The flexure of elastic plates is a central concept in the theory of plate tectonics, where the Earth’s lithosphere (crust and uppermost mantle) reacts to transverse applied loads by bending, a process referred to as flexural isostasy. Estimating the effective elastic thickness (\(T_e\)) of the lithosphere (thickness of an equivalent ideal elastic plate) gives important clues on the rheology of the lithosphere and its thermal state. Estimating \(T_e\) is typically done by modeling the cross-spectral properties (admittance and coherence) between topography and gravity anomaly data, which are proxies for the distribution of flexurally compensated surface and subsurface loads.

This package contains python and fortran modules to calculate the wavelet spectral and cross-spectral quantities of 2D gridded data of topography and gravity anomalies. Once obtained, the wavelet cross-spectral quantities (admittance and coherence) are used to determine the parameters of the effectively elastic plate, such as the effective elastic thickness (\(T_e\)), the initial subsurface-to-surface load ratio (\(F\)) and optionally the initial phase difference between surface and subsurface loads (\(\alpha\)). The estimation can be done using non-linear least-squares or probabilistic (i.e., bayesian) inference methods. The analysis can be done using either the Bouguer or Free air gravity anomalies, and over land or ocean areas. Computational workflows are covered in the Jupyter notebooks bundled with this package. The software contains methods to make publication-quality plots using the seaborn package.


The cross-spectral quantities calculated here are the real-valued admittance and squared-real coherency, as discussed in the references

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