Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale

• Published in: Earth-science reviews 2019-06, Vol.193, p.299-316
• Main Authors: Obu, Jaroslav, Westermann, Sebastian, Bartsch, Annett, Berdnikov, Nikolai, Christiansen, Hanne H., Dashtseren, Avirmed, Delaloye, Reynald, Elberling, Bo, Etzelmüller, Bernd, Kholodov, Alexander, Khomutov, Artem, Kääb, Andreas, Leibman, Marina O., Lewkowicz, Antoni G., Panda, Santosh K., Romanovsky, Vladimir, Way, Robert G., Westergaard-Nielsen, Andreas, Wu, Tonghua, Yamkhin, Jambaljav, Zou, Defu
• Format: Article
• Language: English
• Subjects: Cryosphere; Essential climate variable; Frozen ground; Ground temperatures; Permafrost; Permafrost map; Remote sensing
• ISSN: 0012-8252; 1872-6828
• DOI: 10.1016/j.earscirev.2019.04.023

Permafrost is a key element of the cryosphere and an essential climate variable in the Global Climate Observing System. There is no remote-sensing method available to reliably monitor the permafrost thermal state. To estimate permafrost distribution at a hemispheric scale, we employ an equilibrium state model for the temperature at the top of the permafrost (TTOP model) for the 2000–2016 period, driven by remotely-sensed land surface temperatures, down-scaled ERA-Interim climate reanalysis data, tundra wetness classes and landcover map from the ESA Landcover Climate Change Initiative (CCI) project. Subgrid variability of ground temperatures due to snow and landcover variability is represented in the model using subpixel statistics. The results are validated against borehole measurements and reviewed regionally. The accuracy of the modelled mean annual ground temperature (MAGT) at the top of the permafrost is ±2 °C when compared to permafrost borehole data. The modelled permafrost area (MAGT 0) is around 21 × 106 km2 (22% of exposed land area), which is approximately 2 × 106 km2 less than estimated previously. Detailed comparisons at a regional scale show that the model performs well in sparsely vegetated tundra regions and mountains, but is less accurate in densely vegetated boreal spruce and larch forests.