Articles | Volume 20, issue 3
https://doi.org/10.5194/tc-20-1543-2026
https://doi.org/10.5194/tc-20-1543-2026
Research article
 | 
11 Mar 2026
Research article |  | 11 Mar 2026

Mapping Antarctic geothermal heat flow with deep neural networks optimized by particle swarm optimization algorithm

Shaoxia Liu, Xueyuan Tang, Shuhu Yang, Lijuan Wang, and Jianjie Liu

Data sets

Antarctic geothermal heat flow dataset: deep neural network generation optimized by particle swarm optimization algorithm Shaoxia Liu https://zenodo.org/records/18790294

Volcanoes of the World Global Volcanism Program https://doi.org/10.5479/si.GVP.VOTW5-2025.5.3

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Short summary
Heat from inside the Earth beneath Antarctica affects how fast ice melts and how quickly the sea level rises, but direct measurements are very limited. We built a data-driven computer model that learns the complex links between geophysical features and geothermal heat flow and reports confidence. We find lower heat flow in East Antarctica and higher heat flow in West Antarctica, especially near coasts.
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