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 temperatures (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 100m deep borehole on Sardakh Island
in northeastern Siberia. Our analysis of the Sardakh Island borehole
data confirms previous findings that ground surface temperatures in the
region have likely risen by 5 to 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 to
-1.5°C in cold conditions (i.e. mean annual ground temperature below
-5°C) and as much as -2 to -3°C in warmer conditions where substantial
active layer thickening (>200cm) has occurred. Our results
highlight the importance of considering seasonal freeze-thaw in GST
reconstructions from permafrost boreholes.