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

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.; Romanovskyh, Vladimir; Wayk, Robert G.; Westergaard-Nielsen, Andreas; Wu, Tonghua; Yamkhin, Jambaljav; Zou, Defu

doi:10.1016/j.earscirev.2019.04.023

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

Obu, Jaroslav Department of Geosciences, University of Oslo, Norway
Westermann, Sebastian Department of Geosciences, University of Oslo, Norway
Bartsch, Annett Zentralanstalt für Meteorologie und Geodynamik, Wien, Austria
Berdnikov, Nikolai Earth Cryosphere Institute, Tyumen Scientific Center, Russian Academy of Sciences, Siberian Branch, Tyumen, Russia
Christiansen, Hanne H. Arctic Geology Department, The University Centre in Svalbard, Longyearbyen, Norway
Dashtseren, Avirmed Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia
Delaloye, Reynald Geography Unit, Department of Geosciences, University of Fribourg, Switzerland
Elberling, Bo Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark
Etzelmüller, Bernd Department of Geosciences, University of Oslo, Norway
Kholodov, Alexander Geophysical Institute, University of Alaska Fairbanks, Fairbanks, USA
Khomutov, Artem Earth Cryosphere Institute, Tyumen Scientific Center, Russian Academy of Sciences, Siberian Branch, Tyumen, Russia
Kääb, Andreas Department of Geosciences, University of Oslo, Norway
Leibman, Marina O. Earth Cryosphere Institute, Tyumen Scientific Center, Russian Academy of Sciences, Siberian Branch, Tyumen, Russia
Lewkowicz, Antoni G. Department of Geography, Environment and Geomatics, University of Ottawa, Canada
Panda, Santosh K. Geophysical Institute, University of Alaska Fairbanks, Fairbanks, USA
Romanovskyh, Vladimir Department of Cryosophy, Tyumen State University, Tyumen, Russia
Wayk, Robert G. Labrador Institute, Memorial University of Newfoundland, Happy Valley-Goose Bay, Canada
Westergaard-Nielsen, Andreas Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark
Wu, Tonghua Cryosphere Research Station on Qinghai–Xizang Plateau, Northwest Institute of Eco–Environment and Resources (NIEER), Lanzhou, Gansu, China
Yamkhin, Jambaljav Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia
Zou, Defu Cryosphere Research Station on Qinghai–Xizang Plateau, Northwest Institute of Eco–Environment and Resources (NIEER), Lanzhou, Gansu, China

01.06.2019

Published in:

Earth-Science Reviews. - 2019, vol. 193, p. 299–316

English 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 °C) covers 13.9 × 106 km2 (ca. 15% of the exposed land area), which is within the range or slightly below the average of previous estimates. The sum of all pixels having isolated patches, sporadic, discontinuous or continuous permafrost (permafrost probability >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.

Faculty

Faculté des sciences et de médecine

Department

Département de Géosciences

Language