The Back and Forth Nudging algorithm for data assimilation problems : theoretical results on transport equations

¹ Laboratoire Dieudonné, Université de Nice Sophia Antipolis, Parc Valrose, 06108 Nice Cedex 2, France
auroux@unice.fr
² INRIA, Grenoble, France
³ Université de Grenoble, Laboratoire Jean Kuntzmann, UMR 5224, Grenoble, France
maelle.nodet@inria.fr

Received: 14 March 2010
Revised: 20 September 2010

Abstract

In this paper, we consider the back and forth nudging algorithm that has been introduced for data assimilation purposes. It consists of iteratively and alternately solving forward and backward in time the model equation, with a feedback term to the observations. We consider the case of 1-dimensional transport equations, either viscous or inviscid, linear or not (Burgers’ equation). Our aim is to prove some theoretical results on the convergence, and convergence properties, of this algorithm. We show that for non viscous equations (both linear transport and Burgers), the convergence of the algorithm holds under observability conditions. Convergence can also be proven for viscous linear transport equations under some strong hypothesis, but not for viscous Burgers’ equation. Moreover, the convergence rate is always exponential in time. We also notice that the forward and backward system of equations is well posed when no nudging term is considered.