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Russian Journal of Numerical Analysis and Mathematical Modelling

Editor-in-Chief: Dymnikov, Valentin P. / Kuznetsov, Yuri

Managing Editor: Vassilevski, Yuri V.

Editorial Board: Agoshkov, Valeri I. / Amosov, Andrey A. / Kaporin, Igor E. / Kobelkov, Georgy M. / Mikhailov, Gennady A. / Repin, Sergey I. / Shaidurov, Vladimir V. / Shokin, Yuri I. / Tyrtyshnikov, Eugene E.

IMPACT FACTOR 2018: 0.779

CiteScore 2018: 0.92

SCImago Journal Rank (SJR) 2018: 0.512
Source Normalized Impact per Paper (SNIP) 2018: 1.275

Mathematical Citation Quotient (MCQ) 2018: 0.08

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Volume 22, Issue 2


On error covariances in variational data assimilation

I. Gejadze
  • Department of Civil Engineering, University of Strathclyde, 107 Rottenrow, Glasgow, G4 ONG, UK
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ F.-X. Le Dimet
  • MOISE project (CNRS, INRIA, UJF, INPG); LMC-IMAG, Université Joseph Fourier, BP 51, 38051 Grenoble Cedex 9, France
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ V. Shutyaev
Published Online: 2007-05-31 | DOI: https://doi.org/10.1515/RJNAMM.2007.008

The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function. The equation for the error of the optimal solution (analysis) is derived through the statistical errors of the input data (background and observation errors). The numerical algorithm is developed to construct the covariance operator of the analysis error using the covariance operators of the input errors. Numerical examples are presented.

About the article

Published Online: 2007-05-31

Published in Print: 2007-05-23

Citation Information: Russian Journal of Numerical Analysis and Mathematical Modelling rnam, Volume 22, Issue 2, Pages 163–175, ISSN (Online) 1569-3988, ISSN (Print) 0927-6467, DOI: https://doi.org/10.1515/RJNAMM.2007.008.

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