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Without Bounds: A Scientific Canvas of Nonlinearity and Complex Dynamics pp 729–746Cite as

A Time-Space Description of the Analysis Produced by a Data Assimilation Method

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Part of the Understanding Complex Systems book series (UCS)

Abstract

The objective analysis of the upper ocean temperature field and its error covariance structure are discussed. The assimilation technique used to produce the analysis is based on the application of the Fokker-Planck equation. In the present study, the ocean general circulation model MOM3 from GFDL/NOAA and vertical profiles of temperature from the PIRATA observational array in the tropical Atlantic Ocean are utilised in conjunction with a data assimilation scheme. The results show that the analysis has warmer mixed layer than the model, and cooler temperatures immediately below the mixed layer. The analysis was compared with independent data. The structure of the analysis is assessed by an eigenvector expansion of the error covariance matrix. It is shown that the largest covariance is in the mixed layer, with maxima located around the observational points. Also, the covariance is relevant in a large area in the tropical Atlantic, showing the basin is dynamically linked.

Keywords

  • Mixed Layer
  • Kalman Filter
  • Data Assimilation
  • Ocean General Circulation Model
  • Assimilation Experiment

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. Shirshov Institute of Oceanology (SIORAS), Russian Academy of Science, Nakhimovsky 36, Moscow, 117799, Russia

    K. P. Belyaev

  2. Dept. Geophysics and Geology, Federal University of Bahia, CPGG, Campus Ondina, Travessa Barão de Jeremoabo, s/n, 40170-29, Salvador, BA, Brazil

    C. A. S. Tanajura

Authors
  1. K. P. Belyaev
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  2. C. A. S. Tanajura
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Corresponding author

Correspondence to K. P. Belyaev .

Editor information

Editors and Affiliations

  1. , Dpt. Quimica-Fisica-I, UCM, Madrid, 28040, Spain

    Ramon G. Rubio

  2. Instituto Pluridisciplinar, UCM, Paseo Juan XXIII 1, Madrid, 28040, Spain

    Yuri S. Ryazantsev

  3. , Dpt. of Chemical Engineering, Loughborough University, Loughborough, LE11 3TU, United Kingdom

    Victor M Starov

  4. , Physics Dpt., East China Normal University, Zhongshan Northern Road 3663, Shanghai, 200062, China, People's Republic

    Guo-Xiang Huang

  5. , Faculty of Physics, Saratov State University, Astrakhanskaya Str. 83, Saratov, 410012, Russia

    Alexander P Chetverikov

  6. , Dpt. di Ingegneria Elettrica Elettronica, Università di Catania, V. le A. Doria 6, Catania, 95125, Italy

    Paolo Arena

  7. , Dept. of Mathematics, Technion, Haifa, 32000, Israel

    Alex A. Nepomnyashchy

  8. , Instituto Cajal, CSIC, Av. Dr. Arce 37, Madrid, 28002, Spain

    Alberto Ferrus

  9. Shirshov Institute of Oceanology, Nakhimovsky prospekt 36, Moscow, 117851, Russia

    Eugene G. Morozov

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Belyaev, K.P., Tanajura, C.A.S. (2013). A Time-Space Description of the Analysis Produced by a Data Assimilation Method. In: Rubio, R., et al. Without Bounds: A Scientific Canvas of Nonlinearity and Complex Dynamics. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34070-3_52

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  • DOI: https://doi.org/10.1007/978-3-642-34070-3_52

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  • Online ISBN: 978-3-642-34070-3

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