Preconditioning Representer-based Variational Data Assimilation Systems: Application to NAVDAS-AR
Published In
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications
Document Type
Book Chapter
Publication Date
1-1-2009
Abstract
Assimilation of observations into numerical models has emerged as an essential modeling component in geosciences. This procedure requires the solution of large systems of linear equations. Solving these systems in “real-time” or “near-real-time” in a timely manner is still a computational challenge. This paper shows how new methods in computational linear algebra are used to “speed-up” the representer-based algorithm in a variety of assimilation problems, with particular application to the Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR) system.
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© Springer-Verlag Berlin Heidelberg 2009
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DOI
10.1007/978-3-540-71056-1_16
Persistent Identifier
http://archives.pdx.edu/ds/psu/20795
Publisher
Springer
Citation Details
Chua, B.S., Xu, L., Rosmond, T., Zaron, E.D. (2009). Preconditioning Representer-based Variational Data Assimilation Systems: Application to NAVDAS-AR. In: Park, S.K., Xu, L. (eds) Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71056-1_16