| Summary: | Heat generated in the interior of the Earth provides an indication of tectonic history and lithospheric architecture. In the case of the Antarctic continent, it has an additional importance, as even moderate amounts of geothermal heat transfer impact the thermo-mechanic properties of the ice sheets. In some locations, such geothermal heat is expected to cause basal melting. There are few direct measurements of heat in Antarctica, and due to the large variability, interpolation cannot resolve the spatial distribution. Constraining heat from a temperature gradient derived from univariate geophysical datasets produces contradicting results and depends on unconstrained assumptions. As expected, given the limited data available, the understanding of the thermal properties of Antarctica is far less evolved than for any other continent. We present the multivariate geothermal heat flow model, Aq1, generated from a similarity detection approach of 17 Antarctic observables, and draft the sequential model Aq2, with further improved robustness and uncertainty metrics. Aq1 provides new details in East Antarctica. Low heat flow values around 40mW/m2 are suggested in Wilks Subglacial Basin, Shackleton Range and coastal Dronning Maud Land. The model also suggests elevated heat flow over 70mW/m2 around Gamburtsev Subglacial Mountains, in Queen Mary Land and near the South Pole. However, those suggestions are associated with large uncertainty ranges. Aq2 provides an opportunity to constrain the ambiguities and further improve the robustness. We refine the model parameters by optimizing information entropy and cross-correlated misfit. Aq2 takes advantage of latest seismic tomography models, geological observations and multivariate segmentation. Including higher-resolution tomography improves the spatial resolution of the model result, especially in coastal regions. By comparing Aq2 with calculated maps of steady-state heat flow and other models, we also provide an estimate of the contributing mechanisms that cause excess geothermal heat. We infer the most likely additions from crustal heat production, exhumation, neotectonics and heat transfer from the mantle. Our computational framework is available as an open source resource for the benefit of the solid-Earth and interdisciplinary research communities.
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