Multivariate autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Nonlinear Processes in Geophysics Année : 2006

Multivariate autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry

Résumé

This work addresses the autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry mission. Datasets from remote sensing applications are typically very large and correlated both in time and space. Multivariate analysis methods are useful tools to summarise and extract information from such large space-time datasets. Multivariate autoregressive analysis is a generalisation of Principal Oscillation Pattern (POP) analysis, widely used in the geosciences for the extraction of dynamical modes by eigen-decomposition of a first order autoregressive model fitted to the multivariate dataset of observations. The extension of the POP methodology to autoregressions of higher order, although increasing the difficulties in estimation, allows one to model a larger class of complex systems. Here, sea level variability in the North Atlantic is modelled by a third order multivariate autoregressive model estimated by stepwise least squares. Eigen-decomposition of the fitted model yields physically-interpretable seasonal modes. The leading autoregressive mode is an annual oscillation and exhibits a very homogeneous spatial structure in terms of amplitude reflecting the large scale coherent behaviour of the annual pattern in the Northern hemisphere. The phase structure reflects the seesaw pattern between the western and eastern regions in the tropical North Atlantic associated with the trade winds regime. The second mode is close to a semi-annual oscillation. Multivariate autoregressive models provide a useful framework for the description of time-varying fields while enclosing a predictive potential.
Fichier principal
Vignette du fichier
npg-13-177-2006.pdf (587.74 Ko) Télécharger le fichier
Origine : Accord explicite pour ce dépôt
Loading...

Dates et versions

hal-00302723 , version 1 (18-06-2008)

Identifiants

  • HAL Id : hal-00302723 , version 1

Citer

S. M. Barbosa, M. E. Silva, M. J. Fernandes. Multivariate autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry. Nonlinear Processes in Geophysics, 2006, 13 (2), pp.177-184. ⟨hal-00302723⟩

Collections

INSU EGU
91 Consultations
145 Téléchargements

Partager

Gmail Facebook X LinkedIn More