PyCurious: A Python module for computing the Curie depth from the magnetic anomaly.

Abstract

Our Python package, pycurious, ingests a map of the Earth’s magnetic anomaly and distributes the computation of Curie depth across multiple CPUs. pycurious implements the Tanaka, Okubo, & Matsubayashi (1999) and Bouligand, Glen, & Blakely (2009) methods for computing the thickness of a buried magnetic source. The former selects portions of the radial power spectrum in the low and high frequency domain to compute the depth of magnetic sources, while the latter fits an analytical solution to the entire power spectrum. We cast the Bouligand et al. (2009) method within a Bayesian framework to estimate the uncertainty of Curie depth calculations (Mather & Fullea, 2019). Common computational workflows and geospatial manipulation of magnetic data are covered in the Jupyter notebooks bundled with this package. The mapping module includes a set of functions that help to wrangle maps of the magnetic anomaly into a useful form for pycurious. Such an approach is commonly encountered for transforming global compilations of the magnetic anomaly, e.g., EMAG2 (Meyer, Saltus, & Chulliat, 2017), from latitudinal/longitudinal coordinates to a local projection in eastings/northings.