An Optimization Algorithm for the Meteorological Data Assimilation Problem

Eva Eggeling () and Shlomo Ta’asan ()
Additional contact information
Eva Eggeling: Fraunhofer-lnstitute for Algorithms and Scientific Computing (SCAI)
Shlomo Ta’asan: Carnegie Mellon University, Department of Mathematical Sciences

A chapter in Recent Progress in Computational and Applied PDES, 2002, pp 171-181 from Springer

Abstract: Abstract The aim of this paper is to present an efficient optimization algorithm for solving the meteorological data assimilation problem. In our study this inverse problem is formulated as a constrained optimization problem. An accurate model for the problem involves the Navier-Stokes equations and in certain cases the Euler equations. In order to understand diverse intricate aspects of the problem we have focused on the Euler case and formulated three model problems which aim at tackling some of the basic difficulties faced in the real problem. We study the effect of dissipation in finite difference schemes on the identifiability in the problem. Basically, dissipation will result in bad estimation far from the measurement locations due to loss of information as the waves propagate. We demonstrate results for several cases, including the advection equation and a wave equation. For this purpose we use different measurement types in terms of the location of the measurements, the amount and noise level of the data.

Keywords: Constrained optimization; Data assimilation; Adjoint method; Condition number; Dissipation; Fourier analysis (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4615-0113-8_12

Ordering information: This item can be ordered from
http://www.springer.com/9781461501138

DOI: 10.1007/978-1-4615-0113-8_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().