Supplementary material for "Real-time probabilistic tsunami forecasting in Cascadia from sparse offshore pressure observations"

This repository contains supplementary files for the GRL submission "Real-time probabilistic tsunami forecasting in Cascadia from sparse offshore pressure observations" by Stefan Henneking, Fabian Kutschera, Sreeram Venkat, Alice-Agnes Gabriel, and Omar Ghattas. The repository contains the following folders: Cascadia_3DFullyCoupledEarthquakeTsunami.zip seissol: Input files necessary to run fully-coupled SeisSol simulations for the margin-wide (Model 16) and partial (Model 2) rupture scenario mesh: 3D unstructured mesh with and without the ocean acoustic water layer movies: Slip rate for the margin-wide and partial rupture scenario Sea surface height anomaly (ssha) generated by the margin-wide and partial rupture scenario Vertical particle velocity at the sea surface and seafloor for the margin-wide and partial rupture scenario Cascadia_3DAcousticGravityInversion.zip coordinates: Input files (csv) specifying the (x,y,z) ocean bottom coordinates (ECEF) of the hypothesized sensor configurations (600 sensors, 175 sensors) Input file (csv) specifying the (x,y,z) ocean surface coordinates (ECEF) of the hypothesized tsunami forecasting locations (21 coordinates) mesh: 2D unstructured mesh (vtu) file of the ocean bottom (in ECEF coordinates) used for discretizing the seafloor velocity field in the acoustic–gravity model movies: Two movies (mp4) showing the seafloor normal displacement fields over the 420-second simulation time for the partial rupture and margin-wide rupture scenario. Each movie depicts side-by-side the "ground truth" displacements (computed by the fully-coupled SeisSol forward model simulations) and the inferred displacements obtained from the acoustic–gravity model inversion using synthetic ocean bottom pressure data from two hypothetical sensor configurations of 600 and 175 sensors. Note that the fully-coupled dynamic rupture and tsunami simulations are based on two dynamic rupture-only models of Glehman et al. (2024).