@ARTICLE\{IMM2008-05586,
    author       = "P. G. Thomsen and Z. Zlatev",
    title        = "Development of a data assimilation algorithm.",
    year         = "2008",
    keywords     = "Scientific Models, Splitting techniques, Systems of {PDE'}s, Systems of {ODE'}s, Stiffness, Accuracy, Data assimilation",
    pages        = "2381-2393",
    journal      = "Computers and Mathematics with Applications",
    volume       = "55",
    editor       = "",
    number       = "",
    publisher    = "Elsevier Ltd.",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/5586-full.html",
    abstract     = "It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be  used in the attempts to utilize efficiently observations in a large-scale model (for example, in order to obtain more reliable initial values). Variational data assimilation techniques are based on a combination of three very important components 
• numerical methods for solving differential equations, 
• splitting procedures 
• optimization algorithms. 
It is crucial to select an optimal (or, at least, a good) combination of these three components, because models which are very 
expensive computationally will become much more expensive (the computing time being often increased by a factor greater than 100) when a variational data assimilation technique is applied. Therefore, it is important to study the interplay between the three components of the variational data assimilation techniques as well as to apply powerful parallel computers in the computations. 
Some results obtained in the search for a good combination of numerical methods, splitting techniques and optimization algorithms will be reported. Parallel techniques described in [V.N. Alexandrov, W. Owczarz, P.G. Thomsen, Z. Zlatev, Parallel runs of a large air pollution model on a grid of Sun computers, Mathematics and Computers in Simulation, 65 (2004) 557–577] are used in the runs."
}