EGU24-7800, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-7800
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Seafloor topography recovery improved by combination of different gravity data functionals

david fuseau1,2, Lucia Seoane2,3, Guillaume Ramillien1,2, José Darrozes2,3, Bastien Plazolles1,2, Didier Rouxel4, Thierry Schmitt4, and Corinne Salaün4
david fuseau et al.
  • 1CNRS, Toulouse, France (david.fuseau@get.omp.eu)
  • 2Geophysique Environnement Toulouse (GET), Observatoire Midi-Pyrénées (OMP), Toulouse, France
  • 3Université Toulouse iii-Paul Sabatier, Toulouse, France
  • 4Service Hydrographique et Océanographique de la Marine (SHOM), Brest, France

Tesseroid and radial columns decomposition of the undersea relief strategies have been considered to recover the seafloor topography by Kalman Filter (KF) inversion of gravity data in the case of the Great Meteor seamount located in the North Atlantic ocean. These both modeling approaches are shown to be equivalent at high grid sampling rate (<1'). Different types of gravity data functionals for geoid height anomaly, vertical gravity component and gravity gradient (or tensor) are analyzed by spectral decomposition and combined to retrieve most detailed 3-D seafloor topography solutions, as gravity gradient data provide short-wavelength information to have access to high-resolution details. Besides only the vertical gravity tensor Vzz is usually inverted in previous field-related studies, considering up to six components of the gravity gradient is tested for improving the accuracy of the KF solution. The iterative KF scheme has been optimized and parallelized using C++ Armadillo software to accelerate the determination of a very large number of juxtaposed topographic heights.

How to cite: fuseau, D., Seoane, L., Ramillien, G., Darrozes, J., Plazolles, B., Rouxel, D., Schmitt, T., and Salaün, C.: Seafloor topography recovery improved by combination of different gravity data functionals, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7800, https://doi.org/10.5194/egusphere-egu24-7800, 2024.