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

“Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale” (2019), by Jaroslav Obu et al. Earth and Planetary Sciences research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Jaroslav Obu, Sebastian Westermann, Annett Bartsch, Nikolai Berdnikov, Hanne H. Christiansen, Dashtseren Avirmed, Reynald Delaloye, Bo Elberling, Bernd Etzelmüller, Alexander Kholodov et al.
- Published: April 25, 2019
- Field: Earth and Planetary Sciences
- DOI: https://doi.org/10.1016/j.earscirev.2019.04.023
- Source: https://doi.org/10.1016/j.earscirev.2019.04.023

## Abstract

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.

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