North America

The oldest blocks that form the North American continent are of Archean age. This cratonic core is sourrounded by accreted terrains of progressively younger age. It is a long standing question  how the oldest, coldest and hence densest blocks have maintained buoyancy (Mooney & Kaban 2010).

The USArray Earthscope initiative is one of the largest interdisciplinary experiments to date. Consisting of several different deployments, the goal is cover the area of the United States uniformly with seismic and magnetotelluric stations. The site spacing is approximately 70 km with additional stations, so called flexible arrays, in areas of particular interest. The immense dataset and unique opportunity that this initiatives provides has sparked a tremendous number of publications and has resulted in comprehensive geophysical models for large parts of the continental US.

Despite this wealth of data, there are still differences in models between different methods and even models based on the same data. This is due to the ill-posed nature of the geophysical inverse problem, i.e. a multitude of models can fit the observations with the same degree of uncertainty. A prominent example of such a discrepancy are the published conductivity models in the region of the Yellowstone Hotspot. Zhdanov et al. (2011) published a model that shows significantly enhanced conductivities at depths between 100-300 km beneath Yellowstone that generally coincides in shape with the low velocity zone found in that area. Based on these results they interpret the enhanced conductivities as melt associated with hotspot activity. In contrast, Kelbert et al. (2012) and Meqbel et al. (2014) do not find evidence of such enhanced conductivities. In such situations, formal joint inversion with other data offers a possibility to resolve such ambiguities. Combining seismic, magnetotelluric and gravity data can enhance the resolution and reliability of the resulting models, as demonstrated in various case studies (e.g. Moorkamp 2011). Alternatively, we can use the joint inversion algorithm to test the hypothesis that all observations can be explained by structurally coincident features. Given the obvious advantages of an integrated approach and the suitability of the USArray data for such studies, it is highly surprising that to data no such analysis has been performed. This provides a significant opportunity for novel work with significant impact.