area of about 50,000 km2, for which the accuracy and the main sources of uncertainty of the scheme are evaluated. In a further step, we extend the scheme to mountainous permafrost regions where GlobSnow SWE data are not available by employing an orographic precipitation model to downscale large-scale precipitation fields from ERA reanalyis. The potential of this method is evaluated with CryoGrid 2 runs across the strong climatic gradients on Svalbard.

- 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, modeling, remote sensing, MODIS, land surface temperature, snow


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