Identification of bottom deformations of the ocean from surface measurements - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year : 2024

Identification of bottom deformations of the ocean from surface measurements

Abstract

In this paper we consider a general scheme to solve two different inverse problems related to oceanography, that is retrieving either a tsunami or the shape of the seabed from the measurement of the free surface perturbation. We consider two dimensional geometries and linear potential models in the frequency regime. Such general scheme consists in firstly recovering the potential in the whole domain and secondly compute the seeked parameter at the bottom of the ocean, which in the two inverse problems is a function involved in a more or less complicated boundary condition. The first step amounts to solve an ill-posed Cauchy problem for the Laplace or Helmholtz equation, which we regularize by using a mixed formulation of the Tikhonov regularization and the Morozov principle to compute the regularization parameter. The computation of such Tikhonov-Morozov solution is based on an iterative method consisting in solving a sequence of weak formulations which are discretized with the help of a simple Lagrange type Finite Element Method. In the particular case of the acoustic model, we need to solve a Laplace-type equation associated with the noisy Neumann boundary data and compute the noise amplitude of its solution. A probabilistic method is proposed to obtain such amplitude of noise. Some numerical experiments show the feasibility of our strategy.
Fichier principal
Vignette du fichier
water_waves_PI_ter.pdf (875.78 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04514543 , version 1 (21-03-2024)

Licence

Attribution

Identifiers

  • HAL Id : hal-04514543 , version 1

Cite

Laurent Bourgeois, Jean-François Mercier, Raphaël Terrine. Identification of bottom deformations of the ocean from surface measurements. 2024. ⟨hal-04514543⟩
11 View
10 Download

Share

Gmail Facebook X LinkedIn More