Geophysical investigations and interactive visualizations of the Charlie-Gibbs Fracture Zone.

Abstract

Oceanic transform faults and their associated fracture zones are key constituents of tectonic processes and regions of high seismic activity. While they are of scientific interest, the remote nature and extreme ocean depths at these sites limits manual exploration and sample collection. This challenge has promoted the use of other methods of data collection and analysis such as satellite altimetry, ship depth-soundings, and computational modelling. Despite decades of study and large quantities of data, these features remain poorly understood. A common difficulty in analyzing these structures lies in the fact that many geophysical datasets are largely disjointed and often have incompatible resolutions and file formats. Additionally, some datasets must be derived from others or require processing in order to discern features of interest. This thesis aims to broaden our understanding of the Charlie-Gibbs Fracture Zone, an extensive structure found in the North-Atlantic Ocean. As the largest interruption of the Mid-Atlantic Ridge between Iceland and the Azores, this unique system of two parallel FZs is of particular interest to many geoscientists. Through the processing and compilation of several geophysical datasets, this study sought to find computational methods that could highlight key structural features, enhance small-scall anomalies, and allow hidden patterns to be seen. Freely available datasets for bathymetry, free-air gravity anomaly, and magnetic anomaly were downloaded and read into GMT (the general mapping tools), where they were converted to grid files and clipped to the study region. A bathymetric illumination grid was calculated using the directional derivative of the bathymetry grid, and the Bouguer anomaly was derived from the bathymetry and free-air gravity anomaly grids. Upward continuation and wavelength filtering were applied to both the free-air gravity anomaly and magnetic anomaly datasets, to compare the effects of the different processes and enhance small-scale anomalies and linear features. Transects across final datasets were sampled and intermediate values were interpolated to create profiles in Microsoft Excel. All resulting datasets were converted to netCDF files, from which raster layers were produced in ArcGIS Pro. This allowed the findings to be presented in a new and educational way: through the creation of an online interactive story map.