Abstract
Understanding the future evolution of permafrost requires a better understanding of its climatological past. This requires permafrost models to efficiently simulate the thermal dynamics of permafrost over the past centuries to millennia, taking into account highly uncertain soil and snow properties. In this study, we present a computationally efficient numerical permafrost model which satisfactorily reproduces the current ground temperatures and active layer thicknesses of permafrost in the Arctic and their trends over recent centuries. The performed simulations provide insights into the evolution of permafrost since the 18th century and show that permafrost on the North American continent is subject to early degradation, while permafrost on the Eurasian continent is relatively stable over the investigated 300-year period. Permafrost warming since industrialization has occurred primarily in three "hotspot"regions in northeastern Canada, northern Alaska, and, to a lesser extent, western Siberia. We find that the extent of areas with a high probability (p3m>0.9) of near-surface permafrost (i.e., 3ĝ€¯m of permafrost within the upper 10ĝ€¯m of the subsurface) has declined substantially since the early 19th century, with loss accelerating during the last 50 years. Our simulations further indicate that short-Term climate cooling due to large volcanic eruptions in the Northern Hemisphere in some cases favors permafrost aggradation within the uppermost 10ĝ€¯m of the ground, but the effect only lasts for a relatively short period of a few decades. Despite some limitations, e.g., with respect to the representation of vegetation, the presented model shows great potential for further investigation of the climatological past of permafrost, especially in conjunction with paleoclimate modeling.
Original language | English |
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Pages (from-to) | 363-385 |
Number of pages | 23 |
Journal | Cryosphere |
Volume | 18 |
Issue number | 1 |
DOIs | |
Publication status | Published - 26 Jan 2024 |
Bibliographical note
Publisher Copyright:© 2024 Copernicus GmbH. All rights reserved.
Funding
Jan Nitzbon acknowledges support through the AWI INSPIRES program. Brian Groenke acknowledges the support of the Helmholtz Einstein International Berlin Research School in Data Science (HEIBRiDS). Sebastian Westermann acknowledges the support of the ESA Permafrost_CCI. We thank Vladimir Romanovsky for providing the long-term borehole temperature data from Alaska. We thank the two anonymous reviewers and the editor for their highly valuable comments and suggestions. They contributed greatly to the improvement of the paper. This research has been supported by the Bundesministerium für Bildung und Forschung (grant no. 01LN1709A) and Research Council of Norway (grant no. 301639). The article processing charges for this open-access publication were covered by the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung.
Funders | Funder number |
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ESA Permafrost_CCI | |
Helmholtz Einstein International Berlin Research School in Data Science | |
Bundesministerium für Bildung und Forschung | 01LN1709A |
Norges forskningsråd | 301639 |