Abstract
Application of optimal data assimilation methods in oceanography is, if anything, more important than it is in numerical weather prediction, due to the sparsity of data. Here, a general framework is presented and practical examples taken from the author’s work are described, with the purpose of conveying to the reader some idea of the state of the art of data assimilation in oceanography. While no attempt is made to be exhaustive, references to other lines of research are included. Major challenges to the community include design of statistical error models and handling of strong nonlinearity.
This work was supported by ONR contract N00014-90-J-1125, NSF Grant OCE8800004 and the National Research Council through the Resident Research Associate program.
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© 1996 Springer-Verlag New York, Inc.
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Miller, R.N. (1996). Application of Optimal Data Assimilation Techniques in Oceanography. In: Wheeler, M.F. (eds) Environmental Studies. The IMA Volumes in Mathematics and its Applications, vol 79. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-8492-2_15
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DOI: https://doi.org/10.1007/978-1-4613-8492-2_15
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