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Subglacial heat flow is used as a boundary condition for ice sheet models and in understanding the tectonic development and properties of the lithosphere. Existing Antarctic heat flow estimates at continental scale are based on univariate modelling of a geothermal gradient and do not agree. Disparities arise from assumptions regarding lithospheric properties such as crustal heat production, upper mantle composition and dynamic neotectonics.

We employ a 'similarity approach' that compares Antarctic observables with observables linked to existing high-quality heat flow measurements from global compilations. Previous studies that use similarity to interpolate heat flow values elsewhere, utilise datasets that do not extend to the Antarctic interior with sufficient reliability. Here, we optimise the similarity approach for existing Antarctic geophysical and geological datasets by applying a careful sensitivity analysis and introduce weighting of observables. Observables used include topography, distance to volcanoes, geophysical data sets, and derived products such as depth to Curie temperature isotherm, seismic wave speed and curvature of gravity field. We also include geological observations. In total, 15 observables are used.

The new heat flow map, Aq1, is presented together with uncertainty and measures of information entropy in widely used formats. We also provide the complete workflow as open source Python code relying on the agrid package. The complete computational framework allows for testing of alternative inputs and updates as new data becomes available.

Item Type:	Conference Extract
Keywords:	heat flow, Antarctica, multivariate
Research Division:	Engineering
Research Group:	Fluid mechanics and thermal engineering
Research Field:	Computational methods in fluid flow, heat and mass transfer (incl. computational fluid dynamics)
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in the earth sciences
UTAS Author:	Staal, T (Dr Tobias Staal)
UTAS Author:	Reading, AM (Professor Anya Reading)
UTAS Author:	Halpin, J (Dr Jacqueline Halpin)
UTAS Author:	Whittaker, J (Associate Professor Jo Whittaker)
ID Code:	143900
Year Published:	2020
Deposited By:	Earth Sciences
Deposited On:	2021-04-09
Last Modified:	2021-06-18
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