Spatially dependent parameter estimation and nonlinear data assimilation by autosynchronization of a system of partial differential equations

Sean Kramer; Erik M Bollt

doi:10.1063/1.4812722

Spatially dependent parameter estimation and nonlinear data assimilation by autosynchronization of a system of partial differential equations

Chaos. 2013 Sep;23(3):033101. doi: 10.1063/1.4812722.

Authors

Sean Kramer¹, Erik M Bollt

Affiliation

¹ Department of Mathematics, Clarkson University, Potsdam, New York 13669, USA.

PMID: 24089937
DOI: 10.1063/1.4812722

Abstract

Given multiple images that describe chaotic reaction-diffusion dynamics, parameters of a partial differential equation (PDE) model are estimated using autosynchronization, where parameters are controlled by synchronization of the model to the observed data. A two-component system of predator-prey reaction-diffusion PDEs is used with spatially dependent parameters to benchmark the methods described. Applications to modeling the ecological habitat of marine plankton blooms by nonlinear data assimilation through remote sensing are discussed.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Algorithms
Animals
Data Interpretation, Statistical
Ecology / methods
Ecosystem
Models, Statistical
Nonlinear Dynamics*
Oceans and Seas
Phytoplankton / physiology
Plankton
Population Dynamics
Predatory Behavior
Remote Sensing Technology / methods
Satellite Imagery
Signal Processing, Computer-Assisted
Species Specificity
Zooplankton / physiology