Application of optimal data assimilation techniques in oceanography

Miller, R N

Title: Application of optimal data assimilation techniques in oceanography

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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.

Authors:

Miller, R N ^[1]

Oregon State Univ., Corvallis, OR (United States)

Publication Date:: Tue Dec 31 00:00:00 EST 1996

OSTI Identifier:: 505182

Report Number(s):: CONF-9207256-Vol.79
CNN: Contract N00014-90-J-1125;Grant OCE8800004; TRN: 97:003314-0015

Resource Type:: Conference

Resource Relation:: Conference: IMA summer program on mathematical, computational, and statistical analyses in environmental studies, Minneapolis, MN (United States), 6-31 Jul 1992; Other Information: PBD: 1996; Related Information: Is Part Of Environmental studies: Mathematical, computational, and statistical analysis; Wheeler, M.F. [ed.] [Rice Univ., Houston, TX (United States)]; PB: 414 p.

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; OCEANOGRAPHY; DATA COMPILATION; DATA ANALYSIS; STATISTICAL MODELS

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                    Miller, R N. Application of optimal data assimilation techniques in oceanography.  United States: N. p., 1996. 
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                    Miller, R N. Application of optimal data assimilation techniques in oceanography.  United States.

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                    Miller, R N. 1996.  
        "Application of optimal data assimilation techniques in oceanography".  United States.

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@article{osti_505182,

  title        = {Application of optimal data assimilation techniques in oceanography},

  author       = {Miller, R N},

  abstractNote = {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.},

  doi          = {},

  url          = {https://www.osti.gov/biblio/505182},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Dec 31 00:00:00 EST 1996},

  month        = {Tue Dec 31 00:00:00 EST 1996}

}

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