Optimizing Sensor Configurations for the Detection of Slow-Slip Earthquakes in Seafloor Pressure Records, Using the Cascadia Subduction Zone as a Case Study

We present seafloor pressure records from the Cascadia Subduction Zone, alongside oceanographic and geophysical models, to evaluate the spatial uniformity of bottom pressure and optimize the geometry of sensor networks for resolving offshore slow-slip transients. Seafloor pressure records from 2011 to 2015 show that signal amplitudes are depth-dependent, with tidally filtered and detrended root-mean-squares of 6 cm on the continental shelf. This is consistent with bottom pressure predictions from circulation models and comparable to deformation amplitudes from offshore slow slip observed in other subduction zones. We show that the oceanographic component of seafloor pressure can be reduced to <= 1-cm root-mean-square by differencing against a reference record from a similar depth, under restrictions that vary with depth. Instruments at 100-250 m require depths matched within 10 m at separations of <100 km, while locations deeper than 1,400 m are broadly comparable over separations of at least 300 km. Despite the significant noise reduction from this method, no slow slip was identified in the dataset, possibly due to poor spatiotemporal instrument coverage, nonideal deployment geometry, and limited depth-matched instruments. We use forward predictions of deformation from elastic half-space models and hindcast pressure from circulation models to generate synthetic slow-slip observational records and show that a range of slip scenarios produce resolvable signals under depth-matched differencing. For future detection of offshore slow slip in Cascadia, we recommend a geometry in which instruments are deployed along isobaths to optimize corrections for oceanographic signals.