Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach

• Published in: Geophysical Research Letters
• Main Authors: Rezvanbehbahani, Soroush, Stearns, Leigh A., Kadivar, Amir, Walker, J. Douglas, van der Veen, Cornelis J.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: American Geophysical Union 2018
• Subjects: Greenland ice sheet; Geothermal heat flux; Machine learning; Greenland; Jakobshavn Isbræ; Nioghalvfjerdsfjorden; Petermann Gletscher; Stripe; East Greenland; glacier; ice core; Ice Sheet; Jakobshavn; Jakobshavn isbræ; North Greenland; Petermann gletscher
• Online Access: http://hdl.handle.net/1808/27385; https://doi.org/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 me...