Crustal structure controls geothermal heat flux which is a key basal boundary conditions for ice-sheet flow in Antarctica. The crustal thickness of Antarctica is well resolved at large-scale, but the smaller-scale structures and density variations in the crust remain poorly constrained. Using 3D gravity inversion constrained by seismic Moho estimates, we model crustal structure in Antarctica, resolving sedimentary basin thickness and density, crustal density and internal layering, and the Moho. Spatial variations in upper crustal density are mapped to radiogenic heat production using a petrophysically-defined mapping approach. Significant variations are observed averaging 1.2 to 1.6 µW/m3, and as high as 2 µW/m3 in West Antarctica. The crustal contribution to geothermal heat flow is similarly variable averaging 18 to 27 mW/m2 and could be up to 60 mW/m2. The mapped variations are significant for correctly representing heat flow in Antarctica.

A document by Alan R.A. Aitken. Click on the document to view its contents.

Antarctica’s geothermal heat flow and its glacial isostatic adjustment response are critical to understand ice sheet stability. These demand a knowledge of the temperature of the Antarctic lithosphere, but challenges remain in resolving mantle thermomechanical properties. Here we use a two-stage process to resolve mantle temperature and composition. First, we derive an optimized relationship between shear-wave velocity and temperature, density, and composition, constrained by temperature, attenuation, and the average viscosity of the oceanic upper mantle. Applying this conversion relationship to a seismic shear-wave velocity model from adjoint tomography (ANT-20) yields an estimate of mantle density and temperature. In the second stage we apply a 3D finite-element-method gravity inversion to correct density distribution for the Antarctic lithosphere. The updated density structure further constrains the composition and so the temperature of the lithospheric mantle. Factoring in changes in mantle composition, areas with depleted mantle require a higher temperature than the initial estimate to fit the seismic velocity and density structure. Compared with a primitive mantle, the temperature in the depleted mantle is increased by up to 200 °C. From the updated temperature field, changes to the lithosphere thickness, mantle viscosity, and geothermal heat flow are defined: in East Antarctica, low viscosity area is largely unchanged (<1023 Pa s), while the estimated lithosphere thickness must decrease by up to 150 km, and heat flow must increase by 3–10 mW/m2. Collectively, the effects of an increased mantle temperature estimate suggest that a more dynamic and climate-responsive East Antarctic Ice Sheet is possible.

High-quality aeromagnetic data are important in guiding new knowledge of the solid earth in frontier regions, such as Antarctica, where these data are often among the first data collected. The difficulties of data collection in remote regions often lead to less than ideal data collection, leading to data that are sparse and four-dimensional in nature. Standard aeromagnetic data collection procedures are optimised for the (nearly) 2D data that are collected in industry-standard surveys. In this work we define and apply a robust magnetic data correction approach that is optimised to these four dimensional data. Data are corrected in three phases, first with operations on point data, correcting for spatio-temporal geomagnetic conditions, then operations on line data, adjusting for elevation differences along and between lines and finally a line-based levelling approach to bring lines into agreement while preserving data integrity. For a large-scale East Antarctic survey, the overall median cross-tie error reduction error reduction is 93%, reaching a final median error of 5 nT. Error reduction is are spread evenly between phase 1 and phase 3 levelling operations. Phase 2 does not reduce error directly but permits a stronger error reduction in phase 3. Residual errors are attributed to limitations in the ability to model 4D geomagnetic conditions and also some limitations of the inversion process used in phase 2. Data have improved utility for geological interpretation and modelling, in particular quantitative approaches, which are enabled with less bias and more confidence.

Knowing the heterogeneous crustal structure is essential for understanding the ice dynamics, glacial isostatic adjustment (GIA) and tectonic history in Antarctica. For example, geothermal heat flux (GHF) is a major boundary condition for ice dynamics and the crust thickness and its composition (mafic or felsic) are important factors in GHF. Meanwhile, the GIA signal and its gravity response are essential for detecting mass-balance change and predicting future sea-level change. Errors in the density model used, which may be over 10%, will propagate into the gravity calculations. In this study, we use gravity inversion constrained by seismic depth estimation to recover the heterogeneous crustal structure of Antarctica, and estimate its uncertainties. Specifically, we modify by inversion the density of the uppermost mantle, the crustal density, the Moho depth, and the sedimentary cover thickness with an ensemble model with different density/geometry variation constraints. The output models indicate the most representative model of Antarctic crustal structure within the capacity of the method and current data constraints. Our preliminary results show that crustal density varies between 2.75 to 2.95 g/cm3 while the Moho depth varies between 22 km in Ross Ice Shelf and 54 km in Gamburtsev Subglacial Mountains. Low-density sedimentary basins are modelled at up to 10 km thickness beneath the ice shelf, and 3 km inland of Antarctica. Model also shows mantle density varies from 3.25 to 3.35 g/cm3. These density and thickness variations indicate likely substantial differences in crustal heat production, crustal rheology, and the expected GIA response of Antarctica’s crust.