Robust Reconstruction of Historical Climate Change From Permafrost Boreholes

Brian Groenke*, Moritz Langer, Frederieke Miesner, Sebastian Westermann, Guillermo Gallego, Julia Boike

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Reconstructing historical climate change from deep ground temperature measurements in cold regions is often complicated by the presence of permafrost. Existing methods are typically unable to account for latent heat effects due to the freezing and thawing of the active layer. In this work, we propose a novel method for reconstructing historical ground surface temperature (GST) from borehole temperature measurements that accounts for seasonal thawing and refreezing of the active layer. Our method couples a recently developed fast numerical modeling scheme for two-phase heat transport in permafrost soils with an ensemble-based method for approximate Bayesian inference. We evaluate our method on two synthetic test cases covering both cold and warm permafrost conditions as well as using real data from a 100 m deep borehole on Sardakh Island in northeastern Siberia. Our analysis of the Sardakh Island borehole data confirms previous findings that GST in the region have likely risen by 5–9°C between the pre-industrial period of 1750–1855 and 2012. We also show that latent heat effects due to seasonal freeze-thaw have a substantial impact on the resulting reconstructed surface temperatures. We find that neglecting the thermal dynamics of the active layer can result in biases of roughly −1°C in cold conditions (i.e., mean annual ground temperature below −5°C) and as much as −2.6°C in warmer conditions where substantial active layer thickening (>200 cm) has occurred. Our results highlight the importance of considering seasonal freeze-thaw in GST reconstructions from permafrost boreholes.

Original languageEnglish
Article numbere2024JF007734
Pages (from-to)1-18
Number of pages18
JournalJournal of Geophysical Research: Earth Surface
Volume129
Issue number7
Early online date9 Jul 2024
DOIs
Publication statusPublished - Jul 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors.

Keywords

  • bayesian
  • borehole
  • climate reconstruction
  • inversion
  • numerical modeling
  • permafrost

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