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\begin{document}

\title{Analysis of Lithospheric Stresses Using Satellite Gravimetry: Hypotheses
and Applications to North Atlantic}



\author[1]{Alexander Minakov}%
\author[1]{Sergei Medvedev}%
\affil[1]{Universitetet i Oslo Senter for Jordens utvikling og dynamikk}%


\vspace{-1em}



  
  \date{June 17, 2024}


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\begin{abstract}
A major source of lithospheric stresses is believed to be in variations
of surface topography and lithospheric density. The traditional approach
to stress estimation is based on direct calculations of the
Gravitational Potential Energy (GPE), the depth integrated density
moment of the lithosphere column. GPE is highly sensitive to density
structure which, however, is often poorly constrained. Density structure
of the lithosphere may be refined using methods of gravity modeling.
However, the resulted density models suffer from non-uniqueness of the
inverse problem. An alternative approach is to directly estimate
lithospheric stresses (depth integrated) from satellite gravimetry data.
Satellite gravity gradient measurements by the ESA GOCE mission ensures
a wealth of data for mapping lithospheric stresses if a link between
data and stresses or GPE can be established theoretically. Following
(Camelbeeck et al., 2013), we adopt the method that constrains
lithospheric stresses by direct utilization of the gravity gradient
tensor. For comparison, we use more traditional methods as well: (2) the
filtered geoid approach (e.g., Chase et al., 2002; Coblentz et al.,
2015), and (3) the direct thin-sheet approximation based on depth
integration of density moment (e.g., Medvedev, 2016). Whereas the last
two approaches (2)-(3) calculate GPE and utilize a computationally
expensive finite element mechanical modeling to calculate stresses, the
approach (1) uses a much simpler numerical treatment but requires
simplifying assumptions that yet to be tested. We applied all methods to
the North Atlantic region where reliable additional constraints are
available and tested results against the World Stress Map.%
\end{abstract}%



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