EGU24-9318, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-9318
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Fast seafloor topography mapping of large oceanic provinces by optimization/parallelization

Lucia Seoane1, David Fuseau2, Guillaume Ramillien2, José Darrozes1, Bastien Plazolles2, Didier Rouxel3, Corinne Salaün3, and Thierry Schmitt3
Lucia Seoane et al.
  • 1Paul Sabatier University, GET, Toulouse, France
  • 2CNRS, Géosciences Environnement Toulouse (GET), Observatoire Midi-Pyrénées (OMP),Toulouse, France
  • 3Service Hydrographique et Océanographique de la Marine (Shom), Brest, France

During the last decades, several inversion approaches have been proposed to derive sea floor topography from satellite-based gravity data. Unfortunately, the most accurate non linear ones are based on iterative schemes that remain very time-consuming, especially if the number of topographic heights to be fitted is very important, e.g. when the oceanic domain is large and/or the gravity data is geographically dense and thus the maximum grid resolution to be accessible is high. Our strategy of computation is to decompose the total area into geographical cells that are overlapped to cancel the edge effects. The reference ocean depth given by GEBCO and the elastic thickness for regional compensation in function of the square root of the age of the oceanic crust are assumed to be constant in each cell. The initial inversion code has been translated into C++ and optimized using Armadillo software and LAPACK library to obtain a gain of speed of 1000 for a large region such as the complete North Atlantic Ocean (-54,-26,18,37). Post-fit and absolute errors are typically less than 200 m and 50 m r.m.s. respectively. These new detailed maps of bathymetry represent a precious source of information for geophysical applications. 

How to cite: Seoane, L., Fuseau, D., Ramillien, G., Darrozes, J., Plazolles, B., Rouxel, D., Salaün, C., and Schmitt, T.: Fast seafloor topography mapping of large oceanic provinces by optimization/parallelization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9318, https://doi.org/10.5194/egusphere-egu24-9318, 2024.