A paper appearing in Geophysical Research Letters uses machine learning to craft an improved model for understanding geothermal heat flux—heat emanating from the Earth’s interior—below the Greenland Ice Sheet. It’s a research approach new to glaciology that could lead to more accurate predictions for ice-mass loss and global sea-level rise.