On Tuesday, the team successfully executed the last of seven daring orbit correction maneuvers that kept MESSENGER aloft long enough for the spacecraft's instruments to collect critical information on Mercury's
crustal magnetic anomalies and ice - filled polar craters, among other features.
Using all available geologic, tectonic and geothermal heat flux data for Greenland — along with geothermal heat flux data from around the globe — the team deployed a machine learning approach that predicts geothermal heat flux values under the ice sheet throughout Greenland based on 22 geologic variables such as bedrock topography,
crustal thickness,
magnetic anomalies, rock types and proximity to features like trenches, ridges, young rifts, volcanoes and hot spots.