By Soroush Rezvanbehbahani et al
Geophysical Research Letters, Volume 44, Issue 21,
DOI: 10.1002/2017GL075661
Geothermal heat flux (GHF) is a crucial boundary condition for making accurate predictions of ice sheet mass loss, yet it is poorly known in Greenland due to inaccessibility of the bedrock. Here we use a machine learning algorithm on a large collection of relevant geologic features and global GHF measurements, and produce a GHF map in Greenland which we argue is within ∼15% accuracy.
The main features of our predicted GHF map include a large region with high GHF in central-north Greenland surrounding the NorthGRIP ice core site, and hotspots in the Jakobshavn Isbræ catchment, upstream of Petermann Gletscher, and near the terminus of Nioghalvfjerdsfjorden glacier.
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