Pan-Antarctic map of near-surface permafrost temperatures at 1 km2 scale

Permafrost is present within almost all of the Antarctic's ice-free areas, but little is known about spatial variations in permafrost temperatures except for a few areas with established ground temperature measurements. We modelled a temperature at the top of the permafrost (TTOP) for all the i...

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Bibliographic Details
Published in:The Cryosphere
Main Authors: Obu, Jaroslav, Westermann, Sebastian, Vieira, Gonçalo, Abramov, Andrey, Balks, Megan Ruby, Bartsch, Annett, Hrbáček, Filip, Kääb, Andreas, Ramos, Miguel
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications under license by EGU – European Geosciences Union GmbH 2020
Subjects:
Ice
Online Access:http://hdl.handle.net/10852/81067
http://urn.nb.no/URN:NBN:no-84160
https://doi.org/10.5194/tc-14-497-2020
Description
Summary:Permafrost is present within almost all of the Antarctic's ice-free areas, but little is known about spatial variations in permafrost temperatures except for a few areas with established ground temperature measurements. We modelled a temperature at the top of the permafrost (TTOP) for all the ice-free areas of the Antarctic mainland and Antarctic islands at 1 km2 resolution during 2000–2017. The model was driven by remotely sensed land surface temperatures and downscaled ERA-Interim climate reanalysis data, and subgrid permafrost variability was simulated by variable snow cover. The results were validated against in situ-measured ground temperatures from 40 permafrost boreholes, and the resulting root-mean-square error was 1.9 ∘C. The lowest near-surface permafrost temperature of −36 ∘C was modelled at Mount Markham in the Queen Elizabeth Range in the Transantarctic Mountains. This is the lowest permafrost temperature on Earth, according to global-scale modelling results. The temperatures were most commonly modelled between −23 and −18 ∘C for mountainous areas rising above the Antarctic Ice Sheet and between −14 and −8 ∘C for coastal areas. The model performance was good where snow conditions were modelled realistically, but errors of up to 4 ∘C occurred at sites with strong wind-driven redistribution of snow.